Muse Wonder
Meta
- Released
- October 12, 2026
- Data date
- October 15, 2026
- Price
- Input · Output / 1M tokens
- Input
- Text, Image, Audio, Video
- Output
- Text
Muse Wonder is Meta’s model for complex agentic tasks and long-running software work. It accepts text, image, video, audio, and PDF inputs and returns text.
Its Model API context window is 1,048,576 tokens, and Meta labels it a preview. Meta does not publish a numeric output limit or knowledge cutoff.
Specifications and access
| Specification | Value and source |
|---|---|
| Weights | ProprietarySource |
| Notes | Proprietary model for complex agentic tasks; Meta does not publish a parameter count.Source |
| Access | Model API (Standard mode) and Muse CodeSource |
| Model API model ID | muse-wonder-1.0Source |
| Inputs | Text, image, video, audio, and PDF filesSource |
| Outputs | TextSource |
| Context window | 1,048,576 tokensSource |
Page 1 of 17
Published benchmarks
Agent tasks
AutomationBench-AA (strict pass@1)
Overall
Business workflows in a simulated application environment. Every end-state assertion must pass; max reasoning. Do not merge with other AutomationBench-AA metrics. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-automationbench-aa
- Metric
- strict pass@1; every end-state assertion passed
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- Business workflows in a simulated application environment. Every end-state assertion must pass; max reasoning. Do not merge with other AutomationBench-AA metrics.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-486cc1fd0e30. Source payload hash: 486cc1fd0e30df79c113cefceff8209ee698f3d3c0c502cd5e6a1062f9789755. Parser version: curated-v1. Imported at: 2026-10-15
OSWorld V2.1 (binary completion)
Overall
108 Ubuntu desktop workflows. Full task completion without partial credit, max reasoning. No binary Opus 5.5 score is published. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-osworld-binary
- Metric
- strict binary task completion
- Scale
- 0-100
- Participants
- 4
- Methodology and context
- 108 Ubuntu desktop workflows. Full task completion without partial credit, max reasoning. No binary Opus 5.5 score is published.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-ce462a4d193b. Source payload hash: ce462a4d193bf92a3d779abd513ea6d6a8903cc9eac7f0738f1a7bbb0934408e. Parser version: curated-v1. Imported at: 2026-10-15
OSWorld V2.1 (partial reward)
Overall
108 Ubuntu desktop workflows. Partial reward, max reasoning. Meta attributes the Opus 5.5 score to Anthropic. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-osworld-partial
- Metric
- mean per-task partial reward
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- 108 Ubuntu desktop workflows. Partial reward, max reasoning. Meta attributes the Opus 5.5 score to Anthropic.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-42896ddbba2e. Source payload hash: 42896ddbba2ee26c0f376f3aee7501de06452d1925efc121d8ec29df56f46216. Parser version: curated-v1. Imported at: 2026-10-15
Coding
DeepSWE
Overall
113 tasks across 91 repositories and five languages. Max reasoning. Meta attributes these results to Datacurve; the Muse scores could not be found on its public leaderboard at retrieval. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-deepswe
- Metric
- pass@1
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- 113 tasks across 91 repositories and five languages. Max reasoning. Meta attributes these results to Datacurve; the Muse scores could not be found on its public leaderboard at retrieval.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-29ee4352e632. Source payload hash: 29ee4352e6328b759b9977f09884c2fe89318fcd8099d1a8f6e518422b0e4073. Parser version: curated-v1. Imported at: 2026-10-15
ProgramBench
Overall
Reconstruct programs from a specification. Common mini-swe-agent, clean environment without internet after setup. Share of rollouts passing at least 95% of tests, max reasoning. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-programbench
- Metric
- rollouts passing at least 95% of tests
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- Reconstruct programs from a specification. Common mini-swe-agent, clean environment without internet after setup. Share of rollouts passing at least 95% of tests, max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Harness: mini-swe-agent. Tool policy: no internet after setup. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-48b87e1dd0cc. Source payload hash: 48b87e1dd0cce991eb594d97c5b46b5241df64260ac56d001b5824671fb34242. Parser version: curated-v1. Imported at: 2026-10-15
Vals Finance Agent V2
Overall
Financial research using filings and market data. Private test set, max reasoning. Vals results republished by Meta. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-finance-agent-v2
- Metric
- private test accuracy
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- Financial research using filings and market data. Private test set, max reasoning. Vals results republished by Meta.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-8dc60fff8edf. Source payload hash: 8dc60fff8edfa998d54e5c541cbb3279a1385fd6375774edb6d66cf8334bf9bc. Parser version: curated-v1. Imported at: 2026-10-15
Productivity
GDP.pdf
Overall
Professional work grounded in supplied PDFs. Max reasoning. Meta names Surge as the original source. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
higher is betterAs of October 15, 2026Scale: 0 points - 34.2 points
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-gdp-pdf
- Metric
- published GDP.pdf score
- Scale
- No upper bound is documented. The chart spans the recorded values and zero.
