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Magistral Small 2506 vs Qwen3 VL 4B Thinking

Both models are evenly matched across the benchmarks.

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

Which is better?

Magistral Small 2506 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025). Both models are evenly matched across the benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Magistral Small 2506

  • you are already invested in the Mistral AI ecosystem

Choose Qwen3 VL 4B Thinking

  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

Benchmark wins
1 of 2
1 of 2
Input price
— / M
$0.10 / M
Output price
— / M
$1.00 / M
Context window
262,144
Released
Jun 2025
Sep 2025
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Magistral Small 2506 outperforms in 1 benchmarks (GPQA), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).

Both models are evenly matched across the benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

20.0B diff

Magistral Small 2506 has 20.0B more parameters than Qwen3 VL 4B Thinking, making it 500.0% larger.

Mistral AI
Magistral Small 2506
24.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
24.0B
Magistral Small 2506
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
Magistral Small 2506
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas Magistral Small 2506 does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Magistral Small 2506

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.

Magistral Small 2506

Apache 2.0

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Magistral Small 2506 was released on 2025-06-10, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 3 months newer than Magistral Small 2506.

Magistral Small 2506

Jun 10, 2025

1.2 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

11 months ago

3mo newer

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while Qwen3 VL 4B Thinking's cutoff date is not specified.

We can confirm Magistral Small 2506's training data extends to 2025-06-01, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.

Magistral Small 2506

Jun 2025

Qwen3 VL 4B Thinking

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Magistral Small 2506 and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

Magistral Small 2506
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground

FAQ

Common questions about Magistral Small 2506 vs Qwen3 VL 4B Thinking.

Which is better, Magistral Small 2506 or Qwen3 VL 4B Thinking?

Both models are evenly matched across the benchmarks. Magistral Small 2506 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 benchmark scores, pricing, and capabilities above.

How does Magistral Small 2506 compare to Qwen3 VL 4B Thinking in benchmarks?

Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%. 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 Magistral Small 2506 and Qwen3 VL 4B Thinking?

Magistral Small 2506 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 Magistral Small 2506 and Qwen3 VL 4B Thinking?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes Magistral Small 2506 and Qwen3 VL 4B Thinking?

Magistral Small 2506 is developed by Mistral AI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.