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Meta: Muse Wonder

Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.

Source-linked muse Closed weights Released 2026-10-12
API record Report
InputT
OutputT
Input price$4/M
Output price$20/M
Context1.04858M
Max output131.072K
Providers11
Inference availability

Providers

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

Report a price
Providers offering Muse Wonder
ProviderProvider model IDContextMax outputInputOutputCache readCapabilitiesDocs
LLM Gateway meta/muse-wonder-1.0 1.04858M 1.04858M $4 $20 $0.2 ReasoningToolsJSON Docs ↗
OpenRouter meta/muse-wonder 1.04858M 943.718K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
Meta muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
Cloudflare AI Gateway meta/muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningTools Docs ↗
Vercel AI Gateway meta/muse-wonder-1.0 1.04858M 1.04858M $4 $20 $0.2 ReasoningToolsJSON Docs ↗
DevPass (LLM Gateway) muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
Requesty muse-wonder-1.0 1.04858M 943.718K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
CommandCode meta/muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
OpenCode muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
Eden AI meta/muse-wonder-1.0 1.04858M 131.072K $4 $20 $0.2 ReasoningToolsJSON Docs ↗
Venice AI muse-wonder 1.04858M 131.072K $5 $25 $0.25 ReasoningToolsJSON Docs ↗

Capability badges appear only where the provider catalog explicitly lists support. A blank cell means the source is silent, not that the feature is absent.

Listed rates

Price across providers

Input price per million tokens as published by each provider. Bars are drawn from listed rates only — no traffic weighting, since the catalog observes no requests.

Lowest input $4/M

Across 11 priced providers

Median input $4/M

Midpoint of listed rates

Highest input $5/M

1.2× the lowest listed rate

Output range $20 – $25

Per million output tokens

LLM Gateway $4/M
OpenRouter $4/M
Meta $4/M
Cloudflare AI Gateway $4/M
Vercel AI Gateway $4/M
DevPass (LLM Gateway) $4/M
Requesty $4/M
CommandCode $4/M
OpenCode $4/M
Eden AI $4/M
Venice AI $5/M
Cost calculator

Estimate a workload

$0.00
Excludes taxes, non-token charges, and tiered discounts.

10 providers list the identical $4 input rate, so price alone will not separate them — compare context limits, max output, and capabilities above.

Specification

Capabilities

Recorded from the source catalog and provider listings.

✓ Reasoning Yes
✓ Tool calling Yes
✓ Structured output Yes
✓ 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-1.0
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 #3 of 3
Artificial Analysis Intelligence Index — 4.3 index score · 2026-10-12 Source ↗
52.0 2 models scored — too few for a distribution
AutomationBench strict pass@1 · 2026-10-12 Source ↗
39.1 2 models scored — too few for a distribution
DeepSWE — 1.1 pass@1 · 2026-10-12 Source ↗
78.8 2 models scored — too few for a distribution
GDP.pdf score · 2026-10-12 Source ↗
30.8 2 models scored — too few for a distribution
Harvey Legal Agent Benchmark — 1.1 all-pass rate · 2026-10-12 Source ↗
10.0 2 models scored — too few for a distribution
HealthBench Professional length-normalized weighted rubric score · 2026-10-12 Source ↗
60.5 2 models scored — too few for a distribution
JobBench mean reward · 2026-10-12 Source ↗
70.5 2 models scored — too few for a distribution
OSWorld — 2.1 binary completion rate · 2026-10-12 Source ↗
34.3 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 ↗
50.0 2 models scored — too few for a distribution
SWE-Marathon pass@1 · 2026-10-12 Source ↗
53.1 2 models scored — too few for a distribution
Terminal-Bench — 4.0 accuracy · 2026-10-12 Source ↗
52.0 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.

Provenance

Sources & verification

Every figure on this page traces back to one of these records.

Methodology
Public API

Use this record

Fetch the complete source-linked model record. No key, no account, no rate-limited tier.

API documentation
Endpoint
GET https://modelbench.lol/api/v1/models/meta/muse-wonder-1.0
curl
curl "https://modelbench.lol/api/v1/models/meta/muse-wonder-1.0"
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?

Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal. It is published by Meta and catalogued here from Models.dev.

How much does Muse Wonder cost?

Listed input pricing starts at $4 per million tokens from LLM Gateway, rising to $5 across 11 listed providers.

What is the context length of Muse Wonder?

Muse Wonder accepts up to 1.04858M tokens of context and returns up to 131.072K output tokens.

Does Muse Wonder support tool calling and structured output?

Provider catalogs list support for tool calling, structured output, reasoning, and image input.

Which providers serve Muse Wonder?

11 providers list this model: LLM Gateway, OpenRouter, Meta, Cloudflare AI Gateway, Vercel AI Gateway, DevPass (LLM Gateway) and 5 more.

Are the weights for Muse Wonder open?

No. This model is served through hosted APIs only.

When was Muse Wonder released?

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

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