Model Comparison

Devstral Medium vs Qwen2.5 VL 7B Instruct

Comparing Devstral Medium and Qwen2.5 VL 7B Instruct across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Medium and Qwen2.5 VL 7B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri Apr 17 2026 • llm-stats.com
Mistral AI
Devstral Medium
Input tokens$0.40
Output tokens$2.00
Best providerMistral
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

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
Qwen2.5 VL 7B Instruct
Input- tokens
Output- tokens
Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 7B Instruct supports multimodal inputs, whereas Devstral Medium does not.

Qwen2.5 VL 7B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Devstral Medium

Text
Images
Audio
Video

Qwen2.5 VL 7B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Devstral Medium is licensed under a proprietary license, while Qwen2.5 VL 7B Instruct 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

Qwen2.5 VL 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Devstral Medium was released on 2025-07-10, while Qwen2.5 VL 7B Instruct was released on 2025-01-26.

Devstral Medium is 6 months newer than Qwen2.5 VL 7B Instruct.

Devstral Medium

Jul 10, 2025

9 months ago

5mo newer
Qwen2.5 VL 7B Instruct

Jan 26, 2025

1.2 years ago

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
Larger context window (128,000 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 7B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Devstral Medium
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct

FAQ

Common questions about Devstral Medium vs Qwen2.5 VL 7B Instruct

Devstral Medium (Mistral AI) and Qwen2.5 VL 7B Instruct (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.
Devstral Medium scores SWE-Bench Verified: 61.6%. Qwen2.5 VL 7B Instruct scores DocVQA: 95.7%, Android Control Low_EM: 91.4%, MobileMiniWob++_SR: 91.4%, ChartQA: 87.3%, OCRBench: 86.4%.
Devstral Medium supports 128K tokens and Qwen2.5 VL 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Devstral Medium is developed by Mistral AI and Qwen2.5 VL 7B Instruct is developed by Alibaba Cloud / Qwen Team.