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[Перевод] Эволюция архитектур больших языковых моделей: от GPT-2 к современным решениям

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Прошло семь лет с момента разработки оригинальной архитектуры GPT. На первый взгляд, если оглянуться на GPT-2 (2019) и взглянуть вперёд на DeepSeek-V3 и Llama 4 (2024–2025), можно удивиться, насколько эти модели по-прежнему структурно схожи.

Разумеется, позиционные эмбеддинги эволюционировали от абсолютных к роторационным (RoPE), Multi-Head Attention в значительной степени уступил место Grouped-Query Attention, а более эффективная SwiGLU заменила такие функции активации, как GELU. Но если отбросить эти незначительные усовершенствования, действительно ли мы наблюдаем принципиальные архитектурные сдвиги — или просто продолжаем полировать одни и те же фундаментальные конструкции?

Сравнение LLM между собой с целью выявления ключевых факторов, влияющих на их качество (или недостатки), по-прежнему остаётся крайне нетривиальной задачей: датасеты, методы обучения и гиперпараметры сильно различаются и зачастую плохо документированы.

Тем не менее, я считаю, что изучение именно архитектурных изменений остаётся ценным подходом, позволяющим понять, над чем работают разработчики LLM в 2025 году. (Некоторые из этих архитектур показаны на Рисунке 1 ниже.)

Рисунок 1: Подмножество архитектур, рассмотренных в этой статье.
Рисунок 1: Подмножество архитектур, рассмотренных в этой статье.

Итак, в этой статье я не буду рассуждать о результатах бенчмарков или алгоритмах обучения — вместо этого сосредоточусь на архитектурных нововведениях, которые определяют современные флагманские open-source модели.

1. DeepSeek V3/R1

Как вы, вероятно, уже не раз слышали, модель DeepSeek R1 произвела серьёзный эффект при релизе в январе 2025 года. DeepSeek R1 — это reasoning-модель, построенная на архитектуре DeepSeek V3, представленной в декабре 2024 года.

Хотя основное внимание в этом материале уделено архитектурам, выпущенным в 2025 году, считаю уместным включить сюда и DeepSeek V3, поскольку широкое внимание и активное принятие она получила только после запуска DeepSeek R1.

В этом разделе я сосредоточусь на двух ключевых архитектурных техниках, представленных в DeepSeek V3, которые повысили вычислительную эффективность и отличают её от большинства других LLM:

  • Multi-Head Latent Attention (MLA)

  • Mixture-of-Experts (MoE)

1.1 Multi-Head Latent Attention (MLA)

Прежде чем перейти к Multi-Head Latent Attention (MLA), кратко напомню контекст, объясняющий, зачем вообще возникла эта техника. Начнём с Grouped-Query Attention (GQA) — это замена Multi-Head Attention (MHA), ставшая в последние годы новым стандартом благодаря большей вычислительной и параметрической эффективности.

Кратко о GQA: в отличие от классического MHA, где у каждой attention head свой набор ключей и значений, в GQA несколько head'ов делят одни и те же проекции ключей и значений для снижения потребления памяти.

Например, как показано на рисунке 2 ниже: при наличии двух KV-групп и четырёх attention head'ов, головы 1 и 2 могут использовать одну общую пару {K, V}, а головы 3 и 4 — другую. Это снижает общее число операций над ключами и значениями, уменьшает использование памяти и повышает эффективность (без заметного ущерба для качества моделирования, что подтверждается абляционными экспериментами).

Рисунок 2: Сравнение между MHA и GQA. Здесь размер группы составляет 2 — одна пара ключ/значение разделяется между двумя запросами.
Рисунок 2: Сравнение между MHA и GQA. Здесь размер группы составляет 2 — одна пара ключ/значение разделяется между двумя запросами.

Идея GQA сводится к уменьшению количества K/V-пар путём их шаринга между query head'ами. Это:

  1. Снижает общее количество параметров модели;

  2. Уменьшает нагрузку на память при инференсе, так как в KV-кэше нужно хранить и считывать меньшее число K и V тензоров.

Хотя GQA — это прежде всего оптимизация на уровне эффективности, абляционные исследования (например, в оригинальной статье про GQA и в статье Llama 2) показывают, что по качеству моделирования она сопоставима с классическим MHA.

Теперь — к Multi-Head Latent Attention (MLA). Это другая стратегия сокращения памяти, особенно эффективно работающая с KV-кешированием. В отличие от GQA, которая шарит K/V между head'ами, MLA сжимает тензоры ключей и значений в пространство меньшей размерности перед тем, как они будут сохранены в KV-кэш.

Во время инференса эти сжатые тензоры обратно проецируются в исходное пространство перед использованием — как показано на рисунке 3 ниже. Это добавляет одну дополнительную матричную операцию, но позволяет существенно снизить объём используемой памяти.

Рисунок 3: Сравнение между MLA (используется в DeepSeek V3 и R1) и обычным MHA.
Рисунок 3: Сравнение между MLA (используется в DeepSeek V3 и R1) и обычным MHA.

(К слову, query-компоненты также подвергаются сжатию, но только во время обучения, а не во время инференса.)

Кстати, MLA появилась не впервые в DeepSeek-V3 — эта архитектура использовалась (и даже была представлена) ещё в DeepSeek-V2. Кроме того, в статье по V2 приведены интересные результаты абляционных экспериментов, которые могут объяснить, почему команда DeepSeek отдала предпочтение MLA, а не GQA (см. рисунок 4 ниже).

Рисунок 4: Таблицы из статьи DeepSeek-V2, https://arxiv.org/abs/2405.04434
Рисунок 4: Таблицы из статьи DeepSeek-V2, https://arxiv.org/abs/2405.04434

Как показано на рисунке 4 выше, GQA демонстрирует более низкие результаты по сравнению с MHA, в то время как MLA обеспечивает лучшее качество моделирования, чем MHA — вероятно, именно поэтому команда DeepSeek выбрала MLA вместо GQA.

Резюмируя: MLA — это изящный приём, позволяющий сократить объём KV-кэша, при этом немного превосходя MHA по качеству моделирования.

1.2 Mixture-of-Experts (MoE)

Другим важным архитектурным компонентом в DeepSeek, заслуживающим внимания, является использование слоёв Mixture-of-Experts (MoE). Хотя MoE и не является изобретением DeepSeek, в этом году она вновь набрала популярность, и многие архитектуры, которые будут рассмотрены далее, также её используют.

Скорее всего, ты уже знаком с концепцией MoE, но короткое напоминание будет уместно.

Базовая идея MoE заключается в том, чтобы заменить каждый FeedForward-модуль в блоке трансформера на несколько expert-слоёв, каждый из которых по сути является таким же FeedForward-модулем. То есть вместо одного FeedForward-блока мы подставляем несколько, как показано на рисунке 5 ниже.

Рисунок 5: Иллюстрация модуля Mixture-of-Experts (MoE) в DeepSeek V3/R1 (справа) по сравнению с LLM, использующей стандартный FeedForward-блок (слева).
Рисунок 5: Иллюстрация модуля Mixture-of-Experts (MoE) в DeepSeek V3/R1 (справа) по сравнению с LLM, использующей стандартный FeedForward-блок (слева).

FeedForward-блок внутри трансформера (на рисунке выше он показан тёмно-серым цветом) содержит значительную часть всех параметров модели. (Стоит отметить, что блок трансформера, а вместе с ним и FeedForward-блок, повторяются многократно в LLM; в случае DeepSeek-V3 — 61 раз.)

Таким образом, замена одного FeedForward-блока на несколько (в MoE-конфигурации) существенно увеличивает общее число параметров модели. Однако ключевой трюк заключается в том, что не все эксперты используются ("активируются") для каждого токена. Вместо этого маршрутизатор выбирает лишь небольшое подмножество экспертов для каждого токена.

Поскольку активны только некоторые эксперты, MoE-модули часто называют разрежёнными (sparse), в отличие от плотных (dense) модулей, в которых участвуют все параметры. При этом большое общее количество параметров в MoE повышает ёмкость модели, то есть её способность усваивать больше знаний в процессе обучения. Разреженность же позволяет сохранить эффективность на этапе инференса, так как одновременно задействуется лишь небольшая часть параметров.

Например, в DeepSeek-V3 используется 256 экспертов на MoE-модуль, а общее количество параметров достигает 671 миллиарда. Но во время инференса одновременно активны только 9 экспертов (1 общий и 8, выбранных маршрутизатором). Это означает, что в расчёте на один шаг инференса задействуется лишь 37 миллиардов параметров — вместо всех 671.

