Devstral Medium vs Qwen3 VL 4B Instruct
Comparing Devstral Medium and Qwen3 VL 4B Instruct across benchmarks, pricing, and capabilities.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Devstral Medium and Qwen3 VL 4B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3 VL 4B Instruct is roughly 3.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 4B Instruct also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
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 VL 4B Instruct
- cost matters — it's about 3.6x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Devstral Medium and Qwen3 VL 4B Instructdon'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
Pricing Analysis
Price comparison per million tokens
For input processing, Devstral Medium ($0.40/1M tokens) is 4.0x more expensive than Qwen3 VL 4B Instruct ($0.10/1M tokens).
For output processing, Devstral Medium ($2.00/1M tokens) is 3.3x more expensive than Qwen3 VL 4B Instruct ($0.60/1M tokens).
In conclusion, Devstral Medium is more expensive than Qwen3 VL 4B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 VL 4B Instruct accepts 262,144 input tokens compared to Devstral Medium's 128,000 tokens. Qwen3 VL 4B Instruct can generate longer responses up to 262,144 tokens, while Devstral Medium is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 4B Instruct supports multimodal inputs, whereas Devstral Medium does not.
Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Devstral Medium
Qwen3 VL 4B Instruct
License
Usage and distribution terms
Devstral Medium is licensed under a proprietary license, while Qwen3 VL 4B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Devstral Medium was released on 2025-07-10, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Qwen3 VL 4B Instruct is 2 months newer than Devstral Medium.
Jul 10, 2025
1.1 years ago
Sep 22, 2025
11 months ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Devstral Medium is available from Mistral AI. Qwen3 VL 4B Instruct is available from DeepInfra.
Devstral Medium
Qwen3 VL 4B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Devstral Medium and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Devstral Medium vs Qwen3 VL 4B Instruct.