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Magistral Small 2506 vs Muse Wonder Full

Muse Wonder Full leads the LLM Stats Score 52.1 to 10.7.

Mistral AI · Meta · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 10.7, ranking #13 overall.

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

Choose Magistral Small 2506

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

Choose Muse Wonder Full

  • overall performance matters — it scores 52.1 and ranks #13 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

At a glance

The differences that matter most.

Core performance indexes
10.7
#277
52.1
#13
10.9
#275
38.4
#71
5.2
#215
41.5
#8
Cost, coverage & limits
Benchmark wins
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Input price
— / M
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Output price
— / M
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Context window
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Individual benchmarks

4 reported for Magistral Small 2506 · 16 for Muse Wonder Full

No common benchmarks found

Magistral Small 2506 and Muse Wonder Fulldon'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

Input capabilities

Documented input modalities across available providers

Muse Wonder Full supports multimodal inputs, whereas Magistral Small 2506 does not.

Muse Wonder Full can handle both text and other forms of data like images, making it suitable for multimodal applications.

Magistral Small 2506

Text
Images
Audio
Video

Muse Wonder Full

Text
Images
Audio
Video

License

Usage and distribution terms

Magistral Small 2506 is licensed under Apache 2.0, while Muse Wonder Full uses a proprietary license.

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

Magistral Small 2506

Apache 2.0

Open weights

Muse Wonder Full

Proprietary

Closed source

Release Timeline

When each model was launched

Magistral Small 2506 was released on 2025-06-10, while Muse Wonder Full was released on 2026-10-12.

Muse Wonder Full is 16 months newer than Magistral Small 2506.

Magistral Small 2506

Jun 10, 2025

1.3 years ago

Muse Wonder Full

Oct 12, 2026

0 days ago

1.3yr newer

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while Muse Wonder Full'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 Muse Wonder Full's cutoff date.

Magistral Small 2506

Jun 2025

Muse Wonder Full

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Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Magistral Small 2506 and Muse Wonder Full side-by-side, then vote on the output you prefer.

Magistral Small 2506
✓ Preferred
Muse Wonder Full
Open in Playground

FAQ

Common questions about Magistral Small 2506 vs Muse Wonder Full.

Which is better, Magistral Small 2506 or Muse Wonder Full?

Muse Wonder Full leads the LLM Stats Score 52.1 to 10.7. Magistral Small 2506 is made by Mistral AI and Muse Wonder Full is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Magistral Small 2506 compare to Muse Wonder Full in benchmarks?

Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%. Muse Wonder Full scores MemoryBench: 85.5%, DeepSWE 1.1: 79.0%, OSWorld 2.1 (partial): 78.4%, JobBench: 75.3%, HealthBench Professional: 62.3%.

What are the main differences between Magistral Small 2506 and Muse Wonder Full?

Key differences include LLM Stats Score (10.7 vs 52.1), multimodal support (no vs yes), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Magistral Small 2506 and Muse Wonder Full?

Magistral Small 2506 is developed by Mistral AI and Muse Wonder Full is developed by Meta.