Muse Wonder and Muse Wonder Full released
Meta · Model release
Source confirmed
Data as of October 13, 2026 · How the score is built
CurrentProprietaryReasoning
Muse Wonder Full
Decision readingMuse Wonder Full scores 74.1 out of 100 and ranks #11 of 220. This profile shows 6 source-displayable benchmark rows; its strongest eligible category is Coding at #5. No comparable first-party API price is published in the catalog.
Released Oct 12, 2026 — see all recent releases
Muse Wonder Full will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
74.1/100
field median 49.9#11 of 220 ranked models
Public
#11of 220
Verified —
Price
API rate not published
input median $0.78No comparable first-party hosted token rate
Speed
Not measured
field median 90 tok/sTime to first token not measured
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Coding ranks #5. Particularly well-suited for software development and code generation tasks.
Validate before choosing
6 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 6 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| CodingRank #5 of 148Percentile 97thWeight 20%3 benchmarksVerified | 73.8 | 3 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank #10 of 180Percentile 95thWeight 12%1 benchmarkVerified | 77.7 | 1 benchmark | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
6 of 670 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic2/2 verified
- Coding3/3 verified
- ReasoningNot measured
- MultimodalNot measured
- Knowledge1/1 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Verified sourceProvisionalNot measured
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Muse Wonder Full category percentile values
- AgenticNot eligible
- Coding97th percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge95th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- AgenticNot ranked
- Coding#5/148
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#10/180
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Top decileTop quartileMid-fieldNot eligible
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| DeepSWE | Score79.0% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | GapBest verified | Weight15% ref. weight | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score59.0% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap34 behind | WeightDisplay only | Provider exact |
| sweMarathon | Score57.5% | Versus best verified row Best verified: Step 5 Preview · 72.7% | Gap15.2 behind | WeightDisplay only | Provider exact |
Agentic2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| JobBench | Score75.3% | Versus best verified row Best verified: Muse Wonder Full · 75.3% | GapBest verified | Weight5% ref. weight | Provider exact |
| Finance Agent v2 | Score59.1% | Versus best verified row Best verified: Gemini 4 Argon · 65.4% | Gap6.3 behind | WeightDisplay only | Provider exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HealthBench Professional | Score62.3% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.2% | Gap6.9 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 6 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Radar
Full release historyMuse Wonder Full release history
Radar confirmed these at the source. Use Muse Wonder Full in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedMeta: Muse Wonder models and pricing
- Context window
- 1MMeta: Muse Wonder models and pricing
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Available through Muse Code on the Power Usage and Maximum Usage subscription plans. Meta does not publish a separate API token price for Muse Wonder Full.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordMeta: Muse Wonder models and pricing
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Muse Wonder Full ranks #11 of 220 on the public leaderboard with a score of 74.13/100. It does not yet have enough sourced coverage for a verified position.
Muse Wonder Full is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available through Muse Code on the Power Usage and Maximum Usage subscription plans. Meta does not publish a separate API token price for Muse Wonder Full.
Meta released this model on October 12, 2026. The launch scorecard uses max reasoning effort, except Wonder Full on SWE-Marathon uses xhigh. Scores retain their reported evaluation source and harness. OSWorld V2.1, Meta's internal Personal Superintelligence Index, and MemoryBench remain outside the shared benchmark rows; OSWorld V2.1 is not the stored OSWorld 2.0 protocol.
Muse Wonder Full sits in the Muse Wonder family with Muse Wonder. 6 of 670 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #5, while its lowest eligible position is Knowledge at #10. particularly well-suited for software development and code generation tasks.
Last updated October 13, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Muse Wonder Full perform overall in AI benchmarks?
Muse Wonder Full ranks #11 out of 220 models on the public BenchAlign leaderboard, with a score of 74.13/100. Its evidence status is Estimated, and this profile shows 6 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Muse Wonder Full good for knowledge and understanding?
Muse Wonder Full ranks #10 out of 180 eligible models for knowledge and understanding, with a public category score of 77.7/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Muse Wonder Full good for coding and programming?
Muse Wonder Full ranks #5 out of 148 eligible models for coding and programming, with a public category score of 73.8/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Muse Wonder Full good for agentic tool use and computer tasks?
Muse Wonder Full has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Which sibling models are related to Muse Wonder Full?
Muse Wonder Full belongs to the Muse Wonder family. Related tracked variants include Muse Wonder. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does Muse Wonder Full have full benchmark coverage on BenchLM?
No. Muse Wonder Full currently has 21 source-displayable rows across 670 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Muse Wonder Full?
Muse Wonder Full has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.