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. | 1.8B/3.25B | 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. | 32k | 32k |
| 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. | — | 50% |
| Overview | ||
| Company | Qwen | |
| Release date | Dec 6 2023 | Nov 28 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.0 NanovsClaude Haiku 5.5QwQ-32B-PreviewvsClaude Haiku 5.5Gemini 1.0 NanovsGPT-6.1 SolQwQ-32B-PreviewvsGPT-6.1 SolGemini 1.0 NanovsMuse Spark OpenQwQ-32B-PreviewvsMuse Spark OpenGemini 1.0 NanovsGrok 4.7QwQ-32B-PreviewvsGrok 4.7Gemini 1.0 NanovsDeepSeek-V4.1-Flash-1017QwQ-32B-PreviewvsDeepSeek-V4.1-Flash-1017Gemini 1.0 NanovsMistral Large 4QwQ-32B-PreviewvsMistral Large 4Frequently asked questions
Gemini 1.0 Nano and QwQ-32B-Preview don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.0 Nano shipped 358 days before QwQ-32B-Preview, so benchmark comparisons should account for the intervening progress.
Gemini 1.0 Nano has 1.8B/3.25B parameters, while QwQ-32B-Preview has 32B. Context windows are 32k (Gemini 1.0 Nano) vs 32k (QwQ-32B-Preview). Gemini 1.0 Nano is closed, while QwQ-32B-Preview is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.0 Nano and QwQ-32B-Preview don't publish scores on any of the same benchmarks.