The AI arena is free today

Open Superagent

Mistral Large 4 vs Qwen3 VL 32B Thinking

Mistral Large 4 leads the LLM Stats Score 46.2 to 23.5.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Mistral Large 4 leads the overall LLM Stats Score 46.2 to 23.5, ranking #34 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Mistral Large 4

  • overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen3 VL 32B Thinking

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Mistral Large 4
Mistral AI
Qwen3 VL 32B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
46.2
#34
23.5
#189
Reasoning
44.0
#43
24.6
#170
Agents
34.3
#26
12.7
#112
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.68 / M
— / M
Output price
$2.09 / M
— / M
Context window
1,000,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Mistral Large 4
Qwen3 VL 32B Thinking
Vision
1.1#187
16.9#95
Multimodal
1.7#160
19.3#81
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

18 reported for Mistral Large 4 · 47 for Qwen3 VL 32B Thinking

No common benchmarks found

Mistral Large 4 and Qwen3 VL 32B Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1017.0B diff

Mistral Large 4 has 1017.0B more parameters than Qwen3 VL 32B Thinking, making it 3081.8% larger.

Mistral AI
Mistral Large 4
1.1Tparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
33.0Bparameters
1050.0B
Mistral Large 4
33.0B
Qwen3 VL 32B Thinking

Context Window

Maximum input and output token capacity

Only Mistral Large 4 specifies input context (1,000,000 tokens).

Mistral AI
Mistral Large 4
Input1,000,000 tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Mistral Large 4 and Qwen3 VL 32B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Mistral Large 4

Text
Images
Audio
Video

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Mistral Large 4 is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Mistral Large 4

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mistral Large 4 was released on 2026-10-06, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Mistral Large 4 is 13 months newer than Qwen3 VL 32B Thinking.

Mistral Large 4

Oct 6, 2026

1 days ago

1.0yr newer
Qwen3 VL 32B Thinking

Sep 22, 2025

1.0 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?

Judge for yourself.

Run your own prompts against Mistral Large 4 and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.

Mistral Large 4
✓ Preferred
Qwen3 VL 32B Thinking
Open in Playground

FAQ

Common questions about Mistral Large 4 vs Qwen3 VL 32B Thinking.

Which is better, Mistral Large 4 or Qwen3 VL 32B Thinking?

Mistral Large 4 leads the LLM Stats Score 46.2 to 23.5. Mistral Large 4 is made by Mistral AI and Qwen3 VL 32B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Mistral Large 4 compare to Qwen3 VL 32B Thinking in benchmarks?

Mistral Large 4 scores B3 AI Security Benchmark: 93.3%, CyBench: 93.0%, SciCode: 91.8%, KORABench: 84.5%, CyberGym: 82.0%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for Mistral Large 4 and Qwen3 VL 32B Thinking?

Mistral Large 4 supports 1.0M tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Mistral Large 4 and Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (46.2 vs 23.5), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral Large 4 and Qwen3 VL 32B Thinking?

Mistral Large 4 is developed by Mistral AI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

Related comparisons