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 | 72B |
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 | 32k |
| Overview | ||
| Company | DeepSeek | Qwen |
| Release date | Sep 5 2024 | Nov 30 2023 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5vsClaude Haiku 5.5Qwen-72BvsClaude Haiku 5.5DeepSeek V2.5vsGPT-6.1 SolQwen-72BvsGPT-6.1 SolDeepSeek V2.5vsGemini 4 ArgonQwen-72BvsGemini 4 ArgonDeepSeek V2.5vsMuse Spark OpenQwen-72BvsMuse Spark OpenDeepSeek V2.5vsGrok 4.7Qwen-72BvsGrok 4.7DeepSeek V2.5vsMistral Large 4Qwen-72BvsMistral Large 4Frequently asked questions
DeepSeek V2.5 and Qwen-72B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen-72B shipped 280 days before DeepSeek V2.5, so benchmark comparisons should account for the intervening progress.
DeepSeek V2.5 has 236B parameters, while Qwen-72B has 72B. Context windows are 128k (DeepSeek V2.5) vs 32k (Qwen-72B).
Direct benchmark comparisons are unavailable — DeepSeek V2.5 and Qwen-72B don't publish scores on any of the same benchmarks.