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Alibaba launches Qwen3 AI, claims it's better than DeepSeek R1: Details
Alibaba Group Holding unveiled the third generation of its open-source artificial intelligence (AI) model Qwen3 series, on Tuesday, raising the stakes in an increasingly competitive Chinese and global AI market. The Qwen3 family boasts faster processing speeds and expanded multilingual capabilities compared to other AI models, including DeepSeek-R1 and OpenAI's o1.
What is the Qwen3 series?
The Qwen3 range features eight models, varying from 600 million to 235 billion parameters, each offering performance improvements, according to Alibaba's cloud computing division. Parameters, often seen as a measure of an AI model's complexity and capability, are essential for tasks such as language understanding, coding, and mathematical problem-solving.
How do Qwen3 models compare to rivals?
According to benchmark tests, cited by the developors, the Qwen3-235B and Qwen3-4B models either matched or outperformed advanced competitors from both Chinese and international companies — including OpenAI's o1, Google's Gemini, and DeepSeek's R1 — particularly in instruction following, coding support, text generation, mathematical problem-solving, and complex reasoning.
"Qwen3 represents a significant milestone in our journey towards artificial general intelligence and artificial superintelligence," the Qwen team added, highlighting that enhanced pre-training and reinforcement learning had resulted in a marked leap in the models' intelligence.
"Notably, our smaller MoE model, Qwen3-30B-A3B, surpasses QwQ-32B, and even the compact Qwen3-4B rivals the performance of the much larger Qwen2.5-72B-Instruct," the company added in a blog post on the launch. ALSO READ |
Qwen3 introduces 'hybrid reasoning' capability
One of the standout features of the Qwen3 series is its hybrid reasoning capability. Users can select between a slower but deeper "thinking" mode for complex tasks and a faster "non-thinking" mode for quicker, simpler responses. This flexibility aims to cater to diverse user needs, from casual interactions to advanced problem-solving.
In contrast, DeepSeek-R1 primarily uses Chain-of-Thought (CoT) reasoning, a method where the model generates a sequence of thought steps or reasoning processes before providing a final answer.
Training for the Qwen3 models involved 36 trillion tokens across 119 languages and dialects, tripling the language scope achieved by its predecessor, Qwen2.5. This expansion is expected to significantly enhance the models' ability to understand and generate multilingual content.
Where and how to use Qwen3?
The new Qwen3 models are available for download on platforms such as Hugging Face, ModelScope, Kaggle, and Microsoft's GitHub. Alibaba recommends deployment using frameworks like SGLang and vLLM, while users who prefer local integration can turn to tools such as Ollama, LMStudio, MLX, llama.cpp, and KTransformers.
Global AI race
The release of Qwen3 arrives at a time when the global AI landscape is witnessing a surge of new developments. Baidu recently unveiled two upgraded models, and DeepSeek's R2 launch is also anticipated soon.
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