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Meta: Muse Wonder Full

Muse Wonder Full is the most capable model in Meta's Muse Wonder series, built for long-running professional agents and ultra-long-horizon software engineering. It shares Muse Wonder's Active Memory and Active Focus capabilities and generally scores higher on Meta's agentic and coding evaluations.

Source-linked muse Closed weights Released 2026-10-12
API record Report
InputT
OutputT
Input priceNot listed
Output priceNot listed
Context1.05M
Max outputNot documented
Providers0
Inference availability

Providers

Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.

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Specification

Capabilities

Recorded from the source catalog and provider listings.

? Reasoning Unknown
? Tool calling Unknown
? Structured output Unknown
✓ Attachments Yes
✓ Vision input Yes
× Open weights No
Creator
Meta
Model family
muse
Knowledge cutoff
Not documented
License
Not documented
Release date
2026-10-12
Model ID
meta/muse-wonder-full
Published evaluations

Benchmarks

Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.

Benchmark registry
Finance Agent — v2 accuracy · 2026-10-12 Source ↗
Finance Agent #1 of 3
Artificial Analysis Intelligence Index — 4.3 index score · 2026-10-12 Source ↗
56.0 2 models scored — too few for a distribution
AutomationBench strict pass@1 · 2026-10-12 Source ↗
45.4 2 models scored — too few for a distribution
DeepSWE — 1.1 pass@1 · 2026-10-12 Source ↗
79.0 2 models scored — too few for a distribution
GDP.pdf score · 2026-10-12 Source ↗
33.2 2 models scored — too few for a distribution
Harvey Legal Agent Benchmark — 1.1 all-pass rate · 2026-10-12 Source ↗
13.1 2 models scored — too few for a distribution
HealthBench Professional length-normalized weighted rubric score · 2026-10-12 Source ↗
62.3 2 models scored — too few for a distribution
JobBench mean reward · 2026-10-12 Source ↗
75.3 2 models scored — too few for a distribution
OSWorld — 2.1 binary completion rate · 2026-10-12 Source ↗
39.4 2 models scored — too few for a distribution
ProgramBench share of rollouts passing at least 95% of tests · mini-swe-agent · 2026-10-12 Source ↗
59.0 2 models scored — too few for a distribution
SWE-Marathon pass@1 · 2026-10-12 Source ↗
57.5 2 models scored — too few for a distribution
Terminal-Bench — 4.0 accuracy · 2026-10-12 Source ↗
57.1 2 models scored — too few for a distribution

Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.

Catalog activity

Change log

Field-level changes detected between successful source imports.

Full change log
No changes recorded

This record has not changed within the retained import history.

Public API

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API documentation
Endpoint
GET https://modelbench.lol/api/v1/models/meta/muse-wonder-full
curl
curl "https://modelbench.lol/api/v1/models/meta/muse-wonder-full"
Common questions

Frequently asked questions

Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.

What is Muse Wonder Full?

Muse Wonder Full is the most capable model in Meta's Muse Wonder series, built for long-running professional agents and ultra-long-horizon software engineering. It shares Muse Wonder's Active Memory and Active Focus capabilities and generally scores higher on Meta's agentic and coding evaluations. It is published by Meta and catalogued here from Models.dev.

What is the context length of Muse Wonder Full?

Muse Wonder Full accepts up to 1.05M tokens of context.

Does Muse Wonder Full support tool calling and structured output?

Provider catalogs list support for image input.

Are the weights for Muse Wonder Full open?

No. This model is served through hosted APIs only.

When was Muse Wonder Full released?

The catalog records a release date of 2026-10-12, last verified Oct 24, 2026.

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