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Muse Wonder Full vs Qwen3.8-27B

Muse Wonder Full leads the LLM Stats Score 52.1 to 44.6.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 44.6, ranking #13 overall.

In the 1 individual benchmarks reported for both models, Muse Wonder Full 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 Muse Wonder Full

  • overall performance matters — it scores 52.1 and ranks #13 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen3.8-27B

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

At a glance

The differences that matter most.

Core performance indexes
52.1
#13
44.6
#43
38.4
#71
44.3
#40
41.5
#8
30.2
#54
38.5
#8
29.5
#45
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.40 / M
Output price
— / M
$3.00 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Muse Wonder Full
Qwen3.8-27B
31.7#28
32.9#21
31.8#25
36.6#9
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for Muse Wonder Full · 26 for Qwen3.8-27B

1 shared

Muse Wonder Full outperforms in 1 benchmarks (DeepSWE 1.1), while Qwen3.8-27B is better at 0 benchmarks.

Muse Wonder Full significantly outperforms across most benchmarks.

Wed Oct 14 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Qwen3.8-27B specifies input context (262,144 tokens). Only Qwen3.8-27B specifies output context (262,144 tokens).

Meta
Muse Wonder Full
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input262,144 tokens
Output262,144 tokens
Wed Oct 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Muse Wonder Full and Qwen3.8-27B support multimodal inputs.

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

Muse Wonder Full

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Wonder Full is licensed under a proprietary license, while Qwen3.8-27B 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

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Muse Wonder Full was released on 2026-10-12, while Qwen3.8-27B was released on 2026-08-14.

Muse Wonder Full is 2 months newer than Qwen3.8-27B.

Muse Wonder Full

Oct 12, 2026

2 days ago

1mo newer
Qwen3.8-27B

Aug 14, 2026

2 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?

Judge for yourself.

Run your own prompts against Muse Wonder Full and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Muse Wonder Full
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Muse Wonder Full vs Qwen3.8-27B.

Which is better, Muse Wonder Full or Qwen3.8-27B?

Muse Wonder Full leads the LLM Stats Score 52.1 to 44.6. Muse Wonder Full is made by Meta and Qwen3.8-27B 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 Qwen3.8-27B 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%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for Muse Wonder Full and Qwen3.8-27B?

Muse Wonder Full supports an unknown number of tokens and Qwen3.8-27B 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 Muse Wonder Full and Qwen3.8-27B?

Key differences include LLM Stats Score (52.1 vs 44.6), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Muse Wonder Full and Qwen3.8-27B?

Muse Wonder Full is developed by Meta and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.