Одной из примечательных особенностей MoE-дизайна в DeepSeek-V3 является использование shared expert — эксперта, который всегда активен для любого токена. Эта идея не нова: она была представлена в статьях DeepSeek 2024 MoE и ещё раньше — в DeepSpeedMoE (2022).

Рисунок 6: Иллюстрация из статьи "DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models", https://arxiv.org/abs/2401.06066
Рисунок 6: Иллюстрация из статьи "DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models", https://arxiv.org/abs/2401.06066

Преимущества наличия общего эксперта были впервые отмечены именно в DeepSpeedMoE, где показано, что это улучшает общее качество моделирования по сравнению с конфигурациями без shared expert. Вероятная причина — в том, что общие или повторяющиеся паттерны не нужно учить каждому индивидуальному эксперту отдельно, что оставляет больше места для обучения специализированных шаблонов.

1.3 Краткий итог по DeepSeek

Подводя итог: DeepSeek-V3 — это огромная модель с 671 миллиардом параметров, которая на момент запуска опережала все другие open-weight модели, включая Llama 3 на 405B. Несмотря на больший размер, модель гораздо эффективнее на этапе инференса за счёт архитектуры Mixture-of-Experts (MoE), где одновременно активируются только 37 миллиардов параметров на токен.

Другим ключевым отличием DeepSeek-V3 является использование Multi-Head Latent Attention (MLA) вместо Grouped-Query Attention (GQA). Обе схемы — это более эффективные альтернативы классической Multi-Head Attention (MHA) при использовании KV-кэша. Несмотря на большую сложность реализации MLA, исследования в статье по DeepSeek-V2 показывают, что она обеспечивает более высокое качество моделирования по сравнению с GQA.

2. OLMo 2

Серия моделей OLMo, разработанная некоммерческим Институтом искусственного интеллекта Аллена (Allen Institute for AI), заслуживает внимания благодаря своей прозрачности в отношении обучающих данных и кода, а также достаточно подробной технической документации.

Хотя вы вряд ли увидите OLMo в топах бенчмарков или лидербордов, модели из этой серии довольно «чистые» и, что более важно, служат отличным референсом для разработки LLM благодаря своей открытости.

Несмотря на то, что популярность OLMo 2 в первую очередь связана с прозрачностью, с точки зрения производительности они тоже вполне конкурентоспособны. На момент релиза в январе (до появления Llama 4, Gemma 3 и Qwen 3) модели OLMo 2 находились на границе Парето по соотношению вычислительных затрат и качества, как показано на рисунке 7 ниже.

Рисунок 7: Сравнение производительности на моделирующих бенчмарках (чем выше, тем лучше) и стоимости преподготовки (FLOPs; чем ниже, тем лучше) для различных LLM. Это иллюстрация из статьи OLMo 2: https://arxiv.org/abs/2501.00656
Рисунок 7: Сравнение производительности на моделирующих бенчмарках (чем выше, тем лучше) и стоимости преподготовки (FLOPs; чем ниже, тем лучше) для различных LLM. Это иллюстрация из статьи OLMo 2: https://arxiv.org/abs/2501.00656

Как уже упоминалось ранее, в рамках этой статьи я сосредотачиваюсь только на архитектурных особенностях LLM (без углубления в данные и обучение), чтобы сохранить объём в разумных пределах. Так что же интересного в архитектуре OLMo 2? В основном — это нормализации: размещение слоёв RMSNorm, а также добавление QK-norm, о чём будет сказано ниже.

Также стоит отметить, что OLMo 2 по-прежнему использует классический Multi-Head Attention (MHA), а не MLA или GQA.

2.1 Размещение слоёв нормализации

В целом, OLMo 2 в значительной степени наследует архитектуру оригинальной модели GPT, как и большинство современных LLM. Однако есть несколько важных отличий. Начнём со слоёв нормализации.

Подобно Llama, Gemma и большинству других LLM, OLMo 2 перешёл от LayerNorm к RMSNorm.

Но поскольку RMSNorm — это уже пройденный этап (по сути, упрощённая версия LayerNorm с меньшим числом обучаемых параметров), я не буду подробно разбирать различия между RMSNorm и LayerNorm.

Тем не менее, стоит обсудить именно размещение слоя RMSNorm. В оригинальном трансформере (в статье Attention is all you need) два слоя нормализации располагались внутри трансформерного блока — после модуля внимания и после FeedForward-модуля соответственно.

Такое размещение известно как Post-LN или Post-Norm.

GPT и большинство последующих LLM стали размещать слои нормализации до модулей внимания и FeedForward, что получило название Pre-LN или Pre-Norm. Сравнение Post- и Pre-Norm представлено на схеме ниже.

Рисунок 8: Сравнение Post-Norm, Pre-Norm и варианта Post-Norm из OLMo 2.
Рисунок 8: Сравнение Post-Norm, Pre-Norm и варианта Post-Norm из OLMo 2.

В 2020 году Xiong и соавт. показали, что Pre-LN даёт более устойчивые градиенты на инициализации. Также было отмечено, что Pre-LN хорошо работает даже без тщательной настройки learning rate warm-up, которая обычно критична для Post-LN.

OLMo 2 же применяет разновидность Post-LN (с RMSNorm вместо LayerNorm, поэтому я называю это просто Post-Norm).

В OLMo 2 нормализация располагается после attention и FeedForward, как показано на рисунке ниже. Но при этом, в отличие от оригинального трансформера, нормализация остаётся внутри резидуальных связей (skip connections).

Зачем понадобилось перемещать нормализацию? Ответ — для улучшения стабильности обучения, как показано на графике ниже.

Рисунок 9: График, демонстрирующий устойчивость обучения для Pre-Norm (как в GPT-2, Llama 3 и многих других) по сравнению с версией Post-Norm из OLMo 2. Иллюстрация из статьи OLMo 2: https://arxiv.org/abs/2501.00656
Рисунок 9: График, демонстрирующий устойчивость обучения для Pre-Norm (как в GPT-2, Llama 3 и многих других) по сравнению с версией Post-Norm из OLMo 2. Иллюстрация из статьи OLMo 2: https://arxiv.org/abs/2501.00656

К сожалению, на графике приведён эффект одновременно от перестановки нормализации и применения QK-Norm, так что невозможно точно оценить вклад каждой из техник по отдельности.

2.2 QK-Norm

Поскольку в предыдущем разделе уже упоминался QK-Norm, а в других моделях, о которых пойдёт речь позже (например, Gemma 2 и 3), он тоже используется, кратко объясню, что это.

QK-Norm — это ещё один слой RMSNorm. Он вставляется внутрь модуля Multi-Head Attention и применяется к векторам queries (q) и keys (k) до применения позиционного кодирования RoPE. Ниже приведён фрагмент реализации слоя Grouped-Query Attention (GQA), написанный для реализации Qwen 3 с нуля — применение QK-Norm в GQA аналогично его использованию в MHA у OLMo:

class GroupedQueryAttention(nn.Module):
    def __init__(
        self, d_in, num_heads, num_kv_groups,
        head_dim=None, qk_norm=False, dtype=None
    ):
        # ...

        if qk_norm:
            self.q_norm = RMSNorm(head_dim, eps=1e-6)
            self.k_norm = RMSNorm(head_dim, eps=1e-6)
        else:
            self.q_norm = self.k_norm = None

    def forward(self, x, mask, cos, sin):
        b, num_tokens, _ = x.shape

        # Apply projections
        queries = self.W_query(x) 
        keys = self.W_key(x)
        values = self.W_value(x) 

        # ...

        # Optional normalization
        if self.q_norm:
            queries = self.q_norm(queries)
        if self.k_norm:
            keys = self.k_norm(keys)

        # Apply RoPE
        queries = apply_rope(queries, cos, sin)
        keys = apply_rope(keys, cos, sin)

        # Expand K and V to match number of heads
        keys = keys.repeat_interleave(self.group_size, dim=1)
        values = values.repeat_interleave(self.group_size, dim=1)

        # Attention
        attn_scores = queries @ keys.transpose(2, 3)
        # ...

Как уже говорилось, вместе с Post-Norm, QK-Norm улучшает стабильность обучения. Отмечу, что QK-Norm был придуман не в OLMo 2 — он появился ещё в статье Scaling Vision Transformers в 2023 году.

