Model Comparison

DeepSeek-V2.5 vs Codestral-22BWhich is better in 2026?

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Verdict: DeepSeek-V2.5 vs Codestral-22B — which is better?

DeepSeek-V2.5 (by DeepSeek) and Codestral-22B (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V2.5 outperforms in 1 benchmarks (HumanEval), while Codestral-22B is better at 0 benchmarks. DeepSeek-V2.5 significantly outperforms across most benchmarks.

Choose DeepSeek-V2.5 if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Choose Codestral-22B if…

  • you want the most recent training data — it shipped May 2024
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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V2.5 outperforms in 1 benchmarks (HumanEval), while Codestral-22B is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Mon Jun 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

213.8B diff

DeepSeek-V2.5 has 213.8B more parameters than Codestral-22B, making it 963.1% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Mistral AI
Codestral-22B
22.2Bparameters
236.0B
DeepSeek-V2.5
22.2B
Codestral-22B

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Mon Jun 15 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Codestral-22B uses MNPL-0.1.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V2.5

deepseek

Open weights

Codestral-22B

MNPL-0.1

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Codestral-22B was released on 2024-05-29.

Codestral-22B is 1 month newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.1 years ago

Codestral-22B

May 29, 2024

2.0 years ago

3w newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
Higher HumanEval score (89.0% vs 81.1%)
Mistral AI

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Mistral AI
Codestral-22B

FAQ

Common questions about DeepSeek-V2.5 vs Codestral-22B.

Which is better, DeepSeek-V2.5 or Codestral-22B?

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and Codestral-22B is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V2.5 compare to Codestral-22B in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%.

What are the context window sizes for DeepSeek-V2.5 and Codestral-22B?

DeepSeek-V2.5 supports 8K tokens and Codestral-22B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V2.5 and Codestral-22B?

Key differences include licensing (deepseek vs MNPL-0.1). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Codestral-22B?

DeepSeek-V2.5 is developed by DeepSeek and Codestral-22B is developed by Mistral AI.

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