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Mistral Large 4 vs Qwen2.5 VL 32B Instruct

Mistral Large 4 leads the LLM Stats Score 46.2 to 9.7.

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

Which is better?

Mistral Large 4 leads the overall LLM Stats Score 46.2 to 9.7, 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 coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen2.5 VL 32B Instruct

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

At a glance

The differences that matter most.

Core performance indexes
46.2
#34
9.7
#284
44.0
#43
8.4
#289
35.8
#27
12.3
#158
34.3
#26
-3.3
#194
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
Qwen2.5 VL 32B Instruct
1.1#187
6.3#156
1.7#160
9.0#130
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

18 reported for Mistral Large 4 · 28 for Qwen2.5 VL 32B Instruct

No common benchmarks found

Mistral Large 4 and Qwen2.5 VL 32B Instructdon'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

1016.5B diff

Mistral Large 4 has 1016.5B more parameters than Qwen2.5 VL 32B Instruct, making it 3034.3% larger.

Mistral AI
Mistral Large 4
1.1Tparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
33.5Bparameters
1050.0B
Mistral Large 4
33.5B
Qwen2.5 VL 32B Instruct

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
Qwen2.5 VL 32B Instruct
Input- tokens
Output- tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Mistral Large 4 and Qwen2.5 VL 32B Instruct support multimodal inputs.

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

Mistral Large 4

Text
Images
Audio
Video

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Mistral Large 4 is licensed under a proprietary license, while Qwen2.5 VL 32B Instruct 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

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mistral Large 4 was released on 2026-10-06, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

Mistral Large 4 is 20 months newer than Qwen2.5 VL 32B Instruct.

Mistral Large 4

Oct 6, 2026

2 days ago

1.6yr newer
Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.6 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 Qwen2.5 VL 32B Instruct side-by-side, then vote on the output you prefer.

Mistral Large 4
✓ Preferred
Qwen2.5 VL 32B Instruct
Open in Playground

FAQ

Common questions about Mistral Large 4 vs Qwen2.5 VL 32B Instruct.

Which is better, Mistral Large 4 or Qwen2.5 VL 32B Instruct?

Mistral Large 4 leads the LLM Stats Score 46.2 to 9.7. Mistral Large 4 is made by Mistral AI and Qwen2.5 VL 32B Instruct 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 Qwen2.5 VL 32B Instruct in benchmarks?

Mistral Large 4 scores B3 AI Security Benchmark: 93.3%, CyBench: 93.0%, SciCode: 91.8%, KORABench: 84.5%, CyberGym: 82.0%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.

What are the context window sizes for Mistral Large 4 and Qwen2.5 VL 32B Instruct?

Mistral Large 4 supports 1.0M tokens and Qwen2.5 VL 32B Instruct 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 Qwen2.5 VL 32B Instruct?

Key differences include LLM Stats Score (46.2 vs 9.7), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral Large 4 and Qwen2.5 VL 32B Instruct?

Mistral Large 4 is developed by Mistral AI and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.