Qwen3-4B-Instruct-2507
by Alibaba
Qwen3-4B-Instruct-2507 is a 4-billion-parameter causal language model designed for advanced instruction following, logical reasoning, text comprehension, mathematics, science, coding, and tool usage. It features a native context length of 262,144 tokens and is optimized for non-thinking mode, meaning it does not generate <think> blocks in its output. The model excels in subjective and open-ended tasks, providing helpful and high-quality responses. It is pretrained and post-trained for enhanced performance and alignment with user preferences. Qwen3-4B-Instruct-2507 can be deployed efficiently using frameworks like Hugging Face Transformers, SGLang, and vLLM, and supports extensive long-context understanding suitable for complex tasks.
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Weighted across four pillars · updated August 19, 2026
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