Model Comparison

Codestral-22B vs DeepSeek-V4-Flash-0731Which is better in 2026?

Comparing Codestral-22B and DeepSeek-V4-Flash-0731 across benchmarks, pricing, and capabilities.

Verdict: Codestral-22B vs DeepSeek-V4-Flash-0731 — which is better?

Codestral-22B (by Mistral AI) and DeepSeek-V4-Flash-0731 (by DeepSeek) 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.

Choose Codestral-22B if…

  • you are already invested in the Mistral AI ecosystem

Choose DeepSeek-V4-Flash-0731 if…

  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and DeepSeek-V4-Flash-0731don'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

281.8B diff

DeepSeek-V4-Flash-0731 has 281.8B more parameters than Codestral-22B, making it 1269.4% larger.

Mistral AI
Codestral-22B
22.2Bparameters
DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
22.2B
Codestral-22B
304.0B
DeepSeek-V4-Flash-0731

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
Mon Aug 03 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while DeepSeek-V4-Flash-0731 uses MIT.

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

Codestral-22B

MNPL-0.1

Open weights

DeepSeek-V4-Flash-0731

MIT

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while DeepSeek-V4-Flash-0731 was released on 2026-07-31.

DeepSeek-V4-Flash-0731 is 26 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.2 years ago

DeepSeek-V4-Flash-0731

Jul 31, 2026

3 days ago

2.2yr 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

Mistral AI

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

DeepSeek
Larger context window (1,048,576 tokens)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Codestral-22B and DeepSeek-V4-Flash-0731 side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
DeepSeek-V4-Flash-0731
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
DeepSeek
DeepSeek-V4-Flash-0731

FAQ

Common questions about Codestral-22B vs DeepSeek-V4-Flash-0731.

Which is better, Codestral-22B or DeepSeek-V4-Flash-0731?

Codestral-22B (Mistral AI) and DeepSeek-V4-Flash-0731 (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-V4-Flash-0731 in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%.

What are the context window sizes for Codestral-22B and DeepSeek-V4-Flash-0731?

Codestral-22B supports an unknown number of tokens and DeepSeek-V4-Flash-0731 supports 1.0M 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-V4-Flash-0731?

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

Who makes Codestral-22B and DeepSeek-V4-Flash-0731?

Codestral-22B is developed by Mistral AI and DeepSeek-V4-Flash-0731 is developed by DeepSeek.

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