- Participants
- 5
- Methodology and context
- Professional work grounded in supplied PDFs. Max reasoning. Meta names Surge as the original source.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-38e2b67d4ac7. Source payload hash: 38e2b67d4ac7014ed57688efe7f13cb4944d00c7f49112086f148b0153121188. Parser version: curated-v1. Imported at: 2026-10-15
JobBench
Overall
65 professional tasks across 35 occupations. Mean task-specific reward, max reasoning. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
higher is betterAs of October 15, 2026Scale: 0 points - 75.4 points
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-jobbench
- Metric
- mean task reward
- Scale
- No upper bound is documented. The chart spans the recorded values and zero.
- Participants
- 5
- Methodology and context
- 65 professional tasks across 35 occupations. Mean task-specific reward, max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-b39cb0e087b8. Source payload hash: b39cb0e087b8d78df5e1d8ad024a0c0943bc6b187587e2f9fe07adff5f590fa6. Parser version: curated-v1. Imported at: 2026-10-15
Harvey LAB-AA
Overall
Legal deliverables must pass every criterion including hallucination checks. Max reasoning. Meta attributes the original evaluation to Artificial Analysis. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
higher is betterAs of October 15, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-harvey-lab-aa
- Metric
- all criteria passed with hallucination checks
- Scale
- 0-100
- Participants
- 5
- Methodology and context
- Legal deliverables must pass every criterion including hallucination checks. Max reasoning. Meta attributes the original evaluation to Artificial Analysis.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-7af6eb66695f. Source payload hash: 7af6eb66695f7b16244288df651bbb8b27386a2d20e1c3efc95b5e3d30b515a9. Parser version: curated-v1. Imported at: 2026-10-15
HealthBench Pro
Overall
525 health questions without tools; physician rubrics graded by GPT-5.4. Max reasoning. Meta attributes the Claude scores to Anthropic system cards. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
higher is betterAs of October 15, 2026Scale: 0 points - 65.6 points
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-healthbench-pro
- Metric
- length-normalized weighted rubric score
- Scale
- No upper bound is documented. The chart spans the recorded values and zero.
- Participants
- 5
- Methodology and context
- 525 health questions without tools; physician rubrics graded by GPT-5.4. Max reasoning. Meta attributes the Claude scores to Anthropic system cards.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-83c3853a8435. Source payload hash: 83c3853a843525f2cbab4a36f05fb0db45778331c5451ac8e6a91225f620322e. Parser version: curated-v1. Imported at: 2026-10-15
MemoryBench
Overall
Internal Meta evaluation with 64K-100K-token conversations, distractors and conflicting or updated turns. Max reasoning. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
higher is betterAs of October 15, 2026Scale: 0 points - 85.6 points
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-memorybench
- Metric
- LLM-judge weighted rubric score
- Scale
- No upper bound is documented. The chart spans the recorded values and zero.
- Participants
- 5
- Methodology and context
- Internal Meta evaluation with 64K-100K-token conversations, distractors and conflicting or updated turns. Max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-11b7ecf71c89. Source payload hash: 11b7ecf71c89f805dfde139cde8e8d6533c8bc0af7b4250d630f88e4c2604704. Parser version: curated-v1. Imported at: 2026-10-15
Personal Superintelligence Index
Overall
Meta internal composite of seven personal and professional work evaluations. Max reasoning. Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Note (Muse Wonder): Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Note: Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
higher is betterAs of October 15, 2026Scale: 0 points - 59.1 points
Methodology and context
- Comparison cohort
- meta-wonder-launch-2026-10-12-psi
- Metric
- Meta internal composite score
- Scale
- No upper bound is documented. The chart spans the recorded values and zero.
