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Как запустить Qwen3.8-27B локально на RTX3090 (Win10)

На подготовку данной пошаговой инструкции меня вдохновил пост А все-таки Qwen3.8-27B — думает меньше и быстрее чем 3.6 от @rtrgdfb. При повторении действий по скачиванию и конвертации модели из этого поста я понял, что многие технические детали сокращены или не совсем очевидны при первом знакомстве, так как автор, на мой взгляд, ставил целью донести сообщение о том, что Qwen3.8-27B стала лучше, если правильно настроить параметры для средства запуска моделей llama_server (входит в llama.cpp). И вот как раз для новичков и интересующихся возможностями моделей, работающих локально на собственном компьютере, эти детали мне захотелось раскрыть подробнее, вместе с некоторым опытом преодоления возникающих типовых проблем при настройке модели и подготовке программ для нее.

Оглавление

Что даёт прочтение этой статьи?

В этой статье описывается подробная последовательность для Windows 10 и RTX3090 по установке всего необходимого программного обеспечения (Python, Git, CUDA Toolkit, CMake, MSVC, Ninja, OpenSSL), сборке llama.cpp из исходников с поддержкой GPU, скачивания модели Qwen3.8-27B с Hugging Face, её конвертации в формат GGUF и квантизации в Q4_K_M (чтобы она целиком поместилась в видеопамять GPU), а так же приведены параметры запуска для локального сервера llama.cpp с OpenAI-совместимым API и веб-интерфейсом, позволяющим общаться с моделью через чат в браузере. Каждый шаг сопровождается объяснением, зачем он нужен, что делает каждая команда и что означает каждый параметр у команды.

Стартовые условия и замечания перед началом работы:

  1. Конфигурация локального компьютера:
    Процессор: Intel Core i7-8700K, это шестиядерный процессор

    Оперативная память: 32 ГБ DDR4 (2x16)

    Диски: SSD Samsung EVO 970 1TB (основной диск операционной системы) и внешний диск HDD Ultrastar DC HC320 8Tb (дополнительный для хранения больших файлов, подключен через USB3.0)

    Видеокарта: RTX3090 (с 24 Гб VRAM)

    ⚠️ Конфигурацию компьютера следует учитывать при настройке параметров работы модели локально (см. п. 4 статьи ниже).

  2. Версия windows 10 (с помощью команды ver):

    Microsoft Windows [Version 10.0.19045.6456]

  3. В качестве средства запуска модели локально используется llama.cpp, другие средства в статье не рассматриваются. Сборка приложения выполняется непосредственно и только для RTX3090 (точнее, архитектуры Ampere), флаг сборки для включения поддержки работы llama.cpp в режиме GPU подробно описан в пункте 2.

  4. В качестве консоли командной строки (терминала) в данной статье используется cmd или Powershell. Имеет смысл напомнить о том, что команда where помогает определить, из какого места файловой системы запущена программа команды, что бывает очень полезным при проверке настройки переменной PATH в Windows:

    where cmd
    C:\Windows\System32\cmd.exe
    
  5. Очень часто результат выполнения какой-либо команды сопровождается какими-либо текстовым выводом, сообщениями или логами (от сборщика программы, от компилятора, от llama.cpp и так далее) – имеет смысл их анализировать, так как в этих сообщениях могут быть ценные подсказки (неправильно настроен параметр, не найдена программа на компьютере, устаревшее ключевое слово). Проводить анализ можно, например, с помощью бесплатного Deepseek.

  6. Также в некоторых случаях в консоли командной строки может выводиться сообщение Отказано в доступе. Это означает, что текущих привилегий пользователя для выполнения команды недостаточно, и нужно запустить консоль с привилегиями администратора.

  7. Qwen3.8-27B не является реализацией архитектуры Mixture-of-Experts, как она устроена, можно, например, почитать в этой статье.

1. Подготовка всех необходимых программных средств для запуска модели

1.1 Устанавливаем Python

Python — обязательное предварительное условие для установки командной утилиты Hugging Face CLI (hf), которая устанавливается как пакет Python с помощью pip (см. пункт 1.2 ниже), а так же для работоспособности Python-скрипта convert_hf_to_gguf.py (выполняет конвертацию исходных файлов весов модели из HF в формат GGUF, подробнее в пункте 3.2 ниже).

Шаги по установке Python 3.12 на Windows 10:

  1. Открываем официальную страницу https://www.python.org/downloads/windows/ и скачиваем установщик Python 3.12.x — файл python-3.12.x-amd64.exe. Выбираем только 64-битную (amd64) версию: 32-битная версия не подойдёт для работы из-за проблем с совместимостью.

  2. Запускаем установщик. На первом экране обязательно ставим галочку "Add python.exe to PATH" внизу окна и жмём “Install Now”. Это добавит Python в системную переменную окружения PATH, благодаря чему команды python и pip будут работать в любом терминале без указания полного пути.

  3. Ждём завершения установки и закрываем установщик.

  4. Проверяем установку. Открываем новый терминал (cmd или powershell) и выполняем:

    python --version

    В ответ должно быть что-то вроде Python 3.12.x:

    Python 3.12.9

    Проверяем также pip:

    pip --version

    В ответ должно быть что-то вроде:

    pip 25.1 from C:\ProgramData\anaconda3\Lib\site-packages\pip

    Если команды выполняются и показывают версию — Python установлен корректно. Если видите ошибку вида 'python' is not recognized as an internal or external command, закройте терминал и откройте новый (PATH подхватывается при запуске терминала) либо переустановите Python, поставив галочку “Add python.exe to PATH”.

⚠️ Если на компьютере уже стоит другая версия Python, ставьте 3.12 рядом с ней и убедитесь, что команда python в терминале указывает именно на версию 3.12. Для выбора версии можно использовать встроенный py-запускатель:

py -3.12 --version

1.2 Устанавливаем hf

hf — это командная утилита (CLI) Hugging Face, которая входит в состав пакета huggingface-hub, устанавливаемого с помощью pip (или его аналогов - pipenv, poetry и т.д.). Она нужна для скачивания весов модели с Hugging Face Hub (используется в пункте 3.1 ниже). Дополнительно можно поставить пакет hf_xet — это Rust-реализация нового протокола хранения Xet, который заметно ускоряет загрузку больших файлов, что целесообразно в рамках текущей статьи при скачивании модели весом более 50ГБ. Если hf_xet установлен, huggingface-hub использует его автоматически, никакой дополнительной настройки не требуется.

Установить можно двумя способами: глобально в системный Python или в виртуальное окружение (venv). По результату они равнозначны — команда hf появится в терминале; разница лишь в том, в какой именно Python-интерпретатор (системный или для данного виртуального окружения) будет установлен пакет huggingface-hub.

Способ 1. Глобальная установка в системный Python

Открываем терминал (cmd или PowerShell) и выполняем:

pip install -U huggingface-hub hf_xet

Флаг -U (сокращение от --upgrade) ставит последнюю доступную версию пакета, а если пакет уже установлен — обновляет его до актуальной. После установки команда hf становится доступной в любом новом терминале, потому что pip кладёт исполняемые файлы в каталог Scripts, который при установке Python (пункт 1.1 выше) уже был добавлен в PATH (галочка “Add python.exe to PATH”).

Способ 2. Установка в виртуальное окружение (venv)

Виртуальное окружение изолирует пакеты от системного Python. Это удобно, если не хочется засорять глобальную установку или если в проекте нужен свой отдельный набор пакетов.

  1. Создаём окружение. В той папке, где хотим его держать (например, в папке llama.cpp или рядом с моделью), выполняем:
    python -m venv venv

    Команда создаст папку venv со своим собственным pip и своим набором пакетов, не затрагивая системный Python.

  2. Активируем окружение:

    • в cmd: venv\Scripts\activate

    • в PowerShell: .\venv\Scripts\Activate.ps1

    После активации в начале строки появится префикс (venv) — это признак того, что все последующие команды pip и python теперь работают именно внутри этого окружения.

    ⚠️ Если PowerShell выдаёт ошибку, связанную с политикой выполнения (ExecutionPolicy), выполните один раз Set-ExecutionPolicy -Scope CurrentUser RemoteSigned, либо используйте cmd вместо PowerShell.

  3. Устанавливаем hf в активное окружение: pip install -U huggingface-hub hf_xet

  4. Когда окружение больше не нужно, деактивируем его командой deactivate (или просто закрываем терминал).

Проверка установки (для обоих способов)

В том же терминале — глобальном или в активированном с помощью venv — выполняем:

hf --version

В ответ команда должна показать установленную версию пакета huggingface-hub. Если команда hf не найдена, значит либо терминал не перезапущен (для способа 1 нужно открыть новый), либо venv не активирован (для способа 2). Если хочется убедиться, что пакет точно установлен, можно выполнить:

python -c "import huggingface_hub as h; print(h.__version__)"

⚠️ Если выбрали виртуальное окружение, не забывайте его активировать перед каждым шагом, где используется hf (в первую очередь при скачивании весов в пункте 3.1 ниже). При глобальной установке активировать ничего не нужно.

1.3 Устанавливаем Git for Windows

Git нужен для скачивания (клонирования) репозитория llama.cpp с GitHub — это делается командой git clone с помощью утилиты командной строки git, которой нет в Windows по умолчанию.

Для установки нужно выполнить следующие шаги:

  1. Открываем официальную страницу https://git-scm.com/download/win и скачиваем установщик (файл вида Git-2.x.x-64-bit.exe). Для нашей конфигурации (64-битная система) необходима именно 64-битная версия.

