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Codestral-22B vs Qwen3.8-27B

Comparing Codestral-22B and Qwen3.8-27B across benchmarks, pricing, and capabilities.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Codestral-22B and Qwen3.8-27B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Codestral-22B

  • you are already invested in the Mistral AI ecosystem

Choose Qwen3.8-27B

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

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Qwen3.8-27B
Alibaba Cloud / Qwen Team
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—
Released
May 2024
Aug 2026
License
MNPL-0.1
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and Qwen3.8-27Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

5.6B diff

Qwen3.8-27B has 5.6B more parameters than Codestral-22B, making it 25.1% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
22.2B
Codestral-22B
27.8B
Qwen3.8-27B

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas Codestral-22B does not.

Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Qwen3.8-27B uses Apache 2.0.

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

Codestral-22B

MNPL-0.1

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 27 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.2 years ago

Qwen3.8-27B

Aug 14, 2026

1 weeks 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→

Judge for yourself.

Run your own prompts against Codestral-22B and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Codestral-22B vs Qwen3.8-27B.

Which is better, Codestral-22B or Qwen3.8-27B?

Codestral-22B (Mistral AI) and Qwen3.8-27B (Alibaba Cloud / Qwen Team) 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 Qwen3.8-27B in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the main differences between Codestral-22B and Qwen3.8-27B?

Key differences include multimodal support (no vs yes), licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Qwen3.8-27B?

Codestral-22B is developed by Mistral AI and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.

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