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 | 9B |
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 | 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. | 50% | — |
| Overview | ||
| Company | Qwen | Z.ai |
| Release date | Nov 28 2024 | Jun 5 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
QwQ-32B-PreviewvsClaude Haiku 5.5GLM-4-9BvsClaude Haiku 5.5QwQ-32B-PreviewvsGPT-6.1 TerraGLM-4-9BvsGPT-6.1 TerraQwQ-32B-PreviewvsGemini 4 CarbonGLM-4-9BvsGemini 4 CarbonQwQ-32B-PreviewvsMuse Spark OpenGLM-4-9BvsMuse Spark OpenQwQ-32B-PreviewvsGrok 4.7GLM-4-9BvsGrok 4.7QwQ-32B-PreviewvsDeepSeek-V4.1-Flash-1017GLM-4-9BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
QwQ-32B-Preview and GLM-4-9B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. GLM-4-9B shipped 176 days before QwQ-32B-Preview, so benchmark comparisons should account for the intervening progress.
QwQ-32B-Preview has 32B parameters, while GLM-4-9B has 9B. Context windows are 32k (QwQ-32B-Preview) vs 128k (GLM-4-9B).
Direct benchmark comparisons are unavailable — QwQ-32B-Preview and GLM-4-9B don't publish scores on any of the same benchmarks.