+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Codestral-22B vs Grok-4
Comprehensive side-by-side LLM comparison
Codestral-22B leads with 1.4% higher average benchmark score. Grok-4 supports multimodal inputs. Grok-4 is available on 2 providers. Both models have their strengths depending on your specific coding needs.
+
+
+
+
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.
+
+
+
+
xAI
Grok-4 is a multimodal language model developed by xAI. It achieves strong performance with an average score of 63.1% across 7 benchmarks. It excels particularly in AIME 2025 (91.7%), HMMT25 (90.0%), GPQA (87.5%). It supports a 264K 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. Released in 2025, it represents xAI's latest advancement in AI technology.
1 year newer
Codestral-22B
Mistral AI
2024-05-29
Grok-4
xAI
2025-07-09
Performance Metrics
Context window and performance specifications
Average performance across 14 common benchmarks
+
+
+
+
Codestral-22B
Average Score:32.9%(+1.4%)
+
+
+
+
Grok-4
Average Score:31.5%
+
+
+
+
Knowledge Cutoff
Training data recency comparison
Grok-4
2024-12-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Codestral-22B
0 providers
+
+
+
+
Grok-4
2 providers
xAI
+
+
+
+
Codestral-22B
Avg Score:32.9%(+1.4%)
Providers:0
+
+
+
+
Grok-4
Avg Score:31.5%
Providers:2