+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Codestral-22B vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 12.3% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
+
+
+
+
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.
+
+
+
+
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 OpenAI's latest advancement in AI technology.
10 months newer
Codestral-22B
Mistral AI
2024-05-29
GPT-4.1 nano
OpenAI
2025-04-14
Performance Metrics
Context window and performance specifications
Average performance across 32 common benchmarks
+
+
+
+
Codestral-22B
Average Score:14.4%
+
+
+
+
GPT-4.1 nano
Average Score:26.7%(+12.3%)
+
+
+
+
Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Codestral-22B
0 providers
+
+
+
+
GPT-4.1 nano
1 providers
OpenAI
+
+
+
+
Codestral-22B
Avg Score:14.4%
Providers:0
+
+
+
+
GPT-4.1 nano
Avg Score:26.7%(+12.3%)
Providers:1