Qwen3.6和DeepSeek哪个更好用？2026年最新实测对比

欢迎来到 Qwen 的世界

Qwen 是由阿里巴巴集团 Qwen 团队研发的一系列大语言模型和大型多模态模型。无论是纯语言模型还是多模态模型，该系列均在超大规模的多语言和多模态数据集上进行了预训练，并通过高质量数据进行了后期微调，以更好地对齐人类偏好。Qwen 系列模型具备广泛的能力，包括自然语言理解、文本生成、视觉理解、音频理解、工具调用、角色扮演以及作为智能体进行交互等。

Qwen is a series of large language models (LLMs) and large multimodal models (LMMs) developed by the Qwen team at Alibaba Group. Both the language and multimodal models are pre-trained on massive multilingual and multimodal datasets, and subsequently fine-tuned with high-quality data to align closely with human preferences. The Qwen series possesses a wide range of capabilities, including natural language understanding, text generation, visual comprehension, audio understanding, tool usage, role-playing, and interaction as an AI agent.

Qwen3-2507：指令与思考模型的回归

基于社区的反馈和进一步的研究成果，专精于指令跟随的模型和专注于复杂思考的模型强势回归！其成果便是 Qwen3-2507 系列。

Drawing on community input and insights from further research, models specialized in instruction-following and complex thinking are making a strong comeback! The result is the Qwen3-2507 series.

Qwen3-Instruct-2507 核心特性

Qwen3-Instruct-2507 具备以下显著特性：

• 通用能力显著提升：在指令跟随、逻辑推理、文本理解、数学、科学、代码生成和工具使用等方面均有大幅进步。
• 多语言知识覆盖增强：在多种语言的长尾知识覆盖上取得了实质性增益。
• 主观任务对齐优化：在主观性和开放式任务中，与用户偏好的对齐度显著提高，能够提供更有帮助的回复和更高质量的文本生成。
• 长上下文理解能力：增强了 256K 长上下文理解能力，并可扩展至 1M。

Qwen3-Instruct-2507 boasts the following key features:

• Significant improvements in general capabilities: Major advancements in instruction following, logical reasoning, text comprehension, mathematics, science, coding, and tool usage.
• Enhanced multilingual knowledge coverage: Substantial gains in long-tail knowledge coverage across multiple languages.
• Optimized alignment for subjective tasks: Markedly better alignment with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text generation.
• Long-context understanding: Enhanced capabilities in 256K long-context understanding, extensible to 1M.

Qwen3-Thinking-2507 核心特性

Qwen3-Thinking-2507 具备以下核心优势：

• 推理性能卓越：在逻辑推理、数学、科学、代码生成以及通常需要人类专业知识的学术基准测试上，性能显著提升，在开源思考模型中达到了顶尖水平。
• 通用能力同步增强：在指令跟随、工具使用、文本生成以及与人类偏好对齐等通用能力上也有明显改善。
• 长上下文理解能力：同样具备增强的 256K 长上下文理解能力，并可扩展至 1M。

Qwen3-Thinking-2507 offers the following core advantages:

• Outstanding reasoning performance: 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.
• Concurrent enhancement of general capabilities: Markedly better general capabilities, such as instruction following, tool usage, text generation, and alignment with human preferences.
• Long-context understanding: Also features enhanced 256K long-context understanding capabilities, extensible to 1M.

Qwen3 (Qwen3-2504) 技术特性总览

Qwen3，亦称 Qwen3-2504，是 Qwen 系列的一个重要里程碑，其技术特性总结如下：

Qwen3, also known as Qwen3-2504, represents a significant milestone in the Qwen series. Its technical features are summarized below:

• 全尺寸模型矩阵：提供从 0.6B 到 235B 的全尺寸稠密与混合专家模型，包括 0.6B, 1.7B, 4B, 8B, 14B, 32B, 30B-A3B 和 235B-A22B。
• 双模式无缝切换：支持在思考模式（专用于复杂逻辑推理、数学和编码）与非思考模式（用于高效通用对话）之间进行无缝切换，确保在各种应用场景下的最优性能。
• 推理能力大幅增强：具备显著增强的推理能力，在数学、代码生成和常识逻辑推理方面，其思考模式超越了之前的 QwQ，其非思考模式也超越了 Qwen2.5 指令模型。
• 卓越的人类偏好对齐：拥有卓越的人类偏好对齐能力，在创意写作、角色扮演、多轮对话和指令跟随方面表现优异，能提供更自然、更具吸引力和沉浸感的对话体验。
• 领先的智能体能力：擅长智能体能力，可以在思考和非思考模式下精确集成外部工具，在复杂的基于智能体的任务中，于开源模型里表现领先。
• 强大的多语言支持：支持 100 多种语言和方言，具备强大的多语言理解、推理、指令跟随和生成能力。

