Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 236B | >1T |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 128k | 256k |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $1.20 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $6.00 |
| — | $540Qwen list price | |
| Overview | ||
| Company | DeepSeek | Qwen |
| Release date | Sep 5 2024 | Sep 24 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5vsClaude Haiku 5.5Qwen3-MaxvsClaude Haiku 5.5DeepSeek V2.5vsGPT-6.1 SolQwen3-MaxvsGPT-6.1 SolDeepSeek V2.5vsGemini 4 ArgonQwen3-MaxvsGemini 4 ArgonDeepSeek V2.5vsMuse Spark OpenQwen3-MaxvsMuse Spark OpenDeepSeek V2.5vsGrok 4.7Qwen3-MaxvsGrok 4.7DeepSeek V2.5vsMistral Large 4Qwen3-MaxvsMistral Large 4Frequently asked questions
DeepSeek V2.5 and Qwen3-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3-Max has a verified first-party API price: $1.20 per million input tokens and $6.00 per million output tokens. No pay-as-you-go API rate is tracked for DeepSeek V2.5. DeepSeek V2.5 shipped 384 days before Qwen3-Max, so benchmark comparisons should account for the intervening progress.
DeepSeek V2.5 has 236B parameters, while Qwen3-Max has >1T. Context windows are 128k (DeepSeek V2.5) vs 256k (Qwen3-Max). DeepSeek V2.5 is open weight, while Qwen3-Max is closed.
Direct benchmark comparisons are unavailable — DeepSeek V2.5 and Qwen3-Max don't publish scores on any of the same benchmarks.