Muse Wonder and Muse Wonder Full released
Meta · Model release
Source confirmed
Data as of October 12, 2026 · How the score is built
CurrentProprietaryReasoning
Muse Wonder
Decision readingMuse Wonder scores 70.4 out of 100 and ranks #16 of 220. This profile shows 6 source-displayable benchmark rows; its strongest eligible category is Coding at #10. API pricing is $4 input and $20 output per million tokens, with cached input at $0.2.
Released Oct 12, 2026 — see all recent releases
Muse Wonder 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
70.4/100
field median 49.6#16 of 220 ranked models
Public
#16of 220
Verified —
Price
$4input / $20 output
input median $0.95cached $0.20 · blended $12
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 #10. Particularly well-suited for software development and code generation tasks.
Validate before choosing
6 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
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 #10 of 148Percentile 94thWeight 20%3 benchmarksVerified | 69.8 | 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 #12 of 180Percentile 94thWeight 12%1 benchmarkVerified | 74.0 | 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 668 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 category percentile values
- AgenticNot eligible
- Coding94th percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge94th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- AgenticNot ranked
- Coding#10/148
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#12/180
- 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 | Score78.8% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | Gap0.2 behind | Weight15% ref. weight | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score50.0% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap43 behind | WeightDisplay only | Provider exact |
| sweMarathon | Score53.1% | Versus best verified row Best verified: Step 5 Preview · 72.7% | Gap19.6 behind | WeightDisplay only | Provider exact |
Agentic2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| JobBench | Score70.5% | Versus best verified row Best verified: Muse Wonder Full · 75.3% | Gap4.8 behind | Weight5% ref. weight | Provider exact |
| Finance Agent v2 | Score56.6% | Versus best verified row Best verified: Gemini 4 Argon · 65.4% | Gap8.8 behind | WeightDisplay only | Provider exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HealthBench Professional | Score60.5% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.2% | Gap8.7 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 6 rowsWhat it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
Current modelExplore all models
Muse Wonder · 70.4 score · $12 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Lineage
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.
Base entry
Muse Wonder Full · 73.8Radar
Full release historyMuse Wonder release history
Radar confirmed these at the source. Use Muse Wonder 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
- muse-wonder-1.0Meta: 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 in preview through Meta Model API as muse-wonder-1.0 and through Muse Code.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.20 per million cached input tokensMeta: 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 ranks #16 of 220 on the public leaderboard with a score of 70.44/100. It does not yet have enough sourced coverage for a verified position.
Muse Wonder 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 in preview through Meta Model API as muse-wonder-1.0 and through Muse Code.
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 sits in the Muse Wonder family with Muse Wonder Full. 6 of 668 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #10, while its lowest eligible position is Knowledge at #12. particularly well-suited for software development and code generation tasks.
Last updated October 12, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Muse Wonder perform overall in AI benchmarks?
Muse Wonder ranks #16 out of 220 models on the public BenchAlign leaderboard, with a score of 70.44/100. 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 good for knowledge and understanding?
Muse Wonder ranks #12 out of 180 eligible models for knowledge and understanding, with a public category score of 74/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Muse Wonder good for coding and programming?
Muse Wonder ranks #10 out of 148 eligible models for coding and programming, with a public category score of 69.8/100. 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 good for agentic tool use and computer tasks?
Muse Wonder 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?
Muse Wonder belongs to the Muse Wonder family. Related tracked variants include Muse Wonder Full. 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 have full benchmark coverage on BenchLM?
No. Muse Wonder currently has 21 source-displayable rows across 668 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?
Muse Wonder 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.