Over the past three months, we have continued to scale the thinking capability of Qwen3-235B-A22B, improving both the quality and depth of reasoning. We are pleased to introduce Qwen3-235B-A22B-Thinking-2507, featuring the following key enhancements: — Significantly improved performance on reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks that typically require human expertise — achieving state-of-the-art results among open-source thinking models. — Markedly better general capabilities, such as instruction following, tool usage, text generation, and alignment with human preferences. — Enhanced 256K long-context understanding capabilities. Qwen3-235B-A22B-Thinking-2507 has the following features: — Type: Causal Language Models — Training Stage: Pretraining & Post-training — Number of Parameters: 235B in total and 22B activated — Number of Paramaters (Non-Embedding): 234B — Number of Layers: 94 — Number of Attention Heads (GQA): 64 for Q and 4 for KV — Number of Experts: 128 — Number of Activated Experts: 8 — Context Length: 262,144 natively. Additionally, to enforce model thinking, the default chat template automatically includes .…
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Генерация текста
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Диалог / чат
Задача: Генерация текста
Автор: QuantTrio
Теги: qwen3_moe, Qwen3, GPTQ, Int4-Int8Mix, 量化修复, vLLM, conversational, endpoints_compatible
Лайков: 4 | Загрузок: 17
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