2.3 Краткий итог по OLMo 2

Если кратко, ключевые архитектурные особенности OLMo 2 сводятся к следующему:

  • использование RMSNorm вместо LayerNorm;

  • размещение RMSNorm после, а не до attention и FeedForward (вариант Post-Norm);

  • добавление RMSNorm к queries и keys внутри attention-механизма (QK-Norm).

Обе эти модификации в совокупности улучшают стабильность функции потерь на обучении.

Ниже приведена сравнительная схема OLMo 2 и Llama 3 — как видно, архитектуры во многом схожи, за исключением того, что OLMo 2 продолжает использовать традиционный MHA, а не GQA. (Хотя команда OLMo выпустила версию на 32B спустя 3 месяца, в которой уже используется GQA.)

Рисунок 10: Сравнение архитектуры Llama 3 и OLMo 2.
Рисунок 10: Сравнение архитектуры Llama 3 и OLMo 2.

3. Gemma 3

Модели Gemma от Google всегда были весьма сильными, но, на мой взгляд, традиционно недооценёнными по сравнению с более «громкими» моделями, такими как серия LLaMA.

Одной из отличительных черт Gemma является довольно крупный словарь — это сделано для лучшей поддержки мультиязычности. Кроме того, у моделей акцент именно на размер 27B (в отличие от 8B или 70B). При этом стоит отметить, что Gemma 2 также доступна в меньших конфигурациях: 1B, 4B и 12B.

27B — это действительно удачный компромисс: модель заметно мощнее 8B, но при этом не требует таких ресурсов, как 70B.

Что ещё интересного в Gemma 3? Как мы уже обсуждали ранее, модели вроде DeepSeek-V3/R1 используют архитектуру Mixture-of-Experts (MoE) для снижения требований к памяти при инференсе при фиксированном размере модели. (Подход MoE используется и в других моделях, о которых мы поговорим позже.)

Gemma 3 применяет иной «трюк» для сокращения вычислительных затрат — sliding window attention.

3.1 Sliding Window Attention

Благодаря механизму sliding window attention (впервые представленному в работе LongFormer в 2020 году и уже применявшемуся в Gemma 2), команде Gemma 3 удалось существенно сократить требования к памяти в KV-кэше — как показано на схеме ниже.

Рисунок 11: Иллюстрация из статьи о Gemma 3 (https://arxiv.org/abs/2503.19786), показывающая экономию памяти KV-кэша благодаря механизму sliding window attention.
Рисунок 11: Иллюстрация из статьи о Gemma 3 (https://arxiv.org/abs/2503.19786), показывающая экономию памяти KV-кэша благодаря механизму sliding window attention.

Так что же такое sliding window attention? Если стандартный self-attention можно рассматривать как глобальный механизм внимания (каждый токен может взаимодействовать со всеми остальными), то sliding window attention — это локальное внимание, поскольку здесь область контекста ограничена определённым окном вокруг текущей query-позиции. Это показано на иллюстрации ниже.

Рисунок 12: Сравнение между обычным attention (слева) и sliding window attention (справа).
Рисунок 12: Сравнение между обычным attention (слева) и sliding window attention (справа).

Важно: sliding window attention можно использовать как с Multi-Head Attention, так и с Grouped-Query Attention (GQA); в Gemma 3 используется GQA.

Как упомянуто выше, sliding window attention также называют локальным вниманием, потому что окно ограничено и «скользит» вместе с позицией query. В отличие от этого, обычное self-attention глобально — каждый токен может взаимодействовать со всеми другими токенами.

Следует также отметить, что архитектура Gemma 2 тоже использовала sliding window attention. Разница в Gemma 3 — в изменении соотношения между глобальным и локальным вниманием.

Например, в Gemma 2 применялась гибридная схема: sliding window (локальное) внимание и глобальное внимание использовались в соотношении 1:1. Каждый токен имел доступ к контексту в окне шириной 4k токенов.

В то время как Gemma 2 использовала локальное внимание через один слой, в Gemma 3 это соотношение стало 5:1 — то есть, на каждые 5 слоёв с sliding window attention приходится всего 1 слой с глобальным вниманием. Более того, размер окна был уменьшен с 4096 (в Gemma 2) до 1024 токенов (в Gemma 3). Это делает модель более эффективной и смещает акцент в сторону локализованных вычислений.

Согласно их ablation-исследованию, использование sliding window attention практически не влияет на качество моделирования, что видно из графика ниже.

Рисунок 13: Иллюстрация из статьи о Gemma 3 (https://arxiv.org/abs/2503.19786), демонстрирующая, что sliding window attention практически не влияет на перплексию, генерируемую LLM.
Рисунок 13: Иллюстрация из статьи о Gemma 3 (https://arxiv.org/abs/2503.19786), демонстрирующая, что sliding window attention практически не влияет на перплексию, генерируемую LLM.

Хотя sliding window attention — наиболее заметная архитектурная особенность Gemma 3, я также кратко затрону размещение слоёв нормализации, как продолжение секции про OLMo 2.

3.2 Размещение слоев нормализации в Gemma 3

Небольшой, но интересный момент, заслуживающий внимания: в Gemma 3 используется RMSNorm как в Pre-Norm, так и в Post-Norm конфигурации вокруг модуля grouped-query attention.

Это схоже с тем, что было реализовано в Gemma 2, но всё же стоит отметить, поскольку отличается от:

  1. Post-Norm-схемы, применённой в оригинальном Transformer (“Attention is all you need”),

  2. Pre-Norm, ставшего популярным с GPT-2 и используемого во многих последующих архитектурах,

  3. Post-Norm-варианта в OLMo 2, который мы уже рассматривали ранее.

Рисунок 14: Сравнение архитектур OLMo2 и Gemma 3; обратите внимание на дополнительные слои нормализации в Gemma 3.
Рисунок 14: Сравнение архитектур OLMo2 и Gemma 3; обратите внимание на дополнительные слои нормализации в Gemma 3.

Считаю такой подход к размещению слоя нормализации достаточно интуитивным: он позволяет получить преимущества как Pre-Norm, так и Post-Norm. На мой взгляд, немного дополнительной нормализации — это не проблема. В худшем случае, если она окажется избыточной, мы просто получим небольшую неэффективность из-за дублирования. На практике же, учитывая относительную «дешевизну» RMSNorm с точки зрения вычислений, это не должно существенно повлиять на производительность.

3.3 Сводка по Gemma 3

Gemma 3 — это хорошо сбалансированная LLM, которая, как мне кажется, недооценена в open-source-среде. Самая интересная особенность — использование sliding window attention для повышения эффективности (будет любопытно посмотреть на её комбинацию с MoE в будущем).

Также у Gemma 3 уникальное размещение слоёв нормализации: RMSNorm применяется как до, так и после модулей attention и FeedForward.

3.4 Бонус: Gemma 3n

Через несколько месяцев после релиза Gemma 3 компания Google представила Gemma 3n — модификацию модели Gemma 3, оптимизированную под ограниченные вычислительные ресурсы с целью запуска на мобильных устройствах.

Одна из ключевых оптимизаций в Gemma 3n — использование слоя с параметрами Per-Layer Embedding (PLE). Основная идея здесь заключается в том, чтобы держать только подмножество параметров модели в памяти GPU. Эмбеддинги, специфичные для токенов и модальностей (текст, аудио, визуальные данные), подгружаются по мере необходимости из CPU или SSD.

На диаграмме ниже показана экономия памяти благодаря PLE: указывается 5.44 миллиарда параметров для стандартной версии Gemma 3. Вероятно, речь идёт о варианте Gemma 3 с 4 миллиардами параметров.

Рисунок 15: Иллюстрация из блога Google о Gemma 3n (https://developers.googleblog.com/en/introducing-gemma-3n/), демонстрирующая экономию памяти благодаря PLE.
Рисунок 15: Иллюстрация из блога Google о Gemma 3n (https://developers.googleblog.com/en/introducing-gemma-3n/), демонстрирующая экономию памяти благодаря PLE.

Несоответствие между 5.44 и 4 миллиардами объясняется тем, что Google использует нестандартный способ подсчёта параметров в LLM: эмбеддинги часто исключаются из общего числа параметров, чтобы модель казалась «меньше» — за исключением случаев, когда выгоднее указать большую цифру. Такая практика характерна не только для Google, но и стала общераспространённой в индустрии.

