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. | 16B/236B | — |
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 | 1M |
| Overview | ||
| Company | DeepSeek | Qwen |
| Release date | Jun 17 2024 | Nov 11 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek Coder V2vsClaude Fable 5.2Qwen4-Max PreviewvsClaude Fable 5.2DeepSeek Coder V2vsGPT-6.1 TerraQwen4-Max PreviewvsGPT-6.1 TerraDeepSeek Coder V2vsGemini 4 CarbonQwen4-Max PreviewvsGemini 4 CarbonDeepSeek Coder V2vsMuse EmberQwen4-Max PreviewvsMuse EmberDeepSeek Coder V2vsGrok 4.7Qwen4-Max PreviewvsGrok 4.7DeepSeek Coder V2vsMistral Large 4Qwen4-Max PreviewvsMistral Large 4Frequently asked questions
DeepSeek Coder V2 and Qwen4-Max Preview don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek Coder V2 shipped 877 days before Qwen4-Max Preview, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (DeepSeek Coder V2) vs 1M (Qwen4-Max Preview). DeepSeek Coder V2 is open weight, while Qwen4-Max Preview is closed.
Direct benchmark comparisons are unavailable — DeepSeek Coder V2 and Qwen4-Max Preview don't publish scores on any of the same benchmarks.