  2. Запускаем установщик. На большинстве экранов можно просто жать “Next”, используя значения по умолчанию. На них стоит обратить внимание:

    • “Adjusting your PATH environment” — выбираем вариант “Git from the command line and also from 3rd-party software”. Это добавит git в системный PATH, благодаря чему команда git будет работать в любом терминале.

    • “Choosing the SSH executable to use” — оставляем “Use OpenSSH” (по умолчанию). Встроенный PuTTY-вариант не нужен.

    • “Choosing the default editor used when editing commit messages” — можно оставить Vim, но если не хочется разбираться с ним, выберите “Use Notepad as the Git default editor”.

    • “Configuring line ending conversions” — оставляем “Checkout Windows-style, commit Unix-style” (по умолчанию). Это корректно обрабатывает переводы строк между Windows и репозиториями с Unix-конвенцией.

    • “Configuring the terminal emulator for Git Bash” — можно оставить “Use MinTTY” (по умолчанию).

  3. Ждём завершения установки и закрываем установщик.

  4. Проверяем установку. Открываем новый терминал (cmd или PowerShell) и выполняем:

    git --version

    В ответ должно быть что-то вроде git version 2.x.x.windows.x. Если команда возвращает результат — Git установлен корректно. Если видите ошибку вида 'git' is not recognized as an internal or external command, закройте и откройте новый терминал (обновленный PATH подхватывается при старте\перезапуске терминала) либо переустановите, выбрав вариант PATH “Git from the command line and also from 3rd-party software”.

  5. (Опционально, выполнять не обязательно) Конфигурация имени пользователя и электронной почты

    Git при каждом коммите (записи изменений) хранит в истории имя и e-mail того, кто их внёс. Эти данные не обязательны для работы git clone (шаг 2 ниже), но без них Git выведет некритичную ошибку при первом коммите, а также они полезны, если вы планируете отправлять изменения на GitHub. Поэтому сразу после установки есть смысл задать их глобально — то есть один раз для всех репозиториев на компьютере.

    Открываем терминал и выполняем две команды:

    git config --global user.name "Ваше Имя"
    git config --global user.email "ваша почта@example.com"
    

    Вместо “Ваше Имя” и “ваша почта@example.com” подставьте своё имя и адрес электронной почты.

    Флаг --global означает, что настройки сохраняются в пользовательском конфиге (файл .gitconfig в домашней папке, на Windows это C:\Users\%USERNAME%\.gitconfig) и применяются ко всем репозиториям. Без этого флага Git спрашивал бы эти данные для каждого репозитория отдельно.

    Проверка конфигурации:

    git config --global user.name
    git config --global user.email
    

    Каждая команда должна вывести заданное ранее значение. Если вывод пустой или не совпадает с ожидаемым, повторите команды из предыдущего шага.

    ⚠️ Если вы работаете только локально (без отправки на GitHub), можно указать любые имя и e-mail — они не проверяются. Но если планируете пушить на GitHub, используйте реальные данные аккаунта, чтобы коммиты корректно связывались с вашим профилем.

1.4 Устанавливаем CUDA Toolkit 12.8

CUDA Toolkit — это набор инструментов NVIDIA для разработки и запуска кода на GPU. Для нашей задачи он нужен по двум причинам: во-первых, он предоставляет компилятор nvcc, которым CMake (пункт 1.5) собирает CUDA-код в исходниках llama.cpp под архитектуру GPU RTX3090; во-вторых, он устанавливает библиотеки CUDA Runtime (cudart) и заголовочные файлы, к которым линкуется итоговый llama-server. Без него сборка llama.cpp с поддержкой CUDA невозможна.

RTX 3090 (архитектура Ampere) полностью поддерживается CUDA Toolkit с версией 12.8.

Требования перед установкой:

  • Драйвер NVIDIA. CUDA требует достаточно свежий драйвер. Если драйвер старый, установщик CUDA сам предложит установить актуальный. Чтобы не полагаться на это, рекомендую заранее обновить драйвер — либо через NVIDIA GeForce Experience, либо скачав с https://www.nvidia.com/Download/index.aspx (выбрать GeForce RTX 3090, Windows 10, x64).

  • Свободное место на диске. Полный CUDA Toolkit занимает несколько гигабайт (зависит от выбранных компонентов).

Для скачивания установщика нужно выполнить следующие шаги:

  1. Открываем официальную страницу загрузки https://developer.nvidia.com/cuda-toolkit.

  2. В форме выбора параметров указываем:

    • Operating System: Windows

    • Version: 10

    • Architecture: x86_64

  3. В поле “Download Options” выбираем “Local Installer” (локальный установщик) — это полный установочный файл на несколько гигабайт. Он надёжнее «Network Installer», потому что всё скачивается один раз и установка идёт с диска, без повторных обращений к сети. Нажимаем “Accept” и ждём, пока файл (cuda_12.8.x_xxx.exe) скачается.

Запуск установщика:

  1. Запускаем скачанный .exe-файл.

  2. На первом экране (Installation Type) выбираем “Custom (Advanced)” — НЕ “Express”. Express ставит всё подряд без возможности выбрать компоненты, а нам важно контролировать, что именно ставится.

  3. Принимаем лицензионное соглашение (Accept).

  4. На экране “Components” (список компонентов) убедитесь, что отмечен пункт “CUDA” — он обязателен (включён по умолчанию). Остальные пункты (Nsight Compute, Nsight Systems, Visual Studio Integration, MPS, NSight Graphics и т.д.) — необязательны и занимают место; для сборки llama.cpp достаточно только “CUDA”.

  5. На экране выбора пути установки оставляем путь по умолчанию: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8. Менять не следует — некоторые скрипты и инструменты ожидают именно этот стандартный путь.

  6. Нажимаем “Install” и ждём завершения. Установка может занять несколько минут.

Проверка установки:

  1. Открываем новый терминал (cmd или PowerShell).

  2. Выполняем:

    nvcc --version

    В ответ должно быть что-то вроде:

    nvcc: NVIDIA (R) Cuda compiler driver
    Copyright (c) 2005-2025 NVIDIA Corporation
    Built on Wed_Jan_15_19:38:46_Pacific_Standard_Time_2025
    Cuda compilation tools, release 12.8, V12.8.61
    Build cuda_12.8.r12.8/compiler.35404655_0
    

    Если команда распознаётся и показывает версию 12.8 – CUDA Toolkit установлен корректно.

  3. Проверяем, что пути добавлены в PATH. Выполняем:

    echo %PATH%
    

    (в cmd; в PowerShell: $env:PATH)

    В выводе должны присутствовать пути вида C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin и …\libnvvp. Установщик добавляет их автоматически.

  4. Дополнительно можно проверить переменные окружения:

    echo %CUDA_PATH%
    echo %CUDA_HOME%
    

    Команды должны вернуть значение C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8. Установщик задаёт CUDA_PATH (и CUDA_HOME) сам.

    ⚠️Важные примечания:

  • Если nvcc не находится в терминале, значит либо терминал не перезапущен (откройте новый), либо при установке пути не были добавлены в PATH (переустановите, выбрав Custom и убедившись, что “CUDA” отмечена).

  • Не следует путать CUDA Toolkit с драйвером GPU. Драйвер нужен для работы GPU как устройства, а CUDA Toolkit — это компилятор и библиотеки для разработки. Для запуска модели нужны и драйвер, и toolkit.

  • Версия CUDA (12.8) должна совпадать с версией, под которую планируется собирать llama.cpp (см. пункт 2).

1.5 Устанавливаем cmake

CMake — это система сборки (build system), которая собирает проект из исходников: читает файл CMakeLists.txt в папке llama.cpp, находит компилятор (MSVC из пункта 1.6 ниже), находит CUDA-инструменты (nvcc 12.8 из пункта 1.4 выше), и генерирует план сборки, который затем выполняет Ninja (пункт 1.7 ниже).

Стоит отметить, что CMake сам по себе не компилирует CUDA-код — этим занимается nvcc. CMake лишь находит nvcc и правильно выставляет параметры для него. Поэтому CMake должен быть достаточно свежий, чтобы он корректно находил и настраивал часть сборки, связанную с CUDA (я использую версию 3.29).

⚠️Важные примечания:

  • Минимальную версию CMake, необходимую для сборки llama.cpp можно увидеть в файле CMakeLists.txt в папке исходников llama.cpp (см. пункт 3).

  • NVIDIA рекомендует CMake 3.20+ для корректной работы с CUDA 12.x.

Для установки Cmake нужно выполнить следующие шаги:

  1. Открываем официальную страницу https://cmake.org/download/ и скачиваем установщик для Windows — файл вида cmake-3.3x.x-win64-x86_64.exe (64-битный, для x86_64). Если на странице несколько вариантов, берём именно .exe-установщик (не «zip»).

  2. Запускаем установщик. На большинстве экранов жмём “Next”, используя значения по умолчанию. Единственный важный пункт:

    • На экране “CMake Setup Type” (или “Add CMake to the system PATH for all users”) обязательно выбираем вариант, который добавляет CMake в системный PATH. В классическом установщике это опция “Add CMake to the system PATH”. Это нужно, чтобы команда cmake работала в любом терминале без указания полного пути.

  3. Ждём завершения установки и жмём “Finish”.

Проверка установки

  1. Открываем новый терминал (cmd или PowerShell).

  2. Выполняем:

    cmake --version

    В ответ должно быть что-то вроде cmake version 3.3x.x. Если команда распознаётся и показывает версию 3.20+ – CMake установлен корректно.

  3. Проверяем, что путь до cmake.exe находится в переменной PATH. Выполняем:

    echo %PATH%
    

    (в cmd; в PowerShell: $env:PATH)

    В выводе должен присутствовать каталог, где лежит cmake.exe (например, C:\Program Files\CMake\bin).