Ещё один интересный трюк — концепция MatFormer (сокращение от Matryoshka Transformer). Например, в Gemma 3n используется одна общая трансформер-архитектура, которую можно разрезать на более мелкие, автономно работающие части. Каждая такая «срезка» обучается выполнять задачи самостоятельно, так что на этапе инференса можно использовать только ту часть модели, которая реально нужна, без необходимости загружать всю архитектуру целиком.

4. Mistral Small 3.1

Модель Mistral Small 3.1 с 24 миллиардами параметров, выпущенная в марте вскоре после релиза Gemma 3, примечательна тем, что превзошла Gemma 3 27B по ряду бенчмарков (за исключением задач по математике), при этом обеспечивая более высокую скорость.

Низкая задержка инференса у Mistral Small 3.1 по сравнению с Gemma 3, вероятно, объясняется использованием кастомного токенизатора, а также сокращением объёма KV-кэша и количества слоёв. В остальном архитектура довольно стандартна, как показано на рисунке ниже.

Рисунок 16: Сравнение архитектур Gemma 3 27B и Mistral 3.1 Small 24B.
Рисунок 16: Сравнение архитектур Gemma 3 27B и Mistral 3.1 Small 24B.

Интересно, что более ранние версии моделей Mistral использовали sliding window attention, но от этой механики, похоже, отказались в Mistral Small 3.1. Таким образом, поскольку Mistral применяет обычный Grouped-Query Attention, а не Grouped-Query Attention с использованием скользящего окна, как в Gemma 3, возможно, появляются дополнительные преимущества в производительности за счёт возможности задействовать более оптимизированный код (например, FlashAttention). Я предполагаю, что хотя sliding window attention снижает потребление памяти, это не обязательно ведёт к снижению задержки инференса — а именно на этом сделан фокус в Mistral Small 3.1.

5. Llama 4

Развёрнутое обсуждение архитектуры Mixture-of-Experts (MoE), приведённое ранее в статье, вновь оказывается полезным — Llama 4 также реализует MoE-подход, при этом в остальном она использует довольно стандартную архитектуру, во многом схожую с DeepSeek-V3, как показано на схеме ниже. (Llama 4 изначально поддерживает мультимодальность — как и Gemma или Mistral. Однако в данной статье акцент сделан на языковом моделировании, поэтому рассматривается только текстовая часть модели.)

Рисунок 17: Сравнение архитектур DeepSeek V3 (671 миллиард параметров) и Llama 4 Maverick (400 миллиард параметров).
Рисунок 17: Сравнение архитектур DeepSeek V3 (671 миллиард параметров) и Llama 4 Maverick (400 миллиард параметров).

Хотя архитектура Llama 4 Maverick визуально очень похожа на DeepSeek-V3, между ними есть ряд примечательных различий.

Во-первых, Llama 4, как и её предшественники, использует Grouped-Query Attention, тогда как в DeepSeek-V3 реализован Multi-Head Latent Attention — мы подробно разбирали его в начале статьи. Обе модели относятся к крупным архитектурам, при этом DeepSeek-V3 примерно на 68% превосходит Llama 4 по общему количеству параметров. Однако по числу активных параметров перевес ещё более значителен: DeepSeek-V3 использует 37 миллиардов активных параметров против 17 миллиардов у Llama 4 Maverick.

В Llama 4 Maverick реализована более классическая конфигурация MoE — меньшее число, но более «тяжёлые» эксперты (2 активных эксперта с размерностью скрытого слоя 8192), в то время как в DeepSeek-V3 задействовано 9 активных экспертов с размерностью скрытого слоя по 2048. Кроме того, DeepSeek вставляет MoE-слои в каждый transformer-блок (за исключением первых трёх), тогда как Llama 4 чередует MoE и плотные (dense) модули в каждом втором блоке.

Учитывая множество мелких архитектурных отличий, трудно однозначно оценить их вклад в итоговую производительность модели. Тем не менее, основной вывод таков: архитектуры на базе MoE переживают стремительный рост популярности в 2025 году.

6. Qwen3

Qwen3 — очередная успешная серия, лидирующая в своей размерной категории. В линейке представлено 7 "плотных" (dense) моделей: 0.6B, 1.7B, 4B, 8B, 14B и 32B. И 2 модели с архитектурой Mixture-of-Experts: 30B-A3B и 235B-A22B.

(К слову, отсутствие пробела в “Qwen3” — не опечатка; я намеренно сохраняю оригинальное написание, выбранное разработчиками Qwen.)

6.1 Qwen3 (плотная архитектура)

Начнём с плотных моделей. На момент написания статьи модель 0.6B, возможно, является самой компактной среди современных open-weight LLM. И, по моему личному опыту, она показывает отличные результаты для своего размера. У неё высокая пропускная способность (tokens/sec) и небольшой объём используемой памяти — если вы планируете запускать её локально. Более того, благодаря малому числу параметров её удобно обучать локально (в образовательных целях).

Для большинства задач у меня Qwen3 0.6B уже вытеснила Llama 3 1B. Ниже приведено сравнение этих двух архитектур.

Рисунок 18: Сравнение архитектур Qwen3 0.6B и Llama 3 1B; обратите внимание, что Qwen3 — более глубокая архитектура с большим количеством слоёв, тогда как Llama 3 — более широкая, с большим числом attention-глав.
Рисунок 18: Сравнение архитектур Qwen3 0.6B и Llama 3 1B; обратите внимание, что Qwen3 — более глубокая архитектура с большим количеством слоёв, тогда как Llama 3 — более широкая, с большим числом attention-глав.

Представленные выше показатели вычислительной производительности получены с моей реализации на PyTorch при запуске на GPU A100. Как видно, Qwen3 имеет меньший объём памяти за счёт компактной архитектуры: используются более узкие скрытые слои и меньшее число attention-head'ов. Однако при этом в модели больше трансформер-блоков, чем в Llama 3, что приводит к более медленной генерации (ниже скорость в токенах в секунду).

6.2 Qwen3 (MoE)

Как уже упоминалось, Qwen3 также выпускается в двух MoE-вариантах: 30B-A3B и 235B-A22B. Почему одни архитектуры, вроде Qwen3, имеют как обычные (dense), так и MoE (sparse) версии?

Как отмечалось в начале статьи, MoE-варианты позволяют снизить расходы на инференс для крупных базовых моделей. Предоставление и dense-, и MoE-версий даёт пользователям гибкость в зависимости от их целей и ограничений.

Dense-модели, как правило, проще в fine-tuning’е, деплое и оптимизации под различное оборудование.

С другой стороны, MoE-модели оптимизированы под масштабируемый инференс. Например, при фиксированном бюджете на инференс они обеспечивают большую общую модельную ёмкость (то есть, способность поглощать знания на этапе обучения, за счёт увеличения размеров модели), при этом без пропорционального роста затрат на инференс.

Благодаря выпуску обеих версий, серия Qwen3 охватывает широкий спектр сценариев использования: dense-модели — для устойчивости, простоты и fine-tuning’а, а MoE-модели — для эффективного масштабируемого сервинга.

Чтобы завершить этот раздел, давайте сравним Qwen3 235B-A22B (обратите внимание, что A22B означает «22B активных параметров») с DeepSeek-V3, у которой почти вдвое больше активных параметров — 37B.

Рисунок 19: Сравнение архитектур DeepSeek-V3 и Qwen3 235B-A22B.
Рисунок 19: Сравнение архитектур DeepSeek-V3 и Qwen3 235B-A22B.

Как видно на графике выше, архитектуры DeepSeek-V3 и Qwen3 235B-A22B крайне схожи. Однако важно отметить, что Qwen3 отказались от использования shared expert — в то время как более ранние модели, такие как Qwen2.5-MoE, использовали общего эксперта.

К сожалению, команда Qwen3 не раскрыла причины, по которым они отказались от shared expert. Если предположить, возможно, это оказалось ненужным для обеспечения стабильности обучения при увеличении числа экспертов с 2 (в Qwen2.5-MoE) до 8 (в Qwen3). Таким образом, они смогли сэкономить ресурсы (вычисления/память), задействовав только 8, а не 8+1 экспертов. (Хотя это не объясняет, почему DeepSeek-V3 до сих пор использует shared expert.)

Обновление. Junyang Lin, один из разработчиков Qwen3, прокомментировал это следующим образом:

«В тот момент мы не увидели достаточно заметного прироста от использования shared expert и нас беспокоили возможные сложности с оптимизацией инференса, которые он может вызвать. Если честно, однозначного ответа на этот вопрос у нас нет».