- Participants
- 5
- Methodology and context
- Meta internal composite of seven personal and professional work evaluations. Max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-a806ce9d874b. Source payload hash: a806ce9d874b89e5b56dce8b64dadb02bc6d4672622d6b8f3435cc67776f1942. Parser version: curated-v1. Imported at: 2026-10-15
Recorded measurement details
AutomationBench-AA (strict pass@1): Overall (Show measurement, test conditions, and source)
- Source value
- 39.1
- Score
- 39.1
- Metric
- strict pass@1; every end-state assertion passed
- Unit
- %
- Benchmark version
- Meta Wonder scorecard; version unspecified
- Category
- agentic
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-automationbench-aa
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Business workflows in a simulated application environment. Every end-state assertion must pass; max reasoning. Do not merge with other AutomationBench-AA metrics.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-486cc1fd0e30. Source payload hash: 486cc1fd0e30df79c113cefceff8209ee698f3d3c0c502cd5e6a1062f9789755. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Business workflows in a simulated application environment. Every end-state assertion must pass; max reasoning. Do not merge with other AutomationBench-AA metrics.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
DeepSWE: Overall (Show measurement, test conditions, and source)
- Source value
- 78.8
- Score
- 78.8
- Metric
- pass@1
- Unit
- %
- Benchmark version
- v1.1
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-deepswe
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- 113 tasks across 91 repositories and five languages. Max reasoning. Meta attributes these results to Datacurve; the Muse scores could not be found on its public leaderboard at retrieval.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-29ee4352e632. Source payload hash: 29ee4352e6328b759b9977f09884c2fe89318fcd8099d1a8f6e518422b0e4073. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- 113 tasks across 91 repositories and five languages. Max reasoning. Meta attributes these results to Datacurve; the Muse scores could not be found on its public leaderboard at retrieval.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Vals Finance Agent V2: Overall (Show measurement, test conditions, and source)
- Source value
- 56.6
- Score
- 56.6
- Metric
- private test accuracy
- Unit
- %
- Benchmark version
- V2
- Category
- finance
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-finance-agent-v2
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Financial research using filings and market data. Private test set, max reasoning. Vals results republished by Meta.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-8dc60fff8edf. Source payload hash: 8dc60fff8edfa998d54e5c541cbb3279a1385fd6375774edb6d66cf8334bf9bc. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Financial research using filings and market data. Private test set, max reasoning. Vals results republished by Meta.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
GDP.pdf: Overall (Show measurement, test conditions, and source)
- Source value
- 30.8
- Score
- 30.8
- Metric
- published GDP.pdf score
- Unit
- points
- Benchmark version
- Meta Wonder scorecard; version unspecified
- Category
- productivity
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-gdp-pdf
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Professional work grounded in supplied PDFs. Max reasoning. Meta names Surge as the original source.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-38e2b67d4ac7. Source payload hash: 38e2b67d4ac7014ed57688efe7f13cb4944d00c7f49112086f148b0153121188. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Professional work grounded in supplied PDFs. Max reasoning. Meta names Surge as the original source.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
Harvey LAB-AA: Overall (Show measurement, test conditions, and source)
- Source value
- 10
- Score
- 10
- Metric
- all criteria passed with hallucination checks
- Unit
- %
- Benchmark version
- 1.1
- Category
- legal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-harvey-lab-aa
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Legal deliverables must pass every criterion including hallucination checks. Max reasoning. Meta attributes the original evaluation to Artificial Analysis.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-7af6eb66695f. Source payload hash: 7af6eb66695f7b16244288df651bbb8b27386a2d20e1c3efc95b5e3d30b515a9. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Legal deliverables must pass every criterion including hallucination checks. Max reasoning. Meta attributes the original evaluation to Artificial Analysis.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
HealthBench Pro: Overall (Show measurement, test conditions, and source)
- Source value
- 60.5
- Score
- 60.5
- Metric
- length-normalized weighted rubric score
- Unit
- points
- Benchmark version
- Meta Wonder scorecard; version unspecified
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-healthbench-pro
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- 525 health questions without tools; physician rubrics graded by GPT-5.4. Max reasoning. Meta attributes the Claude scores to Anthropic system cards.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-83c3853a8435. Source payload hash: 83c3853a843525f2cbab4a36f05fb0db45778331c5451ac8e6a91225f620322e. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- 525 health questions without tools; physician rubrics graded by GPT-5.4. Max reasoning. Meta attributes the Claude scores to Anthropic system cards.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
JobBench: Overall (Show measurement, test conditions, and source)