⚠️Примечания:

  • CMake работает в связке с компилятором MSVC (пункт 1.6 ниже) и сборщиком Ninja (пункт 1.7 ниже). Все три компонента независимы: CMake генерирует план сборки, MSVC компилирует C++/CUDA-код, Ninja выполняет сборку.

  • Если cmake не находится в терминале, значит либо терминал старый (откройте новый), либо при установке не была включена опция добавления в PATH (переустановите с этой опцией).

1.6 Устанавливаем средство для сборки C++ приложений

llama.cpp написан на C++, поэтому, чтобы собрать его из исходников, нужен C++ компилятор. На Windows это можно сделать с помощью MSVC (Microsoft Visual C++) — именно его cl.exe (компилятор) и link.exe (линковщик) запускает Ninja в процессе сборки (пункт 1.7). MSVC поставляется в составе Visual Studio, поэтому ставим Visual Studio Community Edition 2022 — бесплатную полнофункциональную версию, которой достаточно для нашей задачи. В некоторых источниках пишут, что достаточно установить просто Build Tools.

⚠️ Важно не путать два продукта:

  • Visual Studio Community — это полная IDE: редактор кода, компилятор MSVC, отладчик и прочее. Бесплатна для личного использования и обучения.

  • Build Tools for Visual Studio — это минимальный набор инструментов для сборки (MSVC + Windows SDK) без редактора.

Для сборки llama.cpp достаточно и того, и другого — важно только, чтобы были установлены компилятор MSVC и Windows SDK. Но Community Edition удобнее: если позже захотите открыть проект в редакторе или написать какой-то код на С++ — IDE уже установлена на компьютере.

Требования перед установкой:

  • Свободное место на диске. Visual Studio Community с рабочей нагрузкой C++ занимает порядка 10–20 ГБ (зависит от компонентов).

Установка:

  1. Открываем официальную страницу https://visualstudio.microsoft.com/ru-ru/downloads/ (или https://visualstudio.microsoft.com/ru/vs/older-downloads/) и находим блок «Visual Studio Community» (или «Скачать Visual Studio 2022» → «Community»). Нажимаем «Скачать» — начнёт качаться небольшой установщик vs_community.exe. Это не сама программа, а оболочка, которая далее скачает нужные компоненты.

  2. Запускаем vs_community.exe. Откроется окно выбора рабочих компонентов (workloads).

  3. В списке компонентов ставим галочку «Разработка классических приложений C++» (в английской версии — «Desktop development with C++»). Именно она содержит компилятор MSVC и Windows SDK, необходимые для сборки llama.cpp.

    • Прочие рабочие компоненты (.NET, веб, Azure, Unity, Android и т.д.) нам не нужны — снимите их галочки, чтобы не тянуть лишнее.

    • Внизу того же окна есть раздел «Индивидуальные компоненты» (Individual components). Убедитесь, что отмечены «Компилятор C++ для x64 (MSVC)» и «Windows 11 SDK» (или «Windows 10 SDK»). Обычно они включаются автоматически вместе с рабочим компонентом C++; если вдруг нет — отметьте вручную.

  4. В поле «Место установки» оставьте путь по умолчанию (обычно C:\Program Files\Microsoft Visual Studio\2022\Community). Менять не следует.

  5. Нажимаем «Установить» (Install). Установщик скачает и установит выбранные компоненты — это может занять от нескольких минут до получаса в зависимости от скорости сети. Ждём завершения и закрываем окно.

Проверка установки

Самый простой способ убедиться, что компилятор на месте, — запустить «родную» для MSVC командную строку. Она называется x64 Native Tools Command Prompt for VS 2022 (меню Пуск → «Visual Studio 2022» → «x64 Native Tools Command Prompt for VS 2022»). Открыв её, выполняем:

cl

В ответ должны появиться сведения о компиляторе (что-то вроде Microsoft (R) C/C++ Optimizing Compiler и версия вида 19.xx.xxxxxxx). Это значит, что MSVC установлен корректно. Нажмите Ctrl+C, чтобы выйти из режима ожидания ввода. Альтернативная проверка — выполнить в том же окне where cl; должен отобразиться путь к cl.exe.

⚠️ Важно для сборки

Обычный cmd или PowerShell, которые открываются из меню Пуск, не содержат в PATH компилятор MSVC (cl.exe, link.exe) и заголовки Windows SDK. По этой причине собрать llama.cpp в них не получится: CMake не найдёт компилятор, а Ninja не сможет его запустить.

Поэтому для сборки llama.cpp (шаг 2 ниже) всегда используйте x64 Native Tools Command Prompt for VS 2022 — она сама подставляет все необходимые переменные окружения (PATH, INCLUDE, LIB) для 64-битной сборки. Запомните это название: на шаге 2 ниже мы именно вернемся к ней для выполнения команды сборки.

1.7 Устанавливаем Ninja

Ninja — это сборщик (build tool), то есть программа, которая непосредственно выполняет сборку: запускает компилятор на каждом файле, собирает результаты и линкует итоговый exe-файл. Если CMake — это архитектор, который составил план стройки (что и в каком порядке собирать), то Ninja — это бригада, которая этот план исполняет.

  • CMake НЕ компилирует код. Он читает CMakeLists.txt, находит компилятор (MSVC из пункта 1.6) и CUDA-toolchain (nvcc из пункта 1.4), решает, какие задачи нужно выполнить и в какой последовательности, и выкладывает этот план в файл build.ninja. На этом его работа на этапе сборки заканчивается.

  • Ninja берёт этот план и исполняет его: запускает cl.exe для C++ файлов, nvcc для CUDA-ядер, link.exe для финальной сборки llama-server.exe — причём задачи, которые не зависят друг от друга, выполняет параллельно, что ускоряет сборку проекта такого размера, как llama.cpp.

Почему используется именно Ninja, а не другой сборщик (например, MSBuild из Visual Studio):

  • это рекомендуемый способ сборки llama.cpp на Windows: в документации проекта приведены команды именно с генератором -G Ninja.

  • он заметно быстрее по времени сборки и проще по логике ошибок — в логе видно, какая именно команда упала;

  • Ninja не требует установленного Visual Studio — достаточно компилятора из шага 1.6 выше;

Способ установки 1. Через winget (рекомендуется)

Открываем PowerShell и выполняем:

winget install Ninja-Ninja.Ninja

winget скачает последнюю версию Ninja и добавит её в PATH. После установки закройте и откройте новый терминал.

Способ установки 2. Ручная установка из архива

У официального проекта Ninja нет .exe-установщика для Windows — дистрибутив распространяется архивом.

  1. Открываем страницу релизов https://github.com/ninja-build/ninja/releases.

  2. В последнем релизе скачиваем файл ninja-win.zip (например, ninja1.12.2-win.zip).

  3. Распаковываем архив в отдельную папку, например C:\ninja (внутри окажется один файл ninja.exe).

  4. Добавляем эту папку в системный PATH: Пуск → поиск «Переменные среды» → «Изменение переменных среды для системы» → «Переменные среды…» → в блоке «Системные переменные» выбираем Path → «Изменить…» → «Создать» → вставляем C:\ninja → OK во всех окнах.

    Более простой вариант: просто скопировать ninja.exe в папку, которая уже есть в PATH (например, C:\Program Files\CMake\bin из шага 1.5), — тогда менять переменные окружения не придётся.

Проверка установки:

  1. Открываем новый терминал (cmd или PowerShell) — PATH подхватывается при старте.

  2. Выполняем:

    ninja --version
    

    В ответ должно быть что-то вроде 1.12.x. Если команда распознаётся и показывает версию — Ninja установлен корректно.

  3. При желании проверяем, что путь до ninja.exe находится в PATH. Выполняем:

    echo %PATH%
    

    (в cmd; в PowerShell: $env:PATH)

    В выводе должна присутствовать папка, где лежит ninja.exe.

⚠️ Примечания:

  • Если ninja не находится в терминале, значит либо терминал старый (откройте новый), либо папка с ninja.exe не попала в PATH.

  • Некоторые новые версии CMake умеют автоматически подгрузить Ninja при генерации, если он не найден. Но всё-таки лучше поставить его явно, тогда сборка не будет зависеть от сети и от конкретной версии CMake.

  • В пункте 2 мы зададим CMake генератор -G Ninja — именно тогда CMake начнёт использовать установленный здесь Ninja для исполнения плана сборки.

1.8 Устанавливаем OpenSSL (Full)

OpenSSL — это криптографическая библиотека (libssl + libcrypto) и стандартная реализация протоколов TLS/SSL. В контексте нашей задачи она нужна для сборки llama.cpp с поддержкой SSL: если при сборке CMake найдёт OpenSSL, то llama-server сможет принимать HTTPS-соединения (TLS), а не только незащищенный HTTP. Это пригодится, если вы планируете обращаться к серверу из других машин или из программ, которые требуют именно https-эндпоинт.

⚠️ OpenSSL — это необязательная зависимость. Как следует из документации llama.cpp, если он не установлен, проект соберётся и будет работать корректно, просто без SSL-поддержки. В пункте 2 ниже мы передаём CMake флаг -DOPENSSL_ROOT_DIR, чтобы впоследствии не приходилось собирать приложение снова.

Откуда скачивать

Официальные бинарные пакеты OpenSSL для Windows выпускает Shining Light Productions (SLB) — страница загрузки: https://slb.certificate.com/openssl/download/ (на неё же ведёт ссылка с сайта openssl.org). Там лежат готовые .exe-установщики, собирать OpenSSL из исходников под Windows не нужно.