7. SmolLM3

SmolLM3, возможно, не так популярен, как другие LLM, рассмотренные в этой статье, но он всё же заслуживает внимания: модель демонстрирует отличные показатели при относительно скромных и удобных 3 миллиардах параметров — промежуточном размере между 1.7B и 4B вариантами Qwen3, как показано на рисунке ниже.

Кроме того, как и в случае с OLMo, команда поделилась большим количеством информации о тренировочном процессе, что редкость и всегда высоко ценится.

Рисунок 20: Иллюстрация из анонсного поста SmolLM3 (https://huggingface.co/blog/smollm3), сравнивающая процент побед SmolLM3 с Qwen3 1.7B и 4B, а также с Llama 3 3B и Gemma 3 4B.
Рисунок 20: Иллюстрация из анонсного поста SmolLM3 (https://huggingface.co/blog/smollm3), сравнивающая процент побед SmolLM3 с Qwen3 1.7B и 4B, а также с Llama 3 3B и Gemma 3 4B.

Как видно из сравнительной схемы архитектур, SmolLM3 использует довольно стандартную архитектуру. Возможно, наиболее интересной особенностью модели является применение NoPE (No Positional Embeddings).

Рисунок 21: Сравнение архитектур Qwen3 4B и SmolLM3 3B в формате side-by-side.
Рисунок 21: Сравнение архитектур Qwen3 4B и SmolLM3 3B в формате side-by-side.

7.1 NoPE (No Positional Embeddings)

NoPE — это достаточно старая идея в контексте LLM, восходящая к статье 2023 года The Impact of Positional Encoding on Length Generalization in Transformers, где предлагалось отказаться от явной инъекции позиционной информации (например, через абсолютные позиционные эмбеддинги в ранних архитектурах GPT или современный RoPE).

В трансформерах позиционное кодирование обычно необходимо, поскольку self-attention изначально не учитывает порядок токенов. Абсолютные позиционные эмбеддинги решают эту проблему, добавляя отдельный эмбеддинг-слой, который кодирует позицию токена.

Рисунок 22: Модифицированная иллюстрация из книги Build A Large Language Model (From Scratch) (https://www.amazon.com/Build-Large-Language-Model-Scratch/dp/1633437167), демонстрирующая абсолютные позиционные эмбеддинги.
Рисунок 22: Модифицированная иллюстрация из книги Build A Large Language Model (From Scratch) (https://www.amazon.com/Build-Large-Language-Model-Scratch/dp/1633437167), демонстрирующая абсолютные позиционные эмбеддинги.

RoPE же действует иначе — он модифицирует (ротирует) векторы запросов и ключей в зависимости от позиции токена.

В слоях NoPE позиционный сигнал не добавляется вообще: ни фиксированный, ни обучаемый, ни относительный — никакой.

Несмотря на отсутствие явного позиционного кодирования, модель всё равно понимает порядок токенов благодаря маске причинности (causal attention mask), которая запрещает каждому токену «заглядывать» в будущее. Таким образом, токен в позиции t может «видеть» только токены в позициях ≤ t, что сохраняет автоагрессивный порядок.

Иными словами, хотя позиционная информация и не добавляется явно, в архитектуре модели всё равно есть встроенное направление, и модель может научиться использовать это при обучении градиентным спуском, если это помогает минимизировать loss. (Подробности — в теоремах из оригинальной статьи про NoPE.)

В целом, авторы статьи про NoPE показали не только то, что явное позиционное кодирование не обязательно, но и то, что отказ от него улучшает length generalization — способность LLM сохранять качество ответов при увеличении длины входной последовательности (см. график ниже).

Рисунок 23: Иллюстрация из статьи о NoPE (https://arxiv.org/abs/2305.19466), показывающая улучшенную обобщающую способность по длине благодаря NoPE.
Рисунок 23: Иллюстрация из статьи о NoPE (https://arxiv.org/abs/2305.19466), показывающая улучшенную обобщающую способность по длине благодаря NoPE.

Важно понимать, что эксперименты проводились на относительно маленькой GPT-подобной модели (~100M параметров) и с ограниченной длиной контекста. Пока неясно, насколько эти выводы масштабируются на современные крупные LLM.

Возможно, именно поэтому команда SmolLM3 применяет NoPE (или точнее, опускает RoPE) только в каждом четвёртом слое.

8. Kimi 2

Kimi 2 недавно наделал немало шума в AI-сообществе как open-weight модель с выдающейся производительностью. Согласно бенчмаркам, она наравне с лучшими проприетарными системами — такими как Gemini от Google, Claude от Anthropic и модели ChatGPT от OpenAI.

Особого внимания заслуживает использование варианта относительно нового оптимизатора Muon вместо классического AdamW. Насколько мне известно, это первый случай применения Muon в продакшн-модели такого масштаба — ранее он демонстрировал масштабируемость только до 16B параметров. Это дало отличную динамику функции потерь во время обучения, что, вероятно, и помогло модели резко вырваться в лидеры среди аналогов.

Хотя многие отмечали, что loss получился необычайно гладким (без характерных скачков), я бы не сказал, что он исключительно гладкий (например, посмотрите на кривую loss у OLMo 2 на графике ниже; к тому же, L2-норма градиента, возможно, была бы лучшей метрикой стабильности обучения). Но что действительно впечатляет — это скорость и стабильность убывания loss.

Тем не менее, как уже упоминалось во введении, методологии обучения — это тема для отдельного обсуждения.

Рисунок 24: Иллюстрации из блога, анонсирующего Kimi K2 (https://moonshotai.github.io/Kimi-K2/), и статьи о OLMo 2 (https://arxiv.org/abs/2305.19466).
Рисунок 24: Иллюстрации из блога, анонсирующего Kimi K2 (https://moonshotai.github.io/Kimi-K2/), и статьи о OLMo 2 (https://arxiv.org/abs/2305.19466).

Сама модель содержит 1 триллион параметров, что по-настоящему впечатляет.

На момент написания статьи это, вероятно, самая крупная LLM текущего поколения, если учитывать, что:

  • LLaMA 4 Behemoth ещё не вышла,

  • проприетарные LLM не учитываются,

  • а 1.6-триллионный Switch Transformer от Google — это энкодер-декодер архитектура из другого поколения.

Таким образом, круг замыкается: Kimi 2 использует архитектуру DeepSeek-V3, с которой мы начали эту статью, только в более масштабном виде, как показано на схеме ниже.

Рисунок 25: Сравнение архитектур DeepSeek V3 и Kimi K2.
Рисунок 25: Сравнение архитектур DeepSeek V3 и Kimi K2.

Как видно, Kimi 2.5 — это по сути тот же DeepSeek V3, но с большим числом экспертов в MoE-модулях и меньшим числом голов в модуле Multi-head Latent Attention (MLA).

Стоит отметить, что Kimi 2 — не взявшийся из ниоткуда проект. Более ранняя модель — Kimi 1.5, подробно описанная в статье Kimi k1.5: Scaling Reinforcement Learning with LLMs, уже тогда выглядела многообещающей. Однако ей не повезло: статья про DeepSeek R1 вышла в тот же день — 22 января. Кроме того, насколько мне известно, веса Kimi 1.5 так и не были опубликованы.

Судя по всему, команда Kimi учла этот опыт и выложила Kimi K2 как open-weight модель до релиза DeepSeek R2.

На момент написания, Kimi K2 — самая впечатляющая open-weight модель, доступная сообществу.

Заключение

Эволюция архитектур LLM в последние годы шла по пути итеративных улучшений, а не революционных прорывов. Технологии, такие как GQA, SwiGLU и RoPE, стали стандартом. В 2025 году мы наблюдаем взрыв популярности архитектур Mixture-of-Experts (MoE), которые позволяют создавать огромные модели (Llama 4, DeepSeek-V3, Kimi K2) с эффективным инференсом. Эти тенденции определяют будущее больших языковых моделей, предлагая разработчикам все более мощные и эффективные инструменты.

