Model Comparison

Codestral-22B vs DeepSeek-V3 0324

Comparing Codestral-22B and DeepSeek-V3 0324 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and DeepSeek-V3 0324 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

648.8B diff

DeepSeek-V3 0324 has 648.8B more parameters than Codestral-22B, making it 2922.5% larger.

Mistral AI
Codestral-22B
22.2Bparameters
DeepSeek
DeepSeek-V3 0324
671.0Bparameters
22.2B
Codestral-22B
671.0B
DeepSeek-V3 0324

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Sat May 02 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while DeepSeek-V3 0324 uses MIT + Model License (Commercial use allowed).

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

Codestral-22B

MNPL-0.1

Open weights

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while DeepSeek-V3 0324 was released on 2025-03-25.

DeepSeek-V3 0324 is 10 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

1.9 years ago

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

10mo 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

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Key Takeaways

Mistral AI

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

DeepSeek
Larger context window (163,840 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
DeepSeek
DeepSeek-V3 0324

FAQ

Common questions about Codestral-22B vs DeepSeek-V3 0324.

Which is better, Codestral-22B or DeepSeek-V3 0324?

Codestral-22B (Mistral AI) and DeepSeek-V3 0324 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Codestral-22B compare to DeepSeek-V3 0324 in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%.

What are the context window sizes for Codestral-22B and DeepSeek-V3 0324?

Codestral-22B supports an unknown number of tokens and DeepSeek-V3 0324 supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Codestral-22B and DeepSeek-V3 0324?

Key differences include licensing (MNPL-0.1 vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and DeepSeek-V3 0324?

Codestral-22B is developed by Mistral AI and DeepSeek-V3 0324 is developed by DeepSeek.