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 | 32B |
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 | 128k |
| These models have no shared benchmark scores. | ||
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 63.4% |
| Overview | ||
| Company | DeepSeek | Qwen |
| Release date | May 6 2024 | Mar 6 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek V2vsClaude Haiku 5.5QwQ-32BvsClaude Haiku 5.5DeepSeek V2vsGPT-6.1 SolQwQ-32BvsGPT-6.1 SolDeepSeek V2vsGemini 4 ArgonQwQ-32BvsGemini 4 ArgonDeepSeek V2vsMuse Spark OpenQwQ-32BvsMuse Spark OpenDeepSeek V2vsGrok 4.7QwQ-32BvsGrok 4.7DeepSeek V2vsMistral Large 4QwQ-32BvsMistral Large 4Frequently asked questions
DeepSeek V2 and QwQ-32B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V2 shipped 304 days before QwQ-32B, so benchmark comparisons should account for the intervening progress.
DeepSeek V2 has 236B parameters, while QwQ-32B has 32B. Context windows are 128k (DeepSeek V2) vs 128k (QwQ-32B).
Direct benchmark comparisons are unavailable — DeepSeek V2 and QwQ-32B don't publish scores on any of the same benchmarks.