Источник

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  • 15.10.25 18:07 crypto

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  • 15.10.25 21:52 harristhomas7376

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  • 15.10.25 21:52 harristhomas7376

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  • 17.10.25 20:17 tyleradams

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  • 17.10.25 20:20 lindseyvonn

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  • 17.10.25 20:22 richardcharles

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  • 17.10.25 21:42 marcushenderson624

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  • 17.10.25 21:42 marcushenderson624

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  • 17.10.25 21:42 marcushenderson624

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  • 21.10.25 08:39 debby131

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  • 21.10.25 11:45 harristhomas7376

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  • 21.10.25 11:45 harristhomas7376

    "In the crypto world, this is great news I want to share. Last year, I fell victim to a scam disguised as a safe investment option. I have invested in crypto trading platforms for about 10yrs thinking I was ensuring myself a retirement income, only to find that all my assets were either frozen, I believed my assets were secure — until I discovered that my BTC funds had been frozen and withdrawals were impossible. It was a devastating moment when I realized I had been scammed, and I thought my Bitcoin was gone forever, Everything changed when a close friend recommended the Capital Crypto Recover Service. Their professionalism, expertise, and dedication enabled me to recover my lost Bitcoin funds back — more than €560.000 DEM to my BTC wallet. What once felt impossible became a reality thanks to their support. If you have lost Bitcoin through scams, hacking, failed withdrawals, or similar challenges, don’t lose hope. I strongly recommend Capital Crypto Recover Service to anyone seeking a reliable and effective solution for recovering any wallet assets. They have a proven track record of successful reputation in recovering lost password assets for their clients and can help you navigate the process of recovering your funds. Don’t let scammers get away with your hard-earned money – contact Email: [email protected] Phone CALL/Text Number: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 22.10.25 04:48 MATT PHILLIP

    I never imagined I’d fall for a crypto romance scam but it happened. Over the course of a few months, I sent nearly $150,000 worth of Bitcoin to someone I genuinely believed I was building a future with. When they disappeared without a trace, I was left heartbroken, humiliated, and financially devastated. For a long time, I didn’t tell anyone. I felt ashamed. But eventually, while searching for answers, I came across a Reddit thread that mentioned Agent Jasmine Lopez. I reached out, not expecting much. To my surprise, she treated me with kindness, not judgment. She used advanced tools like blockchain forensics, IP tracing, and smart contract analysis and with persistence and legal support, she was able to recover nearly 85% of what I lost. I know not everyone gets that kind of outcome, but thanks to [email protected] WhatsApp at +44 736-644-5035, I’ve started to reclaim not just my assets, but my confidence and peace of mind. If you’re going through something similar, you’re not alone and there is hope.

  • 22.10.25 07:36 donnacollier

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  • 22.10.25 11:59 elizabethrush89

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  • 22.10.25 11:59 elizabethrush89

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  • 22.10.25 16:31 MATT PHILLIP

    I never imagined I’d fall for a crypto romance scam but it happened. Over the course of a few months, I sent nearly $150,000 worth of Bitcoin to someone I genuinely believed I was building a future with. When they disappeared without a trace, I was left heartbroken, humiliated, and financially devastated. For a long time, I didn’t tell anyone. I felt ashamed. But eventually, while searching for answers, I came across a Reddit thread that mentioned Agent Jasmine Lopez. I reached out, not expecting much. To my surprise, she treated me with kindness, not judgment. She used advanced tools like blockchain forensics, IP tracing, and smart contract analysis and with persistence and legal support, she was able to recover nearly 85% of what I lost. I know not everyone gets that kind of outcome, but thanks to [email protected] WhatsApp at +44 736-644-5035, I’ve started to reclaim not just my assets, but my confidence and peace of mind. If you’re going through something similar, you’re not alone and there is hope.

  • 23.10.25 01:52 marcushenderson624

    Bitcoin Recovery Testimonial After falling victim to a cryptocurrency scam group, I lost $354,000 worth of USDT. I thought all hope was lost from the experience of losing my hard-earned money to scammers. I was devastated and believed there was no way to recover my funds. Fortunately, I started searching for help to recover my stolen funds and I came across a lot of testimonials online about Capital Crypto Recovery, an agent who helps in recovery of lost bitcoin funds, I contacted Capital Crypto Recover Service, and with their expertise, they successfully traced and recovered my stolen assets. Their team was professional, kept me updated throughout the process, and demonstrated a deep understanding of blockchain transactions and recovery protocols. They are trusted and very reliable with a 100% successful rate record Recovery bitcoin, I’m grateful for their help and highly recommend their services to anyone seeking assistance with lost crypto. Contact: [email protected] Phone CALL/Text Number: +1 (336) 390-6684 Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 23.10.25 01:52 marcushenderson624

    Bitcoin Recovery Testimonial After falling victim to a cryptocurrency scam group, I lost $354,000 worth of USDT. I thought all hope was lost from the experience of losing my hard-earned money to scammers. I was devastated and believed there was no way to recover my funds. Fortunately, I started searching for help to recover my stolen funds and I came across a lot of testimonials online about Capital Crypto Recovery, an agent who helps in recovery of lost bitcoin funds, I contacted Capital Crypto Recover Service, and with their expertise, they successfully traced and recovered my stolen assets. Their team was professional, kept me updated throughout the process, and demonstrated a deep understanding of blockchain transactions and recovery protocols. They are trusted and very reliable with a 100% successful rate record Recovery bitcoin, I’m grateful for their help and highly recommend their services to anyone seeking assistance with lost crypto. Contact: [email protected] Phone CALL/Text Number: +1 (336) 390-6684 Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 23.10.25 15:47 MATT PHILLIP

    I never imagined I’d fall for a crypto romance scam but it happened. Over the course of a few months, I sent nearly $150,000 worth of Bitcoin to someone I genuinely believed I was building a future with. When they disappeared without a trace, I was left heartbroken, humiliated, and financially devastated. For a long time, I didn’t tell anyone. I felt ashamed. But eventually, while searching for answers, I came across a Reddit thread that mentioned Agent Jasmine Lopez. I reached out, not expecting much. To my surprise, she treated me with kindness, not judgment. She used advanced tools like blockchain forensics, IP tracing, and smart contract analysis and with persistence and legal support, she was able to recover nearly 85% of what I lost. I know not everyone gets that kind of outcome, but thanks to [email protected] WhatsApp at +44 736-644-5035, I’ve started to reclaim not just my assets, but my confidence and peace of mind. If you’re going through something similar, you’re not alone and there is hope.

  • 23.10.25 21:43 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

  • 23.10.25 21:43 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

  • 24.10.25 06:08 MATT PHILLIP

    I never imagined I’d fall for a crypto romance scam but it happened. Over the course of a few months, I sent nearly $150,000 worth of Bitcoin to someone I genuinely believed I was building a future with. When they disappeared without a trace, I was left heartbroken, humiliated, and financially devastated. For a long time, I didn’t tell anyone. I felt ashamed. But eventually, while searching for answers, I came across a Reddit thread that mentioned Agent Jasmine Lopez. I reached out, not expecting much. To my surprise, she treated me with kindness, not judgment. She used advanced tools like blockchain forensics, IP tracing, and smart contract analysis and with persistence and legal support, she was able to recover nearly 85% of what I lost. I know not everyone gets that kind of outcome, but thanks to [email protected] WhatsApp at +44 736-644-5035, I’ve started to reclaim not just my assets, but my confidence and peace of mind. If you’re going through something similar, you’re not alone and there is hope.

  • 24.10.25 06:40 elizabethrush89

    God bless Capital Crypto Recover Services for the marvelous work you did in my life, I have learned the hard way that even the most sensible investors can fall victim to scams. When my USD was stolen, for anyone who has fallen victim to one of the bitcoin binary investment scams that are currently ongoing, I felt betrayal and upset. But then I was reading a post on site when I saw a testimony of Wendy Taylor online who recommended that Capital Crypto Recovery has helped her recover scammed funds within 24 hours. after reaching out to this cyber security firm that was able to help me recover my stolen digital assets and bitcoin. I’m genuinely blown away by their amazing service and professionalism. I never imagined I’d be able to get my money back until I complained to Capital Crypto Recovery Services about my difficulties and gave all of the necessary paperwork. I was astounded that it took them 12 hours to reclaim my stolen money back. Without a doubt, my USDT assets were successfully recovered from the scam platform, Thank you so much Sir, I strongly recommend Capital Crypto Recover for any of your bitcoin recovery, digital funds recovery, hacking, and cybersecurity concerns. You reach them Call/Text Number +1 (336)390-6684 His Email: [email protected] Contact Telegram: @Capitalcryptorecover Via Contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 24.10.25 06:40 elizabethrush89

