Over the past three months, we have continued to scale the thinking capability of Qwen3-4B, improving both the quality and depth of reasoning. We are pleased to introduce Qwen3-4B-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. — Markedly better general capabilities, such as instruction following, tool usage, text generation, and alignment with human preferences. — Enhanced 256K long-context understanding capabilities. Qwen3-4B-Thinking-2507 has the following features: — Type: Causal Language Models — Training Stage: Pretraining & Post-training — Number of Parameters: 4.0B — Number of Paramaters (Non-Embedding): 3.6B — Number of Layers: 36 — Number of Attention Heads (GQA): 32 for Q and 8 for KV — Context Length: 262,144 natively. Additionally, to enforce model thinking, the default chat template automatically includes . Therefore, it is normal for the model’s output to contain only without an explicit opening tag. For more details, including benchmark evaluation, hardware requirements, and…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: cyankiwi
Теги: qwen3, conversational, text-generation-inference, endpoints_compatible, compressed-tensors
Лайков: 4 | Загрузок: 64
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
