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GLM-4.6 vs Magistral Small 2506
Comprehensive side-by-side LLM comparison
GLM-4.6 leads with 19.5% higher average benchmark score. GLM-4.6 supports multimodal inputs. GLM-4.6 is available on 2 providers. Overall, GLM-4.6 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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Mistral AI
Magistral Small 2506 is a language model developed by Mistral AI. It achieves strong performance with an average score of 63.2% across 4 benchmarks. Notable strengths include AIME 2024 (70.7%), GPQA (68.2%), AIME 2025 (62.8%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI's latest advancement in AI technology.
3 months newer
Magistral Small 2506
Mistral AI
2025-06-10
GLM-4.6
Zhipu AI
2025-09-30
Performance Metrics
Context window and performance specifications
Average performance across 9 common benchmarks
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GLM-4.6
Average Score:47.6%(+19.5%)
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Magistral Small 2506
Average Score:28.1%
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Knowledge Cutoff
Training data recency comparison
Magistral Small 2506
2025-06-01
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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Magistral Small 2506
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GLM-4.6
Avg Score:47.6%(+19.5%)
Providers:2
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Magistral Small 2506
Avg Score:28.1%
Providers:0