    God bless Capital Crypto Recover Services for the marvelous work you did in my life, I have learned the hard way that even the most sensible investors can fall victim to scams. When my USD was stolen, for anyone who has fallen victim to one of the bitcoin binary investment scams that are currently ongoing, I felt betrayal and upset. But then I was reading a post on site when I saw a testimony of Wendy Taylor online who recommended that Capital Crypto Recovery has helped her recover scammed funds within 24 hours. after reaching out to this cyber security firm that was able to help me recover my stolen digital assets and bitcoin. I’m genuinely blown away by their amazing service and professionalism. I never imagined I’d be able to get my money back until I complained to Capital Crypto Recovery Services about my difficulties and gave all of the necessary paperwork. I was astounded that it took them 12 hours to reclaim my stolen money back. Without a doubt, my USDT assets were successfully recovered from the scam platform, Thank you so much Sir, I strongly recommend Capital Crypto Recover for any of your bitcoin recovery, digital funds recovery, hacking, and cybersecurity concerns. You reach them Call/Text Number +1 (336)390-6684 His Email: [email protected] Contact Telegram: @Capitalcryptorecover Via Contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 24.10.25 06:54 MATT PHILLIP

    I never imagined I’d fall for a crypto romance scam but it happened. Over the course of a few months, I sent nearly $150,000 worth of Bitcoin to someone I genuinely believed I was building a future with. When they disappeared without a trace, I was left heartbroken, humiliated, and financially devastated. For a long time, I didn’t tell anyone. I felt ashamed. But eventually, while searching for answers, I came across a Reddit thread that mentioned Agent Jasmine Lopez. I reached out, not expecting much. To my surprise, she treated me with kindness, not judgment. She used advanced tools like blockchain forensics, IP tracing, and smart contract analysis and with persistence and legal support, she was able to recover nearly 85% of what I lost. I know not everyone gets that kind of outcome, but thanks to [email protected] WhatsApp at +44 736-644-5035, I’ve started to reclaim not just my assets, but my confidence and peace of mind. If you’re going through something similar, you’re not alone and there is hope.

  • 24.10.25 18:18 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

  • 24.10.25 18:18 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

  • 25.10.25 00:49 tyleradams

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  • 25.10.25 00:50 stevekalfman

    If you ever need hacking services, look no further. I found myself in a difficult situation after losing almost $510,000 USD in bitcoin. I was distraught and had no hope of survival because i lost my life savings to this scam, I had no chance of recovering my investment. Until i came across an article on google about ([email protected]). A real-life recovery expert, everything changed completely after contacting him and explaining my ordeal to him and he quickly stepped in and assisted me in recovering 95% of my lost funds. They guarantee their clients and i got the highest level of happiness their services are highly recommended. so I’m putting this here for anyone who require their services too" Email: [email protected]

  • 25.10.25 05:05 victoriabenny463

    A few months ago, I fell for what looked like a legitimate online trading platform. The website was sleek, the support team was responsive, and they even showed me fake profit charts that seemed to grow daily. I started small, and after a few test withdrawals worked, I invested more eventually depositing 2 Bitcoin in hopes of long-term returns. But one morning, when I tried to withdraw, everything changed. The platform suddenly locked my account, claiming there were additional fees to release my funds. The support chat stopped responding, and the website started giving error messages. That’s when I realized I’d been scammed. I was devastated. Two Bitcoins wasn’t pocket change, it was my savings. I filed reports online, but everyone told me it was impossible to recover crypto once it’s sent. Then, through a discussion forum, I came across Dexdert Net Recovery, a team specializing in tracing and recovering stolen digital assets. Skeptical but desperate, I reached out. Their response was immediate and professional. They asked for transaction IDs, wallet addresses, screenshots of my correspondence with the fake platform, and any proof of payment I had. Within days, their analysts traced the stolen Bitcoin through multiple wallets using blockchain forensics, They updated me step-by-step, Working with their recovery experts and blockchain partners, Dexdert Net Recovery successfully froze the funds and verified ownership of my wallet. After 2 days of persistence and verification, I finally saw my 2 Bitcoin restored back into my own wallet. I couldn’t believe it. What stood out most wasn’t just that they recovered my funds, but how transparent and supportive the Dexdert team was throughout the process. They educated me on crypto safety, how to spot fake trading sites, and how to secure my digital assets in the future. Dexdert Net Recovery truly lives up to its name. They gave me back not just my Bitcoin, but my peace of mind. Reach Out Information Below Via: Email: ([email protected]) Telegram: (https://t.me/Dexdertprorecovery) WhatsApp: (+1 (859) 609‑4156)

  • 25.10.25 10:13 wendytaylor015

    My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 25.10.25 10:13 wendytaylor015

    My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 26.10.25 01:03 Christopherbelle

    A terrible financial shock hit me hard. I lost $860,000 in a fake crypto scheme. Things looked good until I tried to cash out my earnings. Suddenly, my account vanished into thin air. I told the police many times, but help never showed up. Despair washed over me; I felt totally beaten. Then, I found Sylvester Bryant Intelligence. Right away, they were skilled and honest about the whole thing. They looked deep into my situation. They tracked where the stolen funds went. They fought hard for me every step of the way. To my great surprise, they got my money back. I thought that was impossible. I owe them so much for their hard work and truthfulness. Sylvester Bryant Intelligence restored my peace. If scams took your crypto, contact them now. Contact Info: Yt7cracker@gmail . com WhatsApp: ‪+1 512 577 7957. or +44 7428 662701.

  • 26.10.25 18:09 victoriabenny463

    A few months ago, I fell for what looked like a legitimate online trading platform. The website was sleek, the support team was responsive, and they even showed me fake profit charts that seemed to grow daily. I started small, and after a few test withdrawals worked, I invested more eventually depositing 2 Bitcoin in hopes of long-term returns. But one morning, when I tried to withdraw, everything changed. The platform suddenly locked my account, claiming there were additional fees to release my funds. The support chat stopped responding, and the website started giving error messages. That’s when I realized I’d been scammed. I was devastated. Two Bitcoins wasn’t pocket change, it was my savings. I filed reports online, but everyone told me it was impossible to recover crypto once it’s sent. Then, through a discussion forum, I came across Dexdert Net Recovery, a team specializing in tracing and recovering stolen digital assets. Skeptical but desperate, I reached out. Their response was immediate and professional. They asked for transaction IDs, wallet addresses, screenshots of my correspondence with the fake platform, and any proof of payment I had. Within days, their analysts traced the stolen Bitcoin through multiple wallets using blockchain forensics, They updated me step-by-step, Working with their recovery experts and blockchain partners, Dexdert Net Recovery successfully froze the funds and verified ownership of my wallet. After 2 days of persistence and verification, I finally saw my 2 Bitcoin restored back into my own wallet. I couldn’t believe it. What stood out most wasn’t just that they recovered my funds, but how transparent and supportive the Dexdert team was throughout the process. They educated me on crypto safety, how to spot fake trading sites, and how to secure my digital assets in the future. Dexdert Net Recovery truly lives up to its name. They gave me back not just my Bitcoin, but my peace of mind. Reach Out Information Below Via: Email: ([email protected]) Telegram: (https://t.me/Dexdertprorecovery) WhatsApp: (+1 (859) 609‑4156)

  • 27.10.25 11:15 harristhomas7376

    "In the crypto world, this is great news I want to share. Last year, I fell victim to a scam disguised as a safe investment option. I have invested in crypto trading platforms for about 10yrs thinking I was ensuring myself a retirement income, only to find that all my assets were either frozen, I believed my assets were secure — until I discovered that my BTC funds had been frozen and withdrawals were impossible. It was a devastating moment when I realized I had been scammed, and I thought my Bitcoin was gone forever, Everything changed when a close friend recommended the Capital Crypto Recover Service. Their professionalism, expertise, and dedication enabled me to recover my lost Bitcoin funds back — more than €560.000 DEM to my BTC wallet. What once felt impossible became a reality thanks to their support. If you have lost Bitcoin through scams, hacking, failed withdrawals, or similar challenges, don’t lose hope. I strongly recommend Capital Crypto Recover Service to anyone seeking a reliable and effective solution for recovering any wallet assets. They have a proven track record of successful reputation in recovering lost password assets for their clients and can help you navigate the process of recovering your funds. Don’t let scammers get away with your hard-earned money – contact Email: [email protected] Phone CALL/Text Number: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 27.10.25 11:15 harristhomas7376

