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. | — | 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. | 1M | 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 | Qwen | |
| Release date | Feb 5 2025 | Mar 6 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 2.0 Flash-LitevsClaude Haiku 5.5QwQ-32BvsClaude Haiku 5.5Gemini 2.0 Flash-LitevsGPT-6.1 SolQwQ-32BvsGPT-6.1 SolGemini 2.0 Flash-LitevsMuse Spark OpenQwQ-32BvsMuse Spark OpenGemini 2.0 Flash-LitevsGrok 4.7QwQ-32BvsGrok 4.7Gemini 2.0 Flash-LitevsDeepSeek-V4.1-Flash-1017QwQ-32BvsDeepSeek-V4.1-Flash-1017Gemini 2.0 Flash-LitevsMistral Large 4QwQ-32BvsMistral Large 4Frequently asked questions
Gemini 2.0 Flash-Lite and QwQ-32B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 2.0 Flash-Lite shipped 29 days before QwQ-32B, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Gemini 2.0 Flash-Lite) vs 128k (QwQ-32B). Gemini 2.0 Flash-Lite is closed, while QwQ-32B is open weight.
Direct benchmark comparisons are unavailable — Gemini 2.0 Flash-Lite and QwQ-32B don't publish scores on any of the same benchmarks.