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GLM-4.6 vs QwQ-32B
Comprehensive side-by-side LLM comparison
QwQ-32B leads with 7.2% higher average benchmark score. GLM-4.6 supports multimodal inputs. GLM-4.6 is available on 2 providers. Overall, QwQ-32B is the stronger choice for coding tasks.
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Zhipu AI
GLM-4.6 is a multimodal language model developed by Zhipu AI. It achieves strong performance with an average score of 61.2% across 7 benchmarks. It excels particularly in AIME 2025 (93.9%), LiveCodeBench v6 (82.8%), GPQA (81.0%). It supports a 197K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Zhipu AI's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
QwQ-32B is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
6 months newer
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
GLM-4.6
Zhipu AI
2025-09-30
Performance Metrics
Context window and performance specifications
Average performance across 13 common benchmarks
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GLM-4.6
Average Score:33.0%
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QwQ-32B
Average Score:40.2%(+7.2%)
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Knowledge Cutoff
Training data recency comparison
QwQ-32B
2024-11-28
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GLM-4.6
2 providers
DeepInfra
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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QwQ-32B
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GLM-4.6
Avg Score:33.0%
Providers:2
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QwQ-32B
Avg Score:40.2%(+7.2%)
Providers:0