Какой файл выбрать: Full или Light

На странице несколько установщиков. Для 64-битной Windows нужен файл вида Win64OpenSSL_3_x_y.exe (например, Win64OpenSSL_3_2_3.exe) — это полная (Full) редакция. Не берите:

  • Win64OpenSSL_Light_3_x_y.exe (Light) — облегчённая редакция;

  • Win32OpenSSL_... — 32-битные пакеты; у нас всё остальное (MSVC, CUDA, сама сборка) 64-битное, поэтому 32-битный OpenSSL нам не подойдёт.

  • Full — полный дистрибутив: инструменты (openssl.exe), заголовочные файлы (include/openssl/*.h), общие библиотеки (DLL) с импортируемыми .lib, статические библиотеки и полный набор алгоритмов/шифров.

  • Light — урезанный вариант: только бинарный исполняемый файл openssl.exe.

Для сборки приложения llama.cpp CMake-модулю find_package(OpenSSL) нужны заголовки и библиотеки libssl/libcrypto — они есть в полном пакете, поэтому берём его.

Установка

  1. Скачиваем Win64OpenSSL_3_x_y.exe с https://slb.certificate.com/openssl/download/.

  2. Запускаем установщик и принимаем лицензионное соглашение.

  3. На экране выбора пути установки оставляем путь по умолчанию: C:\Program Files\OpenSSL-Win64. Важно: именно этот путь мы укажем на шаге 2 в команде CMake (-DOPENSSL_ROOT_DIR="C:/Program Files/OpenSSL-Win64"), поэтому менять его не стоит.

  4. Установщик предложит добавить OpenSSL в PATH (для текущего пользователя или для всех). Ставим галочку — тогда команда openssl будет работать в любом терминале.

  5. Ждём завершения установки и закрываем окно.

Проверка установки

  1. Открываем новый терминал (cmd или PowerShell).

  2. Выполняем:

    openssl version
    

    В ответ должно быть что-то вроде OpenSSL 3.x.y .... Если команда распознаётся и показывает версию 3.x — OpenSSL установлен корректно. Если видите ошибку вида 'openssl' is not recognized as an internal or external command, то либо закройте и откройте новый терминал, либо при установке не была включена опция добавления в PATH и нужно переустановить.

  3. Убедимся, что все нужные для сборки компоненты на месте:

    dir "C:\Program Files\OpenSSL-Win64\bin"
    dir "C:\Program Files\OpenSSL-Win64\lib"
    dir "C:\Program Files\OpenSSL-Win64\include\openssl"
    

    Ожидаем увидеть: в binopenssl.exe, libssl-3-x64.dll, libcrypto-3-x64.dll; в lib — импортируемые библиотеки libssl.lib и libcrypto.lib; в include\openssl — заголовочные файлы (ssl.h, evp.h и другие). Именно эта тройка (заголовки + библиотеки + DLL) — нужна CMake, чтобы собрать llama.cpp с поддержкой SSL.

⚠️ Примечания:

  • Если вы не планируете использовать HTTPS и хотите упростить сборку, этот шаг можно пропустить — тогда в пункте 2 просто уберите из команды CMake флаг -DOPENSSL_ROOT_DIR, и проект соберётся без SSL-поддержки.

  • Версия: подойдёт любая актуальная OpenSSL 3.x; подгонять её под версии CUDA/MSVC не нужно — это независимые компоненты.

2. Собираем llama-сервер из исходников для запуска модели

Для начала сборки необходимо скачать исходные файлы (в любую папку, в которой планируем собирать, я создал папку Sources в корне 8Tb-диска):

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp

Теперь внутри папки llama.cpp создаем папку build и переходим в неё:

mkdir build
cd build

⚠️ Важно: в каком терминале выполнять команду сборки. Команду сборки нужно выполнять не в обычном cmd и не в PowerShell, а в x64 Native Tools Command Prompt for VS 2022 (меню Пуск → «Visual Studio 2022» → «x64 Native Tools Command Prompt for VS 2022»). Только в ней в PATH и переменных окружения (INCLUDE, LIB) есть компилятор MSVC (cl.exe) и заголовки Windows SDK из пункта 1.6 — без них CMake не найдёт компилятор, и сборка упадёт с ошибкой вида «No CMAKE_CXX_COMPILER could be found».

Запуск команды конфигурации сборки

cmake .. -G Ninja -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 -DGGML_CUDA_F16=1 -DCMAKE_BUILD_TYPE=Release -DOPENSSL_ROOT_DIR="C:/Program Files/OpenSSL-Win64"

Разберём по частям, что задаёт каждая часть этой команды:

  • .. — аргумент: путь к каталогу с исходниками. Команда выполняется из папки сборки (build), а CMakeLists.txt проекта лежит на уровень выше, поэтому “…” означает “собирай проект из родительской папки”.

  • -G Ninja — выбор генератора CMake. CMake сгенерирует план сборки в формате Ninja (файл build.ninja) и передаст его сборщику Ninja, установленному в пункте 1.7. Это рекомендуемый способ сборки llama.cpp на Windows.

  • -DGGML_CUDA=ON — флаг для сборки с поддержкой CUDA: собранный проект будет использовать GPU от NVIDIA. Без этого флага llama.cpp собрался бы без поддержки видеокарты (только в режиме CPU).

  • -DCMAKE_CUDA_ARCHITECTURES=86 — задает целевую архитектуру GPU, 86=Ampere, проект не будет собираться с поддержкой других архитектур, что позволит уменьшить размер сборки.

  • -DGGML_CUDA_F16=1 — устанавливает использование 16-битных чисел с плавающей точкой (FP16, “half precision”) в части вычислений на GPU. Настройка этого флага даёт меньший расход памяти видеокарты и прирост скорости. Если по какой-то причине CMake в новой версии выдаст предупреждение о неизвестном флаге, его можно просто убрать при сборке.

  • -DCMAKE_BUILD_TYPE=Release — задаёт конфигурацию сборки: Release — оптимизированная сборка с включённой оптимизацией компилятора и без отладочной информации, что даёт максимальное быстродействие собранной версии llama.cpp.

  • -DOPENSSL_ROOT_DIR="C:/Program Files/OpenSSL-Win64" — флаг указывает путь к библиотеке OpenSSL (корневая папка её установки) для сборки llama.cpp с поддержкой HTTPS/TLS. Если флаг не указан, то проект всё равно соберётся без SSL-поддержки и будет работать корректно, просто без функций, связанных с HTTPS.

Запуск команды компиляции

cmake --build . --config Release

После завершения сборки в папке .\bin появятся исполняемые файлы llama.cpp.

2.1 Делаем виртуальное окружение Python в папке llama.cpp

В пункте 3.2 ниже мы будем конвертировать скачанные веса в GGUF с помощью скрипта convert_hf_to_gguf.py. Это Python-утилита из состава llama.cpp, и у неё довольно тяжёлый набор зависимостей: PyTorch (torch), transformers, gguf, numpy, sentencepiece, protobuf. Ставить их напрямую в системный Python нежелательно: это засорит глобальную установку и может привести к конфликтам версий с другими проектами. Поэтому для этой утилиты создаём отдельное виртуальное окружение (venv) прямо в папке llama.cpp — принцип тот же, что мы разбирали в пункте 1.2 (Способ 2) выше.

Создаём и активируем окружение:

  1. Открываем терминал (cmd или PowerShell) и переходим в папку llama.cpp — туда, где лежат исходники и лежит скрипт convert_hf_to_gguf.py.

  2. Создаём окружение командой:

    python -m venv venv
    

    В папке llama.cpp появится каталог venv со своим pip и своими пакетами.

  3. Активируем его:

    • в cmd: venv\Scripts\activate

    • в PowerShell: .\venv\Scripts\Activate.ps1

    После активации в начале строки появится префикс (venv) — с этого момента команды python и pip работают именно внутри этого окружения.

  4. Устанавливаем зависимости в виртуальное окружение - берём готовый список зависимостей из самого llama.cpp:

    pip install -r requirements.txt
    

    Файл requirements.txt в корне llama.cpp уже перечисляет всё необходимое для Python-скриптов проекта (в том числе для convert_hf_to_gguf.py): PyTorch, transformers, gguf, numpy, sentencepiece, protobuf и т.д.

⚠️ Установка займёт время и скачает несколько гигабайт (в основном из-за PyTorch).

Проверка и использование:

  1. Убедитесь, что префикс (venv) отображается в строке терминала — окружение активно.

  2. Проверить, что зависимости на месте, можно так:

    python -c "import torch, transformers, gguf; print(torch.__version__)"
    

    Должны отобразиться версии установленных пакетов без ошибок. Если увидите ModuleNotFoundError — значит, окружение не активно или зависимости не установлены.

3. Создаем локальную модель Qwen3.8-27B

3.1 Скачиваем опубликованные веса модели

Официальные веса лежат в публичном репозитории Qwen на Hugging Face Hub — Qwen/Qwen3.8-27B (точное имя репозитория сверяйте на странице модели). В составе репозитория находятся следующие файлы:

  • веса модели в формате safetensors, разбитые на части (файлы вида model-00001-of-00XXX.safetensors);

  • служебные файлы: config.json, токенайзеры (tokenizer.json, tokenizer_config.json и др.), generation_config.json.

У модели порядка 27 млрд параметров, каждый из которых в 16-битном формате (BF16) занимает 2 байта: 27 × 10⁹ × 2 байта ≈ 54 ГБ (плюс немного на служебные файлы). Перед запуском скачивания убедитесь, что на целевом диске свободно не менее ~60 ГБ.

Предварительные условия:

  • установлены huggingface-hub + hf_xet (пункт 1.2 выше) — команда hf доступна в терминале;

  • модель публичная, поэтому токен Hugging Face не требуется.

