Model Comparison

Devstral Medium vs Qwen3 VL 4B Thinking

Comparing Devstral Medium and Qwen3 VL 4B Thinking across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Medium and Qwen3 VL 4B Thinking 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

Qwen3 VL 4B Thinking costs less

For input processing, Devstral Medium ($0.40/1M tokens) is 4.0x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, Devstral Medium ($2.00/1M tokens) is 2.0x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, Devstral Medium is more expensive than Qwen3 VL 4B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Thu May 14 2026 • llm-stats.com

Devstral Medium

Input tokens$0.40

Output tokens$2.00

Best providerMistral

Qwen3 VL 4B Thinking

Input tokens$0.10

Output tokens$1.00

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Devstral Medium's 128,000 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Devstral Medium is limited to 128,000 tokens.

Devstral Medium

Input128,000 tokens

Output128,000 tokens

Qwen3 VL 4B Thinking

Input262,144 tokens

Output262,144 tokens

Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas Devstral Medium does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Devstral Medium

Text

Images

Audio

Video

Qwen3 VL 4B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Devstral Medium is licensed under a proprietary license, while Qwen3 VL 4B Thinking 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 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Devstral Medium was released on 2025-07-10, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 2 months newer than Devstral Medium.

Devstral Medium

Jul 10, 2025

10 months ago

Qwen3 VL 4B Thinking

Sep 22, 2025

7 months ago

2mo 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

Provider Availability

Devstral Medium is available from Mistral AI. Qwen3 VL 4B Thinking is available from DeepInfra.

Devstral Medium

Mistral

Input Price:Input: $0.40/1MOutput Price:Output: $2.00/1M

Qwen3 VL 4B Thinking

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Devstral Medium

View details

Mistral AI

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

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature	Devstral Medium	Qwen3 VL 4B Thinking

FAQ

Common questions about Devstral Medium vs Qwen3 VL 4B Thinking.

Which is better, Devstral Medium or Qwen3 VL 4B Thinking?

Devstral Medium (Mistral AI) and Qwen3 VL 4B Thinking (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 VL 4B Thinking in benchmarks?

Devstral Medium scores SWE-Bench Verified: 61.6%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is Devstral Medium cheaper than Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking is 4.0x cheaper for input tokens. Devstral Medium costs $0.40/M input and $2.00/M output via mistral. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.

What are the context window sizes for Devstral Medium and Qwen3 VL 4B Thinking?

Devstral Medium supports 128K tokens and Qwen3 VL 4B Thinking supports 262K 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 VL 4B Thinking?

Key differences include context window (128K vs 262K), input pricing ($0.40 vs $0.10/M), 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 VL 4B Thinking?

Devstral Medium is developed by Mistral AI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.