Mistral Small vs Qwen3 VL 30B A3B Thinking
Comparing Mistral Small and Qwen3 VL 30B A3B Thinking across benchmarks, pricing, and capabilities.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Mistral Small and Qwen3 VL 30B A3B Thinking trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Mistral Small is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 30B A3B Thinking also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Mistral Small
- cost matters — it's about 1.3x cheaper per token
Choose Qwen3 VL 30B A3B Thinking
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Mistral Small and Qwen3 VL 30B A3B Thinkingdon'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, Mistral Small ($0.20/1M tokens) costs the same as Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Mistral Small ($0.60/1M tokens) is 1.7x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than Mistral Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 30B A3B Thinking has 9.0B more parameters than Mistral Small, making it 40.9% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 30B A3B Thinking accepts 131,072 input tokens compared to Mistral Small's 32,768 tokens. Both models can generate responses up to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Mistral Small does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Small
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Mistral Small is licensed under Mistral Research License, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Mistral Research License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Mistral Small was released on 2024-09-17, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 12 months newer than Mistral Small.
Sep 17, 2024
1.9 years ago
Sep 22, 2025
11 months ago
1.0yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mistral Small is available from Mistral AI. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
Mistral Small
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small vs Qwen3 VL 30B A3B Thinking.