Qwen2.5-Max
FreeExploring the Intelligence of Large-scale MoE Model.
FreeFree tier
Inputs: textOutputs: text
About Qwen2.5-Max
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) language model developed by the Qwen Team (Alibaba Cloud). Pretrained on over 20 trillion tokens and refined with Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF), it delivers competitive performance against leading proprietary and open-weight models such as DeepSeek V3, GPT-4o, and Claude-3.5-Sonnet. The model excels in benchmarks like Arena-Hard, LiveBench, LiveCodeBench, GPQA-Diamond, and MMLU-Pro. Qwen2.5-Max is accessible via Qwen Chat (with features like artifacts and search) and through an OpenAI-compatible API via Alibaba Cloud's Model Studio.
Key Features
Large-scale Mixture-of-Experts (MoE) architecture
Pretrained on over 20 trillion tokens
Post-trained with SFT and RLHF
State-of-the-art performance on Arena-Hard, LiveBench, LiveCodeBench, GPQA-Diamond
OpenAI-API compatible for easy integration
Available via Qwen Chat and Alibaba Cloud API
Pros & Cons
Pros
- Outperforms DeepSeek V3 on multiple key benchmarks
- Competitive with GPT-4o and Claude-3.5-Sonnet
- Large-scale training (20T tokens) driven by strong empirical scaling
- OpenAI-API compatible, reducing integration effort for developers
- Available both as a web chat and an API service
Best For
General conversational AICoding assistance and code generationKnowledge-based question answeringComplex reasoning tasksMultimodal applications (via Qwen ecosystem)
FAQ
How can I access Qwen2.5-Max?
You can use Qwen2.5-Max directly in the Qwen Chat web interface (with features like artifacts and search) or via the Alibaba Cloud Model Studio API. The API is OpenAI-API compatible.
What benchmarks does Qwen2.5-Max perform well on?
Qwen2.5-Max shows strong performance on Arena-Hard, LiveBench, LiveCodeBench, GPQA-Diamond, and MMLU-Pro, often outperforming or matching models like DeepSeek V3, GPT-4o, and Claude-3.5-Sonnet.
Is Qwen2.5-Max an open-source model?
The blog post does not state that Qwen2.5-Max is open-source. It is available via API and chat, but its weights are not explicitly released. The Qwen Team has a history of open-sourcing other models.
How was Qwen2.5-Max trained?
It was pretrained on over 20 trillion tokens and further refined using Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).