- Source value
- 70.5
- Score
- 70.5
- Metric
- mean task reward
- Unit
- points
- Benchmark version
- Meta Wonder scorecard; version unspecified
- Category
- productivity
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-jobbench
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- 65 professional tasks across 35 occupations. Mean task-specific reward, max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-b39cb0e087b8. Source payload hash: b39cb0e087b8d78df5e1d8ad024a0c0943bc6b187587e2f9fe07adff5f590fa6. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- 65 professional tasks across 35 occupations. Mean task-specific reward, max reasoning.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
MemoryBench: Overall (Show measurement, test conditions, and source)
- Source value
- 85.6
- Score
- 85.6
- Metric
- LLM-judge weighted rubric score
- Unit
- points
- Benchmark version
- Meta internal Wonder evaluation
- Category
- knowledge
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-memorybench
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Internal Meta evaluation with 64K-100K-token conversations, distractors and conflicting or updated turns. Max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-11b7ecf71c89. Source payload hash: 11b7ecf71c89f805dfde139cde8e8d6533c8bc0af7b4250d630f88e4c2604704. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Internal Meta evaluation with 64K-100K-token conversations, distractors and conflicting or updated turns. Max reasoning.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
OSWorld V2.1 (binary completion): Overall (Show measurement, test conditions, and source)
- Source value
- 34.3
- Score
- 34.3
- Metric
- strict binary task completion
- Unit
- %
- Benchmark version
- V2.1
- Category
- agentic
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-osworld-binary
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- 108 Ubuntu desktop workflows. Full task completion without partial credit, max reasoning. No binary Opus 5.5 score is published.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-ce462a4d193b. Source payload hash: ce462a4d193bf92a3d779abd513ea6d6a8903cc9eac7f0738f1a7bbb0934408e. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- 108 Ubuntu desktop workflows. Full task completion without partial credit, max reasoning. No binary Opus 5.5 score is published.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
OSWorld V2.1 (partial reward): Overall (Show measurement, test conditions, and source)
- Source value
- 72.6
- Score
- 72.6
- Metric
- mean per-task partial reward
- Unit
- %
- Benchmark version
- V2.1
- Category
- agentic
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-osworld-partial
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- 108 Ubuntu desktop workflows. Partial reward, max reasoning. Meta attributes the Opus 5.5 score to Anthropic.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-42896ddbba2e. Source payload hash: 42896ddbba2ee26c0f376f3aee7501de06452d1925efc121d8ec29df56f46216. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- 108 Ubuntu desktop workflows. Partial reward, max reasoning. Meta attributes the Opus 5.5 score to Anthropic.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
ProgramBench: Overall (Show measurement, test conditions, and source)
- Source value
- 50
- Score
- 50
- Metric
- rollouts passing at least 95% of tests
- Unit
- %
- Benchmark version
- Meta Wonder scorecard; version unspecified
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-programbench
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Reconstruct programs from a specification. Common mini-swe-agent, clean environment without internet after setup. Share of rollouts passing at least 95% of tests, max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Harness: mini-swe-agent. Tool policy: no internet after setup. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-48b87e1dd0cc. Source payload hash: 48b87e1dd0cce991eb594d97c5b46b5241df64260ac56d001b5824671fb34242. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Reconstruct programs from a specification. Common mini-swe-agent, clean environment without internet after setup. Share of rollouts passing at least 95% of tests, max reasoning.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort.
Personal Superintelligence Index: Overall (Show measurement, test conditions, and source)
- Source value
- 54.3
- Score
- 54.3
- Metric
- Meta internal composite score
- Unit
- points
- Benchmark version
- Meta Wonder launch scorecard
- Category
- aggregate
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- meta-wonder-launch-2026-10-12-psi
- Source type
- vendor-reported
- Evaluator
- Meta
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Meta internal composite of seven personal and professional work evaluations. Max reasoning.. Source model ID: curated/meta-muse-wonder-1.0. Source model name: Muse Wonder. Provider reported by source: Meta. Evaluator: Meta. Dataset type: public. Reasoning effort: max. Source ID: meta. Evidence capture ID: curated-meta-2026-10-15-a806ce9d874b. Source payload hash: a806ce9d874b89e5b56dce8b64dadb02bc6d4672622d6b8f3435cc67776f1942. Parser version: curated-v1. Imported at: 2026-10-15
- Comparison methodology
- Meta internal composite of seven personal and professional work evaluations. Max reasoning.
- Context
- Comparison table published by Meta. Depending on the benchmark, Meta uses internal runs, provider reports or third-party results and selects the highest available validated score. This is not a uniformly independently measured cohort. The source specifies neither a denominator nor a normalized scale. This is the published raw score, not a percentage.
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