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Gemma 4 26B-A4B vs Muse Wonder Full

Muse Wonder Full leads the LLM Stats Score 52.1 to 29.5.

Google · Meta · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 29.5, ranking #13 overall.

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

Choose Gemma 4 26B-A4B

  • 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 agents — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Gemma 4 26B-A4B
Google
Muse Wonder Full
Meta
Core performance indexes
LLM Stats Score
29.5
#142
52.1
#13
Reasoning
29.2
#137
38.4
#71
Agents
12.6
#114
38.5
#8
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.07 / M
— / M
Output price
$0.34 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemma 4 26B-A4B
Muse Wonder Full
Vision
14.6#103
31.7#28
Multimodal
18.6#86
31.8#25
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for Gemma 4 26B-A4B · 16 for Muse Wonder Full

No common benchmarks found

Gemma 4 26B-A4B 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

Context Window

Maximum input and output token capacity

Only Gemma 4 26B-A4B specifies input context (262,144 tokens). Only Gemma 4 26B-A4B specifies output context (262,144 tokens).

Google
Gemma 4 26B-A4B
Input262,144 tokens
Output262,144 tokens
Meta
Muse Wonder Full
Input- tokens
Output- tokens
Sat Oct 17 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 4 26B-A4B and Muse Wonder Full support multimodal inputs.

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

Gemma 4 26B-A4B

Text
Images
Audio
Video

Muse Wonder Full

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 26B-A4B 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.

Gemma 4 26B-A4B

Apache 2.0

Open weights

Muse Wonder Full

Proprietary

Closed source

Release Timeline

When each model was launched

Gemma 4 26B-A4B was released on 2026-04-02, while Muse Wonder Full was released on 2026-10-12.

Muse Wonder Full is 6 months newer than Gemma 4 26B-A4B.

Gemma 4 26B-A4B

Apr 2, 2026

6 months ago

Muse Wonder Full

Oct 12, 2026

5 days ago

6mo newer

Knowledge Cutoff

When training data ends

Gemma 4 26B-A4B has a documented knowledge cutoff of 2025-01-01, while Muse Wonder Full's cutoff date is not specified.

We can confirm Gemma 4 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without Muse Wonder Full's cutoff date.

Gemma 4 26B-A4B

Jan 2025

Muse Wonder Full

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Gemma 4 26B-A4B and Muse Wonder Full side-by-side, then vote on the output you prefer.

Gemma 4 26B-A4B
✓ Preferred
Muse Wonder Full
Open in Playground

FAQ

Common questions about Gemma 4 26B-A4B vs Muse Wonder Full.

Which is better, Gemma 4 26B-A4B or Muse Wonder Full?

Muse Wonder Full leads the LLM Stats Score 52.1 to 29.5. Gemma 4 26B-A4B is made by Google 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 Gemma 4 26B-A4B compare to Muse Wonder Full in benchmarks?

Gemma 4 26B-A4B scores AIME 2026: 88.3%, MMMLU: 86.3%, t2-bench: 85.5%, MMLU-Pro: 82.6%, MathVision: 82.4%. 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 context window sizes for Gemma 4 26B-A4B and Muse Wonder Full?

Gemma 4 26B-A4B supports 262K tokens and Muse Wonder Full supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 4 26B-A4B and Muse Wonder Full?

Key differences include LLM Stats Score (29.5 vs 52.1), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 26B-A4B and Muse Wonder Full?

Gemma 4 26B-A4B is developed by Google and Muse Wonder Full is developed by Meta.

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