Команда скачивания

Открываем терминал (cmd или PowerShell) и выполняем:

hf download Qwen/Qwen3.8-27B --local-dir D:\models\Qwen3.8-27B

Разберём по частям параметры загрузки:

  • Qwen/Qwen3.8-27B — идентификатор репозитория в формате «владелец/имя_репозитория».

  • --local-dir D:\models\Qwen3.8-27B — папка, куда складываются файлы. Без этого флага файлы установились бы в кэш по умолчанию (%USERPROFILE%\.cache\huggingface\hub), откуда их потом пришлось бы переносить. Можно указать свой путь — главное, чтобы диск был подключён и на нём было не менее 60 ГБ свободного места.

⚠️ Примечания:

  • Пока идёт загрузка, hf показывает прогресс по каждому файлу и фактическую скорость — по ней и стоит сверять оценку времени из расчёта ниже.

  • Прерывание не страшно: если сеть упала или компьютер ушёл в сон, просто выполните ту же самую команду заново — загрузка продолжится с места обрыва, уже скачанные части повторно не качаются. Поэтому для многочасовой загрузки имеет смысл в настройках питания Windows выставить «Сон — Никогда».

Проверка результата

После завершения перечисляем содержимое папки:

dir D:\models\Qwen3.8-27B

В папке должны присутствовать все safetensors из набора (без пропусков в нумерации частей), config.json, файлы токенайзера и generation_config.json. Совокупный размер файлов должен совпасть с размером репозитория, указанным на странице модели (~54 ГБ). Именно эту папку с весами мы укажем в пункте 3.2 ниже при конвертации в GGUF.

Оценим время скачивания при скорости 5 Мбит/с:

54 ГБ × 8 = 432 Гбит = 432 000 Мбит; 432 000 Мбит ÷ 5 Мбит/с = 86 400 с = 24 часа;

Итог - при такой скорости время скачивания модели составит около суток;

⚠️ Практический совет: запускайте скачивание на вечер выходного, отключите сон компьютера, и к утру следующего дня (или чуть позже) модель будет готова к конвертации в пункте 3.2 ниже.

3.2 Конвертируем веса в gguf-файл модели с точностью F16

Прежде чем выполнять команду, разберёмся, что именно мы делаем, зачем нужен формат GGUF и почему размер результата по размеру окажется практически таким же, как у исходных весов.

Зачем нужен формат GGUF

GGUF (GPT-Generated Unified Format) — бинарный формат хранения языковых моделей, созданный разработчиками llama.cpp. Это самодостаточный контейнер — в одном файле объединяется всё, что нужно для запуска модели:

  • сами веса (тензоры всех слоёв сети);

  • метаданные об архитектуре: количество слоёв, размер скрытого слоя, число головок внимания, размер контекста и т.д. — то есть всё, что движку нужно для правильной сборки графа вычислений;

  • токенайзер (словарь): соответствия между токенами и текстом, служебные токены;

  • дополнительные служебные параметры (шаблон диалога, имя модели и пр.).

До появления GGUF для работы с llama.cpp приходилось собирать набор из нескольких файлов: файл с весами, файл токенайзера, конфигурация — можно было легко потерять один из них или перепутать версии. Благодаря GGUF-формату всё лежит в одном контейнере, поэтому GGUF стал де-факто стандартом для локального запуска: его понимают llama.cpp и его производные, Ollama, LM Studio и другие движки.

Что именно происходит при конвертации

Скрипт convert_hf_to_gguf.py не обучает и не квантует модель — он последовательно делает три вещи:

  1. Читает исходник. Скрипт получает папку с весами (результат пункта 3.1) и читает из неё config.json (по нему определяется архитектура модели и все её параметры), токенайзер и все части *.safetensors по очереди.

  2. Переводит на «язык» llama.cpp. В Hugging Face тензоры именованы по собственным правилам (например, model.layers.0.self_attn.q_proj.weight), а llama.cpp ожидает свои имена (например, blk.0.attn_q.weight). В скрипте есть таблицы соответствий имён для каждой поддерживаемой архитектуры — по ним переименовываются все десятки тысяч тензоров. Там, где нужно, тензоры также перекладываются (транспонируются) под тот порядок хранения в памяти, который ожидает библиотека ggml; в зависимости от архитектуры и версии llama.cpp некоторые проекции могут объединяться или, наоборот, раздельно храниться. Это оптимизация для вычислений, и к квантованию отношения не имеет.

  3. Приводит тип и упаковывает в один файл. Здесь работает флаг --outtype f16: каждый вес приводится из исходного типа (у моделей Qwen это BF16) к типу F16 (float16). Затем всё записывается в единый GGUF-файл последовательно: сначала заголовок (служебные байты GGUF, версия формата, метаданные: архитектура, токенайзер, параметры), затем по каждому тензору его описание (имя, размерности, тип, смещение в файле), и сами веса.

Почему общий размер модели при этом не меняется

Мы конвертировали модель в формат GGUF, а выходной файл получился примерно того же размера (~54 ГБ), что и исходники. Причина проста — конвертация с --outtype f16 не меняет размер выходного файла:

  • В исходных safetensors каждый из 27 млрд параметров хранился как 16-битное число (BF16): 27×10⁹ × 2 байта ≈ 54 ГБ;

  • В GGUF-файле каждый параметр по-прежнему хранится как 16-битное число (F16): 27×10⁹ × 2 байта ≈ 54 ГБ.

Всё, что мы сделали, это поменяли формат 16-битного числа, а не уменьшили количество бит. Разница между BF16 и F16 — во внутренней раскладке этих 16 бит: у BF16 шире динамический диапазон (8 бит экспоненты, как у FP32) при меньшей точности (7 бит мантиссы), у F16 диапазон уже (5 бит экспоненты), но точность выше (10 бит мантиссы). Для нейросетей это практически взаимозаменяемые форматы — отсюда и равенство размеров входных файлов и выходного GGUF-контейнера модели (на самом деле GGUF-файл может оказаться чуть больше суммы safetensors — на десятки мегабайт из-за накладных расходов контейнера (заголовок, метаданные, токенайзер, описания тензоров).

Сокращение размера модели происходит только на следующем шаге 3.3, при квантовании в Q4_K_M на каждый параметр в среднем уходит около 4,8 бита вместо 16, и файл уменьшается примерно втрое (~16–17 ГБ).

Запуск команды конвертации

Сначала создаём папку, в которой будет лежать результат:

mkdir ..\models\Qwen3.8-27B\my_conversions\

Затем запускаем конвертацию (из папки llama.cpp, с активированным виртуальным окружением из пункта 2.1 выше):

(venv) D:\llama.cpp>python convert_hf_to_gguf.py ..\Qwen3.8-27B_official_sources_from_Qwen --outfile ../models/Qwen3.8-27B/my_conversions/Qwen3.8-27B-F16.gguf --outtype f16

Разберём команду по частям:

  • ..\Qwen3.8-27B_official_sources_from_Qwen — путь к папке со скачанными весами (результат пункта 3.1).

  • --outfile ... — имя и путь результирующего GGUF-файла.

  • --outtype f16 — точность весов в результирующем файле: F16 (float16).

Проверка результата

После завершения в папке my_conversions должен оказаться файл Qwen3.8-27B-F16.gguf размером ~54 ГБ. Время конвертации зависит от скорости диска: последовательно считывается ~54 ГБ и записывается примерно столько же, поэтому на HDD это может занять от десятка минут до часа и более. Если скрипт упал с ошибкой, то самая частая причина состоит в том, что зависимости не установлены в активном venv (шаг 2.1 выше): проверьте активацией окружения и командой python -c "import torch, transformers, gguf" установленные зависимости.

3.3 Выполняем квантование модели с параметром Q4_K_M

На этом шаге мы уменьшаем модель до размера, который влезает в нашу видеокарту. Напомню, что мастер-файл в F16 весит ~54 ГБ, а у RTX 3090 — 24 ГБ видеопамяти. Загрузить модель «как есть» не получится — пришлось бы раскидывать слои модели между GPU и оперативной памятью, что резко снижает производительность (узким местом становится медленная DDR4, скорость генерации токенов падает до 3-5 токенов\сек). Квантование решает именно эту проблему.

Что происходит при квантовании

Квантование — это снижение точности, с которой в файле хранятся веса модели. В мастер-файле каждый из 27 млрд параметров занимает 16 бит (F16). При квантовании в Q4_K_M тот же параметр в среднем занимает около 4,8 бита. При этом веса не «обрезаются» до 4 бит напрямую: инструмент разбивает веса тензора на небольшие группы, для каждой группы подбирает масштабирующий коэффициент (scale) и смещение (min), а в файл записывает уже не сами значения, а сжатые 4-битные индексы плюс эти коэффициенты. При загрузке модели сервер llama.cpp восстанавливает приблизительные значения весов из индексов и коэффициентов — отсюда и название «квантование»: непрерывные числа заменяются набором дискретных уровней внутри каждой группы.

Что это даёт практически:

  • Снижение размера файла. 27×10⁹ параметров × 16 бит ≈ 54 ГБ превращаются в 27×10⁹ × ~4,8 бит ≈ 16–17 ГБ — файл становится примерно в 3,3 раза меньше.

  • Модель целиком помещается в видеопамять. ~16–17 ГБ весов плюс KV-кэш (контекст) укладываются в 24 ГБ RTX 3090, и инференс (ответ) у модели идёт полностью на VRAM GPU, без задействования RAM. Это главный практический выигрыш: модель не просто стала меньше, но ещё и работает на полной скорости видеокарты.

  • Прирост скорости генерации. Генерация токенов упирается в пропускную способность памяти: чтобы выдать каждый новый токен, из памяти приходится перечитать все веса сети. Если объём данных в ~3 раза меньше, то и время на их чтение в разы меньше (реальный прирост чуть скромнее, но ощутимый).