    "In the crypto world, this is great news I want to share. Last year, I fell victim to a scam disguised as a safe investment option. I have invested in crypto trading platforms for about 10yrs thinking I was ensuring myself a retirement income, only to find that all my assets were either frozen, I believed my assets were secure — until I discovered that my BTC funds had been frozen and withdrawals were impossible. It was a devastating moment when I realized I had been scammed, and I thought my Bitcoin was gone forever, Everything changed when a close friend recommended the Capital Crypto Recover Service. Their professionalism, expertise, and dedication enabled me to recover my lost Bitcoin funds back — more than €560.000 DEM to my BTC wallet. What once felt impossible became a reality thanks to their support. If you have lost Bitcoin through scams, hacking, failed withdrawals, or similar challenges, don’t lose hope. I strongly recommend Capital Crypto Recover Service to anyone seeking a reliable and effective solution for recovering any wallet assets. They have a proven track record of successful reputation in recovering lost password assets for their clients and can help you navigate the process of recovering your funds. Don’t let scammers get away with your hard-earned money – contact Email: [email protected] Phone CALL/Text Number: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 27.10.25 17:08 raymondgonzales

    Three Cheers for Wizard Hilton Cyber Tech, Bitcoin Savior Extraordinaire In the ever-evolving world of cryptocurrency, where volatility and uncertainty reign supreme, one individual has emerged as a beacon of hope and innovation - Wizard Hilton Cyber Tech, the self-proclaimed "Bitcoin Savior Extraordinaire." This enigmatic figure, with his uncanny ability to navigate the complexities of the digital asset landscape, has captivated the attention of crypto enthusiasts and skeptics alike. Wizard Hilton Cyber Tech journey began as a humble programmer, tinkering with the underlying blockchain technology that powers Bitcoin. But it was his visionary approach and unwavering commitment to the cryptocurrency's potential that propelled him into the limelight. Through a series of strategic investments, groundbreaking algorithmic trading strategies, and a knack for anticipating market shifts, Wizard Hilton Cyber Tech has managed to consistently outperform even the savviest of Wall Street traders. Wizard Hilton Cyber Tech ability to turn even the most tumultuous of Bitcoin price swings into opportunities for substantial gains has earned him the moniker "Wizard," a testament to his unparalleled mastery of the digital currency realm. But Wizard Hilton Cyber Tech impact extends far beyond personal wealth accumulation - Wizard Hilton Cyber Tech has tirelessly advocated for the widespread adoption of Bitcoin, working tirelessly to educate the public, lobby policymakers, and collaborate with industry leaders to overcome the barriers that have long hindered the cryptocurrency's mainstream acceptance. With infectious enthusiasm and boundless energy, Wizard Hilton Cyber Tech has become a true champion of the Bitcoin cause, inspiring a new generation of crypto enthusiasts to embrace the transformative power of this revolutionary technology. As the digital currency landscape continues to evolve, Wizard Hilton Cyber Tech name will undoubtedly be etched in the annals of cryptocurrency history as a visionary, a trailblazer, and, above all, the Bitcoin Savior Extraordinaire. To get your stolen bitcoin back, reach out to Wizard Hilton Cyber Tech via: Email : wizardhiltoncybertech ( @ ) gmail (. ) com WhatsApp number  +18737715701 Good Day.

  • 27.10.25 17:20 fatimanorth

    The Federal Trade Commission said that more than $1 billion had been lost to cryptocurrency scams in 2023. Victims frequently lose everything, including hope, trust, and wealth. When your hard-earned money disappears into digital shadows, you feel trapped. Nowadays, cryptocurrency frauds are very common. You can get help from recovery specialist Marie at [email protected] and via WhatsApp at +1 7127594675.

  • 28.10.25 00:55 elizabethrush89

    God bless Capital Crypto Recover Services for the marvelous work you did in my life, I have learned the hard way that even the most sensible investors can fall victim to scams. When my USD was stolen, for anyone who has fallen victim to one of the bitcoin binary investment scams that are currently ongoing, I felt betrayal and upset. But then I was reading a post on site when I saw a testimony of Wendy Taylor online who recommended that Capital Crypto Recovery has helped her recover scammed funds within 24 hours. after reaching out to this cyber security firm that was able to help me recover my stolen digital assets and bitcoin. I’m genuinely blown away by their amazing service and professionalism. I never imagined I’d be able to get my money back until I complained to Capital Crypto Recovery Services about my difficulties and gave all of the necessary paperwork. I was astounded that it took them 12 hours to reclaim my stolen money back. Without a doubt, my USDT assets were successfully recovered from the scam platform, Thank you so much Sir, I strongly recommend Capital Crypto Recover for any of your bitcoin recovery, digital funds recovery, hacking, and cybersecurity concerns. You reach them Call/Text Number +1 (336)390-6684 His Email: [email protected] Contact Telegram: @Capitalcryptorecover Via Contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 28.10.25 00:55 elizabethrush89

    God bless Capital Crypto Recover Services for the marvelous work you did in my life, I have learned the hard way that even the most sensible investors can fall victim to scams. When my USD was stolen, for anyone who has fallen victim to one of the bitcoin binary investment scams that are currently ongoing, I felt betrayal and upset. But then I was reading a post on site when I saw a testimony of Wendy Taylor online who recommended that Capital Crypto Recovery has helped her recover scammed funds within 24 hours. after reaching out to this cyber security firm that was able to help me recover my stolen digital assets and bitcoin. I’m genuinely blown away by their amazing service and professionalism. I never imagined I’d be able to get my money back until I complained to Capital Crypto Recovery Services about my difficulties and gave all of the necessary paperwork. I was astounded that it took them 12 hours to reclaim my stolen money back. Without a doubt, my USDT assets were successfully recovered from the scam platform, Thank you so much Sir, I strongly recommend Capital Crypto Recover for any of your bitcoin recovery, digital funds recovery, hacking, and cybersecurity concerns. You reach them Call/Text Number +1 (336)390-6684 His Email: [email protected] Contact Telegram: @Capitalcryptorecover Via Contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 29.10.25 03:43 Christopherbelle

    A sudden money crisis struck me. I dropped $82,000 to a phony crypto scam. All seemed fine until I went to pull out my gains. Then, i was unable to get back my hard earned money. I reported it to the police several times. No aid came my way. Deep sadness hit me; I felt crushed. That's when I learned about Sylvester Bryant Intelligence. They acted quick and fair from the start. They checked my case closely. They followed the path of my lost cash. They pushed strong for me at each turn. In shock, they brought my funds back. I had figured it could not happen. I thank them for their effort and honesty. Sylvester Bryant Intelligence gave me calm again. If a scam stole your crypto, reach out to them today. Contact Info: Yt7cracker@gmail . com WhatsApp: +1 512 577 7957 or +44 7428 662701.

  • 29.10.25 10:56 wendytaylor015

    My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 29.10.25 10:56 wendytaylor015

    My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

  • 30.10.25 09:49 Christopherbelle

    I suffered a huge money blow when $80,000 slipped away in a bogus crypto plot. It all looked great at first. Then I went to pull out my gains, and poof—my account was gone. I kept telling the cops about it, but they did zip. I felt shattered and lost. That's when I stumbled on Sylvester Bryant Intelligence. Things turned around fast. Right away, they showed clear steps, sharp know-how, and real drive to fix it. They tracked my missing cash step by step and pushed hard till they got it back. I swear, I figured it was a lost cause. Their straight-up work and trust brought back my calm. If a scam stole your crypto, reach out to them now. yt7cracker@gmail . com | WhatsApp: +1 512 577 7957 or +44 7428 662701

  • 30.10.25 12:03 elizabethrush89

    God bless Capital Crypto Recover Services for the marvelous work you did in my life, I have learned the hard way that even the most sensible investors can fall victim to scams. When my USD was stolen, for anyone who has fallen victim to one of the bitcoin binary investment scams that are currently ongoing, I felt betrayal and upset. But then I was reading a post on site when I saw a testimony of Wendy Taylor online who recommended that Capital Crypto Recovery has helped her recover scammed funds within 24 hours. after reaching out to this cyber security firm that was able to help me recover my stolen digital assets and bitcoin. I’m genuinely blown away by their amazing service and professionalism. I never imagined I’d be able to get my money back until I complained to Capital Crypto Recovery Services about my difficulties and gave all of the necessary paperwork. I was astounded that it took them 12 hours to reclaim my stolen money back. Without a doubt, my USDT assets were successfully recovered from the scam platform, Thank you so much Sir, I strongly recommend Capital Crypto Recover for any of your bitcoin recovery, digital funds recovery, hacking, and cybersecurity concerns. You reach them Call/Text Number +1 (336)390-6684 His Email: [email protected] Contact Telegram: @Capitalcryptorecover Via Contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1

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