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Codestral-22B vs Grok-3
Comprehensive side-by-side LLM comparison
Codestral-22B leads with 2.7% higher average benchmark score. Grok-3 supports multimodal inputs. 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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xAI
Grok-3 is a multimodal language model developed by xAI. This model demonstrates exceptional performance with an average score of 85.7% across 5 benchmarks. It excels particularly in AIME 2025 (93.3%), AIME 2024 (93.3%), GPQA (84.6%). It supports a 136K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents xAI's latest advancement in AI technology.
8 months newer
Codestral-22B
Mistral AI
2024-05-29
Grok-3
xAI
2025-02-17
Performance Metrics
Context window and performance specifications
Average performance across 12 common benchmarks
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Codestral-22B
Average Score:38.4%(+2.7%)
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Grok-3
Average Score:35.7%
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Knowledge Cutoff
Training data recency comparison
Grok-3
2024-11-17
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Codestral-22B
0 providers
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Grok-3
1 providers
xAI
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Codestral-22B
Avg Score:38.4%(+2.7%)
Providers:0
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Grok-3
Avg Score:35.7%
Providers:1