  • Небольшую потерю точности. Квантование — это сжатие с потерями: часть точности весов безвозвратно теряется, и обратно F16-версию из Q4_K_M восстановить не получится. Именно поэтому на шаге 3.2 мы сначала сделали полноразмерный мастер: из него можно получить модели других квантований при необходимости.

Почему выбран именно Q4_K_M

llama.cpp поддерживает много типов квантования — от Q2_K (~2,6 бита на вес) до Q8_0 (~8,5 бита). Больше бит — выше качество, но и больше файл. Ориентировочная карта размеров для нашей 27B-модели:

  • Q4_K_S — ~4,5 бита — ~15 ГБ;

  • Q4_K_M — ~4,8 бита — ~16–17 ГБ (наш выбор);

  • Q5_K_M — ~5,9 бита — ~20 ГБ;

  • Q6_K — ~6,6 бита — ~22 ГБ;

  • Q8_0 — ~8,5 бита — ~29 ГБ (в 24 ГБ видеопамяти уже не помещается).

Буква K означает принадлежность к семейству «K-quants» — схемы хранения, которые точнее «простых» Q4_0/Q5_0. Их принцип — двухуровневое масштабирование: веса каждого тензора разбиваются на суперблоки по 256 значений, а каждый суперблок — на 8 малых блоков по 32 значения. Для каждого малого блока вычисляется собственный масштаб (scale) и смещение (min); для всего суперблока дополнительно хранится ещё один, более точный общий масштаб. Иными словами, каждый весовый параметр калибруется «на двух уровнях»: своим локальным коэффициентом внутри группы из 32 и общим для суперблока из 256. Ошибка округления отдельных весов до 4 бит таким образом частично компенсируется этими более точными коэффициентами групп — за счёт этого K-quants при том же числе бит заметно лучше сохраняют качество, чем старые одноуровневые схемы (Q4_0).

Буква M (Mix) означает, что это «смешанный» тип: большинство тензоров хранится в 4-битном представлении, но наиболее значимые для качества — в первую очередь выходной слой (матрица, предсказывающая токены) и часть внутренних MLP-проекций — сохраняются с повышенной точностью (Q6_K). Это стоит лишь несколько процентов размера и заметно улучшает качество по сравнению с «чистым» Q4_K_S. Поэтому Q4_K_M считается де-факто стандартом рекомендаций для локального запуска больших моделей: наилучший баланс «размер/качество», который ещё и влезает в 24 ГБ видеопамяти.

Как квантование делается с помощью llama-quantize

Инструмент llama-quantize входит в состав llama.cpp и уже собран вместе с остальными файлами в пункте 2 выше. В отличие от скрипта конвертации (пункт 3.2 выше), ему не нужен Python и виртуальное окружение — это готовый исполняемый файл, лежащий в папке build\bin рядом с llama-server.exe.

Запуск инструмента — это три аргумента: входной файл, выходной файл и тип квантования. Что происходит под капотом:

  1. Читает мастер-файл. Открывает F16-GGUF из шага 3.2, считывает все тензоры, метаданные и токенайзер.

  2. Квантует каждый тензор. Применяет описанную выше схему: разбивает веса на суперблоки, подбирает scale/min, сжимает значения в 4-битные индексы; для выделенных «важных» тензоров использует более точный Q6_K — это и есть часть «Mix».

  3. Записывает результат в новый файл. Метаданные, параметры архитектуры и токенайзер копируются из мастера как есть, а веса записываются уже в новом сжатом формате. Получившийся файл самодостаточен: его так же, как и F16, можно отдать llama-server.

  4. Исходный файл не трогает. Мастер в F16 остаётся нетронутым — если Q4_K_M по какой-то причине не устроит, из того же мастера можно сделать Q5_K_M или Q8_0, не качая и не конвертируя модель заново.

Операция выполняется на CPU (GPU не требуется), использует несколько ядер процессора, а её время ограничено в основном чтением ~54 ГБ с диска — на конфигурации из статьи это около 10 минут. В консоль при этом печатается отчёт по каждому тензору: имя, размерность и тип, в который он был записан (можно увидеть и основные q4_K, и более точные q6_K для отдельных слоёв).

Запуск команды квантования

Запускаем из корня папки llama.cpp (та же рабочая папка, что и на шаге 3.2). Сам инструмент лежит в подпапке build\bin, поэтому указываем его полным путём (либо заранее добавьте build\bin в PATH — тогда можно просто написать llama-quantize). Все остальные пути в команде относительные — отсчитываются от текущей папки:

build\bin\llama-quantize ..\models\Qwen3.8-27B\my_conversions\Qwen3.8-27B-F16.gguf ..\models\Qwen3.8-27B\my_conversions\Qwen3.8-27B-Q4_K_M.gguf Q4_K_M

Разберём по частям:

  • build\bin\llama-quantize — сам инструмент llama-quantize.exe из папки сборки. Если build\bin есть в PATH, этот путь можно опустить.

  • ..\models\Qwen3.8-27B\my_conversions\Qwen3.8-27B-F16.gguf — входной файл: полноразмерный мастер, созданный на шаге 3.2. Он только читается и не изменяется.

  • ..\models\Qwen3.8-27B\my_conversions\Qwen3.8-27B-Q4_K_M.gguf — выходной файл. Кладем его рядом с мастером в my_conversions: все варианты модели остаются в одном месте.

  • Q4_K_M — целевой тип квантования. Список всех поддерживаемых типов (q4_k_s, q5_k_m, q6_k, q8_0 и др.) можно посмотреть командой llama-quantize -h.

Проверка результата

После завершения в папке my_conversions должен оказаться файл Qwen3.8-27B-Q4_K_M.gguf размером ~16–17 ГБ (вместе с мастером F16). Проверяем:

dir ..\models\Qwen3.8-27B\my_conversions\Qwen3.8-27B-Q4_K_M.gguf

Если размер близок к ожидаемому (~16–17 ГБ) — квантование прошло успешно, и файл готов к загрузке в llama-server на шаге 4. Мастер-файл (~54 ГБ) при этом по-прежнему лежит в my_conversions — оставьте его на месте: из него можно получить другие варианты квантования.

⚠️ Примечания:

  • Свободное место. Перед запуском на целевом диске должно быть свободно не менее ~17 ГБ под результат (сам мастер при этом никуда не денется).

  • Не удаляйте мастер раньше времени. Квантование — операция односторонняя: F16 из Q4_K_M не восстановить.

  • Q4_K_M — не единственный вариант. Если после запуска покажется, что ответы модели заметно ухудшились, из того же мастера можно сделать Q5_K_M (~20 ГБ) — он тоже влезет в 24 ГБ видеопамяти и даст чуть лучшее качество. Q6_K (~22 ГБ) — верхняя граница для нашей карты; Q8_0 (~29 ГБ) целиком в VRAM уже не помещается.

4. Запускаем локальную модель Qwen3.8-27B

Все приготовления завершены: веса скачаны (пункт 3.1 выше), сконвертированы в GGUF (пункт 3.2 выше) и выполнения их квантизация в Q4_K_M (пункт 3.3 выше). Осталось загрузить модель в llama-server — серверную утилиту из состава llama.cpp, собранную в пункте 2. Она делает две вещи: поднимает HTTP-сервер с OpenAI-совместимым API (чтобы к модели могли обращаться программы) и предоставляет встроенный веб-интерфейс, где можно поговорить с моделью через чат в браузере.

Команда запуска (Windows, cmd):

llama-server -m ./my_conversions/Qwen3.8-27B-Q4_K_M.gguf -ngl 999 ^
 --port 8882 ^
 --temp 0.6  ^
 --top-p 0.95 ^
 --top-k 20 ^
 --min-p 0.00 ^
 -t 6 -c 64000 ^
 --cache-type-k q8_0 --cache-type-v q8_0 ^
 --parallel 1 --flash-attn on --presence-penalty 0.52 --repeat-penalty 1.0 --repeat-last-n 206 ^
 --reasoning-budget 8192 --reasoning-budget-message "Let's move on to the final answer." --chat-template-kwargs "{\"reasoning_effort\": \"xhigh\"}" ^
 --reasoning-preserve  --spec-type draft-mtp --spec-draft-n-max 3 ^
 --cache-ram 16384

⚠️ Два практических замечания перед разбором параметров:

  • Символ ^ в конце строки — это знак продолжения строки в cmd: все эти строки вместе образуют одну команду, разбитую на строки для читаемости. В PowerShell роль ^ играет обратная кавычка `.

  • Путь к модели указан относительно текущей папки: команду нужно выполнять из той папки, где лежит подпапка my_conversions (в нашей схеме это D:\models\Qwen3.8-27B), либо поправить путь под своё расположение файла.

Теперь разберём каждый параметр по отдельности:

Параметр

Расшифровка

llama-server

Сам исполняемый файл сервера (собран на шаге 2): загружает GGUF-файл, поднимает HTTP-сервер с OpenAI-совместимым API и встроенным веб-интерфейсом.

-m ./my_conversions/Qwen3.8-27B-Q4_K_M.gguf

-m (короткая форма --model) — путь к файлу модели. Здесь — квантизированный на шаге 3.3 файл Q4_K_M.

-ngl 99

Количество слоёв модели, которые нужно передать на GPU. 99 — означает разместить 99 слоёв в видеопамяти. Т.к. модель состоит из 64 слоев, этого значения более чем достаточно. Для других моделей значение количества слоёв нужно уточнять перед запуском.

--port 8882

TCP-порт HTTP-сервера (по умолчанию 8080). После запуска веб-интерфейс будет доступен по адресу http://localhost:8882.

