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Devstral Medium vs Qwen3.8-27B

Comparing Devstral Medium and Qwen3.8-27B across benchmarks, pricing, and capabilities.

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

Which is better?

Devstral Medium 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 Devstral Medium

  • you want predictable pricing at $0.40/M input and $2.00/M output

Choose Qwen3.8-27B

  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.40 / M
— / M
Output price
$2.00 / M
— / M
Context window
128,000
Released
Jul 2025
Aug 2026
License
Proprietary
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Medium 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

Context Window

Maximum input and output token capacity

Only Devstral Medium specifies input context (128,000 tokens). Only Devstral Medium specifies output context (128,000 tokens).

Mistral AI
Devstral Medium
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input- tokens
Output- tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas Devstral Medium does not.

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

Devstral Medium

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Devstral Medium is licensed under a proprietary license, while Qwen3.8-27B uses Apache 2.0.

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

Devstral Medium

Proprietary

Closed source

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Devstral Medium was released on 2025-07-10, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 13 months newer than Devstral Medium.

Devstral Medium

Jul 10, 2025

1.1 years ago

Qwen3.8-27B

Aug 14, 2026

1 weeks ago

1.1yr 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 Devstral Medium and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Devstral Medium
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Devstral Medium vs Qwen3.8-27B.

Which is better, Devstral Medium or Qwen3.8-27B?

Devstral Medium (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 Devstral Medium compare to Qwen3.8-27B in benchmarks?

Devstral Medium scores SWE-Bench Verified: 61.6%. 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 context window sizes for Devstral Medium and Qwen3.8-27B?

Devstral Medium supports 128K tokens and Qwen3.8-27B 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 Devstral Medium and Qwen3.8-27B?

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

Who makes Devstral Medium and Qwen3.8-27B?

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