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Muse Wonder Full vs Qwen2.5-Omni-7B

Muse Wonder Full leads the LLM Stats Score 52.1 to 5.2.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 5.2, ranking #13 overall.

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

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

Choose Qwen2.5-Omni-7B

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

At a glance

The differences that matter most.

Muse Wonder Full
Meta
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
52.1
#13
5.2
#315
Reasoning
38.4
#71
1.4
#328
Coding
41.5
#8
1.1
#249
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Muse Wonder Full
Qwen2.5-Omni-7B
Vision
31.7#28
5.1#165
Multimodal
31.8#25
6.5#144
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for Muse Wonder Full · 45 for Qwen2.5-Omni-7B

No common benchmarks found

Muse Wonder Full and Qwen2.5-Omni-7Bdon'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

Both Muse Wonder Full and Qwen2.5-Omni-7B support multimodal inputs.

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

Muse Wonder Full

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Wonder Full is licensed under a proprietary license, while Qwen2.5-Omni-7B uses Apache 2.0.

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

Muse Wonder Full

Proprietary

Closed source

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Muse Wonder Full was released on 2026-10-12, while Qwen2.5-Omni-7B was released on 2025-03-27.

Muse Wonder Full is 19 months newer than Qwen2.5-Omni-7B.

Muse Wonder Full

Oct 12, 2026

1 days ago

1.5yr newer
Qwen2.5-Omni-7B

Mar 27, 2025

1.5 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 Muse Wonder Full and Qwen2.5-Omni-7B side-by-side, then vote on the output you prefer.

Muse Wonder Full
✓ Preferred
Qwen2.5-Omni-7B
Open in Playground

FAQ

Common questions about Muse Wonder Full vs Qwen2.5-Omni-7B.

Which is better, Muse Wonder Full or Qwen2.5-Omni-7B?

Muse Wonder Full leads the LLM Stats Score 52.1 to 5.2. Muse Wonder Full is made by Meta and Qwen2.5-Omni-7B 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 Muse Wonder Full compare to Qwen2.5-Omni-7B in benchmarks?

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%. Qwen2.5-Omni-7B scores FLEURS: 95.9%, DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%.

What are the main differences between Muse Wonder Full and Qwen2.5-Omni-7B?

Key differences include LLM Stats Score (52.1 vs 5.2), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Muse Wonder Full and Qwen2.5-Omni-7B?

Muse Wonder Full is developed by Meta and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.

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