--temp 0.6

Температура выборки: масштабирует вероятности токенов перед выбором. Меньше значение — более предсказуемые и «сфокусированные» ответы, больше — более случайные. 0.6 — умеренное значение, рекомендуемое для моделей Qwen.

--top-p 0.95

Ядерное (nucleus) сэмплирование: в выборку допускаются только токены, чья накопленная вероятность укладывается в 95%. Обрезает «хвост» маловероятных токенов.

--top-k 20

Оставляет для выбора только 20 самых вероятных токенов. Работает в связке с top-p — фактически действует более строгое из двух ограничений.

--min-p 0.00

Минимальная вероятность относительно лучшего токена: токены с вероятностью ниже min-p × P(лучший) отбрасываются. 0.00 — этот фильтр выключен.

-t 6

Число CPU-потоков для вычислений, идущих на процессоре (слои, не попавшие на GPU, вспомогательные операции). 6 — число физических ядер нашего i7-8700K (см. начало статьи).

-c 64000

Размер контекстного окна в токенах: сколько текста (промпт + сгенерированное) модель «видит» за один раз. 64000 токенов — большой контекст; именно он требует много памяти под KV-кэш (см. cache-type-* и cache-ram ниже).

--cache-type-k q8_0

Тип хранения K-части KV-кэша (ключи внимания): Q8_0 вместо F16 — вдвое меньше потребление памяти при почти незаметной потере качества.

--cache-type-v q8_0

То же самое, но для V-части KV-кэша (значения внимания).

--parallel 1

Число параллельных слотов (одновременных последовательностей): 1 — сервер обрабатывает по одному запросу за раз. Экономит память и подходит для одного пользователя.

--flash-attn on

Включает Flash Attention — оптимизированный алгоритм внимания: меньше потребление памяти и быстрее вычисления на этапе attention.

--presence-penalty 0.52

Штраф за присутствие: чем чаще токен уже встречался в сгенерированном тексте, тем ниже его вероятность — подавляет повторы. 0 — выключено, значения до 1 — сильнее подавление. 0.52 — умеренное значение.

--repeat-penalty 1.0

Штраф за повторение: множитель, применяемый к вероятностям уже встречавшихся токенов. 1.0 — выключено (не влияет на выбор).

--repeat-last-n 206

Окно (в токенах), в котором проверяются повторы для repeat-penalty: учитываются только повторы в пределах последних 206 токенов. Пока repeat-penalty = 1.0, параметр не активен.

--reasoning-budget 8192

Ограничение на число токенов в «размышляющей» (reasoning) части ответа: модель может потратить на «размышления» не более 8192 токенов. Не даёт модели думать бесконечно.

--reasoning-budget-message "Let's move on to the final answer."

Подсказка, которая подставляется в контекст, когда бюджет размышлений исчерпан.

--chat-template-kwargs "{\"reasoning_effort\": \"xhigh\"}"

Дополнительные параметры, передаваемые шаблону диалога (chat template): задаёт уровень интенсивности рассуждений xhigh (максимальный). Модели Qwen3 выбирают глубину «размышлений» как раз по этому параметру.

--reasoning-preserve

Сохранять блоки рассуждений модели в контексте между ходами диалога, а не выбрасывать их, то есть модель «помнит» собственные цепочки рассуждений в рамках разговора.

--spec-type draft-mtp

Включает спекулятивное декодирование с использованием встроенного в модель модуля MTP (Multi-Token Prediction) в роли «черновика»: черновик предлагает несколько токенов вперёд, а основная модель за один шаг проверяет их — генерация ускоряется.

--spec-draft-n-max 3

Максимальное число «черновых» токенов за один шаг спекуляции: предлагается и проверяется сразу до 3 токенов.

--cache-ram 16384

Ограничивает объём системной RAM (в мегабайтах), который допускается использовать под KV-кэш, если он целиком не помещается в видеопамять. 16384 МБ = 16 ГБ.

Что должно произойти после запуска:

  1. В консоли сервер напечатает лог загрузки: архитектуру модели, распределение слоёв между GPU и CPU, размер KV-кэша, а затем строку вида listening on http://127.0.0.1:8882.

  2. Открываем в браузере http://127.0.0.1:8882 — это встроенный веб-интерфейс на локалхосте, в нём можно сразу начать диалог с моделью.

  3. Заработает программный доступ — через OpenAI-совместимый API на том же порту (например, http://localhost:8882/v1/chat/completions).

⚠️ Примечания:

  • Остановка сервера — Ctrl+C в том терминале, где он запущен.

  • Первый запуск может занять заметно больше времени, чем следующие: сервер прогревает (warmup) вычисления и выделяет память под KV-кэш.

  • Если сервер сообщает, что часть слоёв не поместилась на GPU и осталась на CPU, то это не ошибка — просто уменьшите контекст (-c) или добавьте/усильте квантование KV-кэша; в нашем раскладе (Q4_K_M + q8_0-кэш + 64k контекст) всё должно уложиться в 24 ГБ VRAM.

  • Все параметры выборки (temp, top-p, top-k, штрафы) можно менять не только в команде запуска, но и в запросах к API — там они переопределяют значения по умолчанию сервера.

Вместо итогов

Если вы дошли до этого места, то значит, вас можно поздравить с первым опытом настройки и запуска модели локально! Теперь вы можете оценить, какой объём действий на самом деле нужно выполнять для, казалось бы, простой операции запуска модели.

Встроенный чат модели по ссылке http://127.0.0.1:8882 замеряет скорость генерации токенов модели, у меня получилась скорость генерации от 30 (без mtp-параметров) до 55 токенов в секунду (с mtp-параметрами). Также скорость генерации токенов можно посмотреть в логах терминала, в котором запущен llama-server.

⚠️ Если скорость генерации у модели получилась в районе 5-10 в секунду, то нужно посмотреть, нет ли сообщения от llama-server о нехватке объёма VRAM.

Далее поднятый локальный сервер можно использовать как безлимитный API при разработке с помощью агентов, но это уже тема отдельной статьи.

Буду признателен за обратную связь по формату и целесообразности подобных инструкций. Спасибо за внимание!

Источник

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    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 25.06.26 21:13 Emilie Safi

    A fraudulent investment scheme operated by BTCMining.limited functions as a fake return scam. In this setup, scammers lure victims with false promises of high returns. Through manipulative tactics, they gain individuals' trust and convince them to invest, ultimately leading to financial loss. If you have ever faced a cyber threat or fallen victim to an online crypto scam and need to reach the authorities, I recommend contacting [email protected], [email protected], WhatsApp +19852969146, telegram @resqprofirm. They are a legitimate team that helps victims of online crypto scams using advanced tools.

  • 25.06.26 21:25 Emilie Safi

    So I ended up losing $38,000 to this platform. At first, they kept asking me to put in more money so I could get into my portfolio. I did that, but then they wouldn’t let me withdraw anything—just kept asking for more deposits. It got way too suspicious, so I stopped. I found this company called ResQProfirm on Google and told them what happened. They got in touch, asked me to walk them through everything, and I gave them all the proof I had. They did an amazing job tracking down my money and getting it back. Big thanks to them at [email protected] and on WhatsApp at +19852969146. Please be careful out there and always research before investing.

  • 26.06.26 01:04 robertalfred175

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  • 26.06.26 01:04 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 26.06.26 02:48 Miriam Rocha

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  • 26.06.26 02:52 Miško Bakić

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  • 26.06.26 02:56 Asunción Herrera

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  • 26.06.26 15:05 Riley Stephens

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  • 28.06.26 00:37 kimberlyhebertt673

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  • 28.06.26 00:37 kimberlyhebertt673

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  • 29.06.26 22:37 riley777

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  • 30.06.26 15:08 wendytaylor015

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  • 30.06.26 15:08 wendytaylor015

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  • 02.07.26 01:22 Lieneke Bonnema

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  • 02.07.26 01:26 Clara Morin

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  • 04.07.26 15:32 Fraddy Pual

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  • 05.07.26 14:44 lydiassmith567

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  • 05.07.26 14:44 lydiassmith567

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  • 06.07.26 16:20 Olga Ognjanović

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  • 06.07.26 16:31 Joseph Weigl

    Invest wisely and stay cautious. Don't be influenced by promises of unusually high returns or convincing sales pitches from brokers. I learned this the hard way after falling victim to an investment scam that promised huge profits. Fortunately, I acted quickly and reported the incident to a recovery firm for assistance. Contact: Email: [email protected] Telegram: @Resqprofirm WhatsApp: +1 985 296 9146

  • 06.07.26 16:33 Jaran Løvlien

    A heartfelt thank you to RESQPRO FIRM for their commitment and professionalism throughout the investigation of my case. Their team worked diligently and helped recover assets valued at $88,000, which were returned to my wallet. I truly appreciate their support, clear communication, and dedication, and I'm grateful for the assistance I received. Contact: Email: [email protected] Telegram: @Resqprofirm WhatsApp: +1 985 296 9146

  • 07.07.26 18:00 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 07.07.26 18:01 robertalfred175

    CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 09.07.26 19:06 Toivo Walli

    I lost 8.56btc to a fake Bitcoin mining site, I tried withdrawing but couldn't approved my process, I reported to !R£SQPROFIRM! via °R£SQproFirm°àt°gmail•com° °tEL£°gram=R£SQprofirm °whaT°Zap+198°52°96°91°46

  • 09.07.26 19:10 Misty Alexander

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  • 09.07.26 19:13 Clara Soto

    Anyone receiving continued requests for additional deposits from a scam platform should immediately cut off communication and submit the case to a reputable re­covery service for investigation. R£sQprofirm is a dependable firm you can reach at °ResQproFirm°àt°g,*ma'il(•)¢om°, TEL£gram ResQprofirm, or |whaTZap| +1-985-296-9146.

