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Codestral-22B vs GLM-4.6
Comprehensive side-by-side LLM comparison
Codestral-22B leads with 2.3% higher average benchmark score. GLM-4.6 supports multimodal inputs. GLM-4.6 is available on 2 providers. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Codestral-22B is a language model developed by Mistral AI. It achieves strong performance with an average score of 65.9% across 7 benchmarks. It excels particularly in HumanEvalFIM-Average (91.6%), HumanEval (81.1%), MBPP (78.2%). Released in 2024, it represents Mistral AI's latest advancement in AI technology.
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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.
1 year newer
Codestral-22B
Mistral AI
2024-05-29
GLM-4.6
Zhipu AI
2025-09-30
Performance Metrics
Context window and performance specifications
Average performance across 14 common benchmarks
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Codestral-22B
Average Score:32.9%(+2.3%)
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GLM-4.6
Average Score:30.6%
Provider Availability & Performance
Available providers and their performance metrics
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Codestral-22B
0 providers
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GLM-4.6
2 providers
DeepInfra
Throughput: 85 tok/s
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Codestral-22B
Avg Score:32.9%(+2.3%)
Providers:0
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GLM-4.6
Avg Score:30.6%
Providers:2