Qwen-Max

Qwen-Max by Alibaba excels in the Coding category, where it ranks #219 with a composite score of 42/100. Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown. It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

Qwen-Max is priced at $1.60 per million input tokens and $6.40 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, Qwen-Max holds rank #219 out of 6 models tracked. Its quality rank is #219 and adoption rank is #219. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

Qwen-Max has been evaluated across 6 different signals. Its strongest areas include Capabilities (43/100), Context Window (72/100), Output Capacity (65/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 42/100 reflects a weighted combination of all tracked signals.

Qwen-Max is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check Alibaba's website for current free tier availability and promotional offers.