  • 12.07.26 03:30 Kora Baltacha

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  • 12.07.26 03:33 Pahal Mathew

    It's important to move proactively by engaging an experienced recovery specialist. They will assist you throughout the process. To help them, provide: · Transaction evidence · Scammer information · Any additional relevant details The experts will then track and try to retrieve your funds from the scammers' hidden accounts or wallets. R£sQprofirm offers recovery assistance with no upfront fees. Contact: Telegram: @ResQprofirm WhatsApp: +19852969146 Email: [email protected]

  • 13.07.26 23:49 [email protected]

    One of the biggest concerns I have about cryptocurrency is the lack of regulation. It creates opportunities for scammers to invent convincing stories and fraudulent investment schemes. Unfortunately, some social media platforms continue to display these ads because they profit from them, even after users report them.I personally clicked on a Facebook advertisement for a company called Chickenfastmining and ended up losing more than $120,000 in a scam. I reported the ad, but nothing was done. Later, through a Reddit community, I found a recovery service called CYBERBERSPY that, in my personal experience, they helped me recover $110,000 of my lost funds. If you've been a victim of a cryptocurrency scam, don't lose hope. Explore your options carefully, and always verify the legitimacy of any recovery service before trusting them or paying any fees. Based on my own experience, CYBERBERSPY was helpful to me and i was able to recover my funds back, but I encourage everyone to do their own research before using any recovery service.i highly recommend: ([email protected])

  • 15.07.26 11:53 Sarah Green

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  • 15.07.26 11:58 Lily Gagné

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  • 16.07.26 21:38 patricialovick86

    How To Recover Your Bitcoin Without Falling Victim To Scams: A  Testimony Experience With Capital Crypto Recover Services, Contact Telegram: @Capitalcryptorecover Dear Everyone, I would like to take a moment to share my positive experience with Capital Crypto Recover Services. Initially, I was unsure if it would be possible to recover my stolen bitcoins. However, with their expertise and professionalism, I was able to fully recover my funds. Unfortunately, many individuals fall victim to scams in the cryptocurrency space, especially those involving fraudulent investment platforms. However, I advise caution, as not all recovery services are legitimate. I personally lost $273,000 worth of Bitcoin from my Binance account due to a deceptive platform. If you have suffered a similar loss, you may be considering crypto recovery, The Capital Crypto Recover is the most knowledgeable and effective Capital Crypto Recovery Services assisted me in recovering my stolen funds within 24 hours, after getting access to my wallet. Their service was not only prompt but also highly professional and effective, and many recovery services may not be trustworthy. Therefore, I highly recommend Capital Crypto Recover to you. i do always research and see reviews about their service, For assistance finding your misplaced cryptocurrency, get in touch with them, They do their jobs quickly and excellently, Stay safe and vigilant in the crypto world. Contact: [email protected]  You can reach them via email at [email protected] OR Call/Text Number +1 (336)390-6684 his contact website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 16.07.26 21:38 patricialovick86

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  • 20.08.26 11:32 michaeldavenport218

    I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR WhatsApp Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 23.08.26 20:02 leslieyee

    Excellent analysis by /dataviz! I was particularly struck by how strictly the order is defined: "data meaning first, color last" and how the validator actually adjusts the palette according to OKLCH, color blindness, and WCAG standards. These rules greatly improve the quality of charts. By the way, a similar approach to clean and legible charts is highly valued in trading—for example, on the ExpertOption platform, the interface and price visualization are designed to ensure information is read instantly and without unnecessary noise.

  • 25.08.26 13:44 lydiassmith567

    HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 25.08.26 13:44 lydiassmith567

    HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 30.08.26 15:37 [email protected]

    Discovering I had been defrauded, I searched online for services claiming to recover stolen ETH. I contacted several companies, but none succeeded. Although some claimed they could trace assets or recover funds, I could not verify their success or recover my money. I later found SYLVESTER BRYANT Recovery through Google. After contacting him, he recovered 450,000,00. He can be reached at [email protected] or WhatsApp at +1 512 577 7957.

  • 30.08.26 15:37 [email protected]

    Discovering I had been defrauded, I searched online for services claiming to recover stolen ETH. I contacted several companies, but none succeeded. Although some claimed they could trace assets or recover funds, I could not verify their success or recover my money. I later found SYLVESTER BRYANT Recovery through Google. After contacting him, he recovered 450,000,00. He can be reached at [email protected] or WhatsApp at +1 512 577 7957.

  • 01.09.26 11:16 lisawerth897

    My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684

  • 01.09.26 11:16 lisawerth897

    My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684

  • 01.09.26 17:34 Garry42

    Really crazy world. These fraudsters go at any length to steal your hard earned funds. I have been a victim of a bitcoin scam about 7 months back. A Con artist gained access to my cashapp account through a phishing scam. They stole $409,000. I was really devastated. I did everything to get back my funds by contacting the FBI but they claimed there was nothing they could do. A friend told me about a recovery expert. He helps fight against various phishing and investment scams and they were able to help trace and recover my funds even though it took over 2 days. you can reach out to him through recoverydarek@gmail. com . I can guarantee his services are still active.

  • 01.09.26 17:34 Garry42

    Really crazy world. These fraudsters go at any length to steal your hard earned funds. I have been a victim of a bitcoin scam about 7 months back. A Con artist gained access to my cashapp account through a phishing scam. They stole $409,000. I was really devastated. I did everything to get back my funds by contacting the FBI but they claimed there was nothing they could do. A friend told me about a recovery expert. He helps fight against various phishing and investment scams and they were able to help trace and recover my funds even though it took over 2 days. you can reach out to him through recoverydarek@gmail. com . I can guarantee his services are still active.

  • 02.09.26 03:43 kimberlyhebertt6877

    I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684

  • 02.09.26 03:43 kimberlyhebertt6877

    I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684

  • 04.09.26 21:51 Kovengray

    Recovering your lost investment funds as the case might be, is not what you can do alone, you’d require the service of a trained recovery specialist. A recovery specialist is a person or a group of people who are well equipped to work around the brokerage network. They have vast knowledge about the whole network and have the right software and private keys to follow any transaction. I was ripped off trading online to an investment broker, good thing I got every penny back through the help of Gavin ray he’s a genius Contact : Gavinray78 at gmail com or WhatsApp +1 352 322 2096 It is also important to be patient and really calm during the process.

  • 05.09.26 21:38 [email protected]

    I invested 45,000  Euro, and later aggreviated to 198,000 Euro.  I requested  to place ‎Withdrawal of my funds to be paid to my Bank account. But nothing happened I was subjected to pay more fee until I can get my funds on my account, i got in touch with Theodore ryan here on this platform who had helped a lot of people, I followed all instructions and he legally got back my withheld funds, I got threatened by the company that if I don’t pay they will get my account frozen, all thanks to Theodore ryan and I highly recommend him to anyone dealing with an unregulated broker company… contact him on his Gmail - theodoreryan318@  gmail .  com

  • 09.09.26 21:31 lisawerth897

    My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684

  • 09.09.26 21:31 lisawerth897

    My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684

  • 09.09.26 23:22 Fraddy Pual

    Hearing that these individuals are focusing on other people makes me very sad. I had a similar situation with them and lost a lot of money, but after learning about (Cruxcipherteam @ proton DoT me), whataqq:+168160-15021, telegram: @Cruxcipherteam I was able to get my money back. It's critical that we all be watchful and keep reporting these occurrences.

  • 11.09.26 03:23 kimberlyhebertt6877

    I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684

  • 11.09.26 03:23 kimberlyhebertt6877

    I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684

  • 15.09.26 03:35 elioduncan

    I fell victim to a freelance web development contract scam that ultimately cost me CAD 4,000. It all started when I came across a job posting on Indeed Canada, a popular online job portal. The position seemed perfect: a freelance web developer role for an established company looking for someone to design and build a fully functional e-commerce website. The job promised a high payment of CAD 20,000 upon successful completion, which sounded like a great opportunity for me to gain experience and earn decent pay.The employer, who introduced himself as a project manager from a "well-known" tech company, was very persuasive and professional in our initial communication. He explained that the project involved developing a user-friendly, responsive online store for their client and that they had a strict timeline to meet. He assured me that the payment would be made promptly after completing the tasks. However, before starting the work, he told me that I would need to pay an upfront fee of CAD 4,000 to cover certain software tools and licensing fees required for the project. This was supposedly a part of their company policy for freelance contractors, ensuring access to their premium resources. The idea of working on a professional project, coupled with the promise of a substantial payout, convinced me to pay the upfront fee.As soon as I made the payment, the project manager became increasingly difficult to reach. He initially responded to my emails and provided some vague instructions on what the project would entail, but as time went on, communication slowed to a complete halt. I never received the required tools or any proper project details. My emails went unanswered, and any attempts to contact the company were met with silence. After waiting for weeks, I realized that I had been scammed.Desperate to recover my money, I turned to TechY Force Cyber Retrieval, a service that specializes in helping victims of online scams. They helped me track the payment and took legal steps to pursue the fraudsters. Through their guidance, I was able to recover the full CAD 4,000. TechY Force Cyber Retrieval worked with my bank to reverse the transaction and liaised with the authorities to trace the scammer's details.This was a hard lesson, and I now know to be highly cautious about online job offers that require upfront payments. It is crucial to research companies thoroughly and avoid any job that seems too good to be true, especially when it involves paying money upfront. WhatsApp https://wa.link/2x6ktp Mail. [email protected]

  • 15.09.26 15:45 lydiassmith567

    HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 15.09.26 15:45 lydiassmith567

    HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

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