Mistral Small 4 vs Qwen3 VL 30B A3B Thinking
Mistral Small 4 and Qwen3 VL 30B A3B Thinking are closely matched at 19.0 and 18.3 on the LLM Stats Score. Mistral Small 4 is 1.5x cheaper per token.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Mistral Small 4 and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 19.0 and 18.3.
In the 4 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Small 4 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Small 4 also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Mistral Small 4
- cost matters — it's about 1.5x cheaper per token
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Mar 2026
Choose Qwen3 VL 30B A3B Thinking
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Mistral Small 4 · 50 for Qwen3 VL 30B A3B Thinking
Mistral Small 4 outperforms in 1 benchmarks (AIME 2025), while Qwen3 VL 30B A3B Thinking is better at 3 benchmarks (GPQA, MMLU-Pro, MMMU-Pro).
Qwen3 VL 30B A3B Thinking shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Mistral Small 4 ($0.15/1M tokens) is 1.3x cheaper than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Mistral Small 4 ($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 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Small 4 has 88.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 283.9% larger.
Context Window
Maximum input and output token capacity
Mistral Small 4 accepts 256,000 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. Mistral Small 4 can generate longer responses up to 256,000 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both Mistral Small 4 and Qwen3 VL 30B A3B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Mistral Small 4
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Mistral Small 4 was released on 2026-03-16, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Mistral Small 4 is 6 months newer than Qwen3 VL 30B A3B Thinking.
Mar 16, 2026
6 months ago
5mo newerSep 22, 2025
12 months ago
Knowledge 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 4 is available from Mistral AI. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
Mistral Small 4
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small 4 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small 4 vs Qwen3 VL 30B A3B Thinking.