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GPT-5.6 Luna vs Muse Wonder Full

Muse Wonder Full leads the LLM Stats Score 52.1 to 44.2.

OpenAI · Meta · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 44.2, ranking #13 overall.

In the 4 individual benchmarks reported for both models, Muse Wonder Full wins 4; 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 GPT-5.6 Luna

  • you want predictable pricing at $0.20/M input and $1.20/M output

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 4 of 4 exact shared results
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

GPT-5.6 Luna
OpenAI
Muse Wonder Full
Meta
Core performance indexes
LLM Stats Score
44.2
#45
52.1
#13
Reasoning
43.2
#47
38.4
#71
Coding
34.4
#34
41.5
#8
Agents
30.0
#42
38.5
#8
Cost, coverage & limits
Benchmark wins
0 of 4
4 of 4
Input price
$0.20 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,050,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
GPT-5.6 Luna
Muse Wonder Full
Vision
23.1#66
31.7#28
Multimodal
23.6#64
31.8#25
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

45 reported for GPT-5.6 Luna · 16 for Muse Wonder Full

4 shared

GPT-5.6 Luna outperforms in 0 benchmarks, while Muse Wonder Full is better at 4 benchmarks (Artificial Analysis, DeepSWE 1.1, GDP.pdf, HealthBench Professional).

Muse Wonder Full significantly outperforms across most benchmarks.

Sat Oct 17 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-5.6 Luna specifies input context (1,050,000 tokens). Only GPT-5.6 Luna specifies output context (128,000 tokens).

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 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 GPT-5.6 Luna and Muse Wonder Full support multimodal inputs.

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

GPT-5.6 Luna

Text
Images
Audio
Video

Muse Wonder Full

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-5.6 Luna

Proprietary

Closed source

Muse Wonder Full

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Muse Wonder Full was released on 2026-10-12.

Muse Wonder Full is 3 months newer than GPT-5.6 Luna.

GPT-5.6 Luna

Jul 9, 2026

3 months ago

Muse Wonder Full

Oct 12, 2026

5 days ago

3mo newer

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Muse Wonder Full's cutoff date is not specified.

We can confirm GPT-5.6 Luna's training data extends to 2026-02-16, but cannot make a direct comparison without Muse Wonder Full's cutoff date.

GPT-5.6 Luna

Feb 2026

Muse Wonder Full

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Muse Wonder Full side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Muse Wonder Full
Open in Playground

FAQ

Common questions about GPT-5.6 Luna vs Muse Wonder Full.

Which is better, GPT-5.6 Luna or Muse Wonder Full?

Muse Wonder Full leads the LLM Stats Score 52.1 to 44.2. GPT-5.6 Luna is made by OpenAI 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 GPT-5.6 Luna compare to Muse Wonder Full in benchmarks?

GPT-5.6 Luna scores Connectors: 99.9%, HealthBench Consensus: 95.1%, GPQA: 92.3%, Search and Function-Calling: 89.7%, Capture-the-Flag Challenges (Internal): 85.2%. 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 GPT-5.6 Luna and Muse Wonder Full?

GPT-5.6 Luna supports 1.1M 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 GPT-5.6 Luna and Muse Wonder Full?

Key differences include LLM Stats Score (44.2 vs 52.1). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.6 Luna and Muse Wonder Full?

GPT-5.6 Luna is developed by OpenAI and Muse Wonder Full is developed by Meta.

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