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Midnight Raid: How Alibaba Qwen3 Seized the Global Open Source Throne in One Go?

#AI25
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Alibaba's new model, Qwen3, has been released as an open-source project, quickly becoming the top open-source model globally. It features a hybrid reasoning model that integrates both fast and deep thinking processes, allowing for efficient responses to simple queries and thorough analysis of complex problems. With a total of 235 billion parameters and a pre-training dataset of 36 terabytes, Qwen3 outperforms leading models like DeepSeek-R1 and OpenAI's offerings while significantly reducing deployment costs. Key features include: - A hybrid reasoning approach with two modes: thoughtful (for complex issues) and non-thoughtful (for quick answers). - Support for 119 languages and dialects, enhancing its multilingual capabilities. - Improved performance in reasoning, instruction following, and tool integration. Qwen3 has received widespread acclaim, garnering 17,000 stars on GitHub within three hours of its release, reflecting strong interest from the developer community.

Late Night Raid, Alibaba Qwen3 Tops the Global Open Source Throne!#

Just early this morning, the highly anticipated new generation of Alibaba's Tongyi Qianwen model, Qwen3, was open-sourced! Upon its release, it immediately ascended to the throne of the world's strongest open-source model. Its parameter count is only 1/3 of DeepSeek-R1, but the cost has significantly decreased, and its performance has comprehensively surpassed that of R1, OpenAI-o1, and other top global models.

Features of Qwen3#

  • Hybrid Reasoning Model: The first "hybrid reasoning model" in China, integrating "fast thinking" and "slow thinking" into a single model.
    • For simple needs, it can provide answers with low computational power in "seconds."
    • For complex problems, it can perform multi-step "deep thinking," greatly saving computational resources.
  • Architecture and Parameters: Utilizes a mixture of experts (MoE) architecture, with a total parameter count of 235B, activating only 22B.
  • Pre-training Data: The pre-training data volume reaches 36T, and in the post-training phase, multiple rounds of reinforcement learning seamlessly integrate non-thinking modes into the thinking model.

Performance#

  • Benchmark Testing: Qwen3, upon its birth, immediately swept through major benchmarks.
  • Deployment Cost: While performance has significantly improved, deployment costs have drastically decreased, requiring only 4 H20 to deploy the full version of Qwen3, with memory usage being only 1/3 of similar performance models!

Highlights Summary#

  • Various sizes of dense models and mixture of experts (MoE) models, including 0.6B, 1.7B, 4B, 8B, 14B, 32B, as well as 30B-A3B and 235B-A22B.
  • Capable of seamless switching between thinking mode (for complex logical reasoning, mathematics, and coding) and non-thinking mode (for efficient general chatting).
  • Significantly enhanced reasoning capabilities, surpassing the previous QwQ in thinking mode and the Qwen2.5 instruct model in non-thinking mode.
  • More aligned with human preferences, excelling in creative writing, role-playing, multi-turn dialogue, and instruction following.
  • Proficient in AI agent capabilities, supporting precise integration with external tools in both thinking and non-thinking modes.
  • First to support 119 languages and dialects, with strong multilingual instruction following and translation capabilities.

Access Links#

As of now, Alibaba Tongyi has open-sourced over 200 models, with global downloads exceeding 300 million, and the number of Qianwen derivative models surpassing 100,000, completely surpassing the American Llama, becoming the world's first open-source model!

Qwen3 Family Debuts#

This time, Alibaba has open-sourced 8 hybrid reasoning models at once, including 2 MoE models of 30B and 235B, as well as 6 dense models of 0.6B, 1.7B, 4B, 8B, 14B, and 32B, all under the Apache 2.0 license.

  • The 30B parameter MoE model of Qwen3 achieves over 10 times the model performance leverage, with only 3B activated, comparable to the performance of the previous Qwen2.5-32B model.
  • The performance of Qwen3's dense models continues to break through, achieving the same high performance with half the parameter count.

New King of Open Source Models, Breaking Records#

Qwen3 has significantly enhanced reasoning, instruction following, tool calling, and multilingual capabilities, setting a new performance high for all domestic models and global open-source models—scoring 81.5 points in the AIME25 evaluation at the level of Olympiad mathematics, breaking the open-source record.

  • The flagship model Qwen3-235B-A22B has shown impressive results in coding, mathematics, and general capabilities across various benchmark tests compared to other top models (such as DeepSeek-R1, o1, o3-mini, Grok-3, and Gemini-2.5-Pro).

Main Features#

Hybrid Reasoning Mode#

The Qwen3 model introduces a hybrid problem-solving approach, supporting two modes:

  1. Thinking Mode: Step-by-step reasoning, suitable for complex problems.
  2. Non-Thinking Mode: Quickly provides answers, suitable for simple problems.

This flexibility allows users to control the model's reasoning process based on the complexity of the task.

Multilingual Support#

The Qwen3 model supports 119 languages and dialects, with great potential for creating international applications.

More Powerful Agent Capabilities#

Alibaba has optimized the Qwen3 model to enhance coding and agent capabilities, and has strengthened support for MCP.

Rave Reviews Across the Internet#

Within less than 3 hours of its open-source release, Qwen3 garnered 17k stars on GitHub, igniting enthusiasm in the open-source community. Developers are downloading it in droves, starting rapid testing.

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