The AI arena is free today

Open Superagent

Ministral 3 (8B Instruct 2512) vs Qwen3 VL 4B Thinking

Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking are closely matched at 7.7 and 12.9 on the LLM Stats Score.

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

Which is better?

Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking are closely matched on the overall LLM Stats Score at 7.7 and 12.9.

In the 1 individual benchmarks reported for both models, Ministral 3 (8B Instruct 2512) wins 1; this is a narrower head-to-head signal than the composite indexes.

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

Choose Ministral 3 (8B Instruct 2512)

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Dec 2025

Choose Qwen3 VL 4B Thinking

  • you want predictable pricing at $0.10/M input and $1.00/M output

At a glance

The differences that matter most.

Core performance indexes
7.7
#285
12.9
#249
9.2
#263
14.0
#231
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.10 / M
Output price
— / M
$1.00 / M
Context window
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Ministral 3 (8B Instruct 2512)
Qwen3 VL 4B Thinking
8.1#83
11.0#72
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for Ministral 3 (8B Instruct 2512) · 48 for Qwen3 VL 4B Thinking

1 shared

Ministral 3 (8B Instruct 2512) outperforms in 1 benchmarks (MM-MT-Bench), while Qwen3 VL 4B Thinking is better at 0 benchmarks.

Ministral 3 (8B Instruct 2512) significantly outperforms across most benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

4.0B diff

Ministral 3 (8B Instruct 2512) has 4.0B more parameters than Qwen3 VL 4B Thinking, making it 100.0% larger.

Mistral AI
Ministral 3 (8B Instruct 2512)
8.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
8.0B
Ministral 3 (8B Instruct 2512)
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

Mistral AI
Ministral 3 (8B Instruct 2512)
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking support multimodal inputs.

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

Ministral 3 (8B Instruct 2512)

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Ministral 3 (8B Instruct 2512)

Apache 2.0

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Ministral 3 (8B Instruct 2512) was released on 2025-12-04, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Ministral 3 (8B Instruct 2512) is 2 months newer than Qwen3 VL 4B Thinking.

Ministral 3 (8B Instruct 2512)

Dec 4, 2025

9 months ago

2mo newer
Qwen3 VL 4B Thinking

Sep 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.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

Ministral 3 (8B Instruct 2512)
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground

FAQ

Common questions about Ministral 3 (8B Instruct 2512) vs Qwen3 VL 4B Thinking.

Which is better, Ministral 3 (8B Instruct 2512) or Qwen3 VL 4B Thinking?

Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking are closely matched on the LLM Stats Score at 7.7 and 12.9. Ministral 3 (8B Instruct 2512) is made by Mistral AI and Qwen3 VL 4B 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 Ministral 3 (8B Instruct 2512) compare to Qwen3 VL 4B Thinking in benchmarks?

Ministral 3 (8B Instruct 2512) scores MATH: 87.6%, Wild Bench: 66.8%, Arena Hard: 50.9%, MM-MT-Bench: 8.1%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking?

Ministral 3 (8B Instruct 2512) supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking?

Key differences include LLM Stats Score (7.7 vs 12.9). See the full comparison above for benchmark-by-benchmark results.

Who makes Ministral 3 (8B Instruct 2512) and Qwen3 VL 4B Thinking?

Ministral 3 (8B Instruct 2512) is developed by Mistral AI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.