• Full-Scale Model Matrix: Offers a complete range of dense and mixture-of-experts (MoE) models from 0.6B to 235B parameters, including 0.6B, 1.7B, 4B, 8B, 14B, 32B, 30B-A3B, and 235B-A22B.
• Seamless Dual-Mode Switching: Supports seamless switching between Thinking Mode (specialized for complex logical reasoning, mathematics, and coding) and Non-Thinking Mode (for efficient general conversation), ensuring optimal performance across various application scenarios.
• Substantially Enhanced Reasoning: Possesses significantly enhanced reasoning capabilities. In Thinking Mode, it surpasses the previous QwQ model, and in Non-Thinking Mode, it outperforms the Qwen2.5 Instruct model in mathematics, code generation, and commonsense logical reasoning.
• Exceptional Human Preference Alignment: Demonstrates exceptional alignment with human preferences, excelling in creative writing, role-playing, multi-turn dialogue, and instruction following to deliver more natural, engaging, and immersive conversational experiences.
• Leading Agent Capabilities: Excels in agent capabilities, enabling precise integration of external tools in both Thinking and Non-Thinking modes, achieving leading performance among open-source models in complex agent-based tasks.
• Powerful Multilingual Support: Supports over 100 languages and dialects, with strong multilingual understanding, reasoning, instruction-following, and generation capabilities.

Qwen3 系列模型规格对比

为了更清晰地展示 Qwen3 系列模型的差异与定位，我们将其核心规格整理如下：

特性维度	Qwen3-Instruct-2507	Qwen3-Thinking-2507	Qwen3 (2504) 系列
核心定位	通用指令跟随与对话	复杂推理与问题求解	全尺寸、多模态基础模型系列
突出能力	指令跟随、多语言生成、主观任务对齐	逻辑推理、数学、科学、编码	双模式切换、智能体能力、多语言支持
上下文长度	256K (可扩展至1M)	256K (可扩展至1M)	128K (部分模型支持更长)
模式支持	非思考模式 (默认)	思考模式 (默认)	思考与非思考模式无缝切换
模型规模	未明确 (推测为指令微调版本)	未明确 (推测为思考增强版本)	0.6B, 1.7B, 4B, 8B, 14B, 32B, 30B-A3B, 235B-A22B

资源与链接

想了解更多关于 Qwen 的详细信息、体验在线演示或获取模型资源，欢迎访问以下链接：

For more detailed information about Qwen, to try online demos, or to access model resources, please visit the following links:

• Qwen 主页 (Qwen Home Page)
• 与 Qwen 对话 (Chat with Qwen，具备深度研究和网页开发功能)
• 技术博客 (Blog)
• GitHub 仓库 (GitHub)
• Hugging Face 主页 (Hugging Face)
• ModelScope 主页 (ModelScope)
• Qwen3 模型集合 (Qwen3 Collection)

我们诚挚邀请您加入 Qwen 社区，与其他开发者和研究者交流。您可以通过 Discord 或扫描 微信群 二维码加入我们。期待与您相见！

We cordially invite you to join the Qwen community to exchange ideas with other developers and researchers. You can join us via Discord or by scanning the QR code for our WeChat group. We look forward to meeting you!

常见问题（FAQ）

Qwen3.6的智能体能力具体有哪些增强？

Qwen3.6在智能体能力方面表现领先，可在思考与非思考模式下精确集成外部工具，擅长处理复杂的基于智能体的任务，在开源模型中处于前沿水平。

Qwen3.6支持多长的上下文？

Qwen3.6系列具备增强的256K长上下文理解能力，并可扩展至1M，显著提升了处理长文档和多轮对话的能力。

Qwen3-Instruct和Qwen3-Thinking模型有什么区别？

Qwen3-Instruct专注于指令跟随与通用任务，在主观性任务中与用户偏好对齐度更高；Qwen3-Thinking专精于复杂逻辑推理、数学和代码生成，在推理性能上达到开源思考模型顶尖水平。