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Codestral-22B vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
Llama 4 Scout leads with 19.2% higher average benchmark score. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Llama 4 Scout is the stronger choice for coding tasks.
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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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Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
10 months newer
Codestral-22B
Mistral AI
2024-05-29
Llama 4 Scout
Meta
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 18 common benchmarks
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Codestral-22B
Average Score:25.6%
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Llama 4 Scout
Average Score:44.9%(+19.2%)
Provider Availability & Performance
Available providers and their performance metrics
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Codestral-22B
0 providers
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Llama 4 Scout
6 providers
DeepInfra
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Codestral-22B
Avg Score:25.6%
Providers:0
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Llama 4 Scout
Avg Score:44.9%(+19.2%)
Providers:6