{
  "page": "https://opencode.ai/data/meta/muse-wonder-1-0",
  "updatedAt": null,
  "summary": "Muse Wonder costs $4.00 per 1M input tokens and $20.00 per 1M output tokens.",
  "model": {
    "id": "meta/muse-wonder-1.0",
    "name": "Muse Wonder",
    "lab": "meta",
    "labName": "Meta",
    "family": "muse",
    "description": "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.",
    "releaseDate": "2026-10-12",
    "lastUpdated": "2026-10-12",
    "knowledgeCutoff": null,
    "contextTokens": 1048576,
    "outputTokens": 131072,
    "inputModalities": [
      "text",
      "image",
      "video",
      "pdf",
      "audio"
    ],
    "outputModalities": [
      "text"
    ],
    "reasoning": true,
    "toolCall": true,
    "openWeights": false,
    "weights": [],
    "priceUsdPer1M": {
      "input": 4,
      "output": 20,
      "cachedInput": 0.2,
      "cacheWrite": null
    },
    "benchmarks": [
      {
        "name": "Harvey Legal Agent Benchmark",
        "score": 10,
        "metric": "all-pass rate",
        "variant": "max effort; Artificial Analysis LAB-AA",
        "version": "1.1",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "Finance Agent",
        "score": 56.6,
        "metric": "accuracy",
        "variant": "max effort",
        "dataset": "Vals AI private test set",
        "version": "v2",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "HealthBench Professional",
        "score": 60.5,
        "metric": "length-normalized weighted rubric score",
        "variant": "max effort",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "AutomationBench",
        "score": 39.1,
        "metric": "strict pass@1",
        "variant": "max effort; Artificial Analysis AutomationBench-AA",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "GDP.pdf",
        "score": 30.8,
        "metric": "score",
        "variant": "max effort",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "JobBench",
        "score": 70.5,
        "metric": "mean reward",
        "variant": "max effort",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "OSWorld",
        "score": 72.6,
        "metric": "mean partial score",
        "variant": "max effort",
        "version": "2.1",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "OSWorld",
        "score": 34.3,
        "metric": "binary completion rate",
        "variant": "max effort",
        "version": "2.1",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "Terminal-Bench",
        "score": 52,
        "metric": "accuracy",
        "variant": "max effort; Artificial Analysis Terminal-Bench 4.0-AA",
        "version": "4.0",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "DeepSWE",
        "score": 78.8,
        "metric": "pass@1",
        "variant": "max effort",
        "version": "1.1",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "SWE-Marathon",
        "score": 53.1,
        "metric": "pass@1",
        "variant": "max effort",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "ProgramBench",
        "score": 50,
        "metric": "share of rollouts passing at least 95% of tests",
        "harness": "mini-swe-agent",
        "variant": "max effort",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      },
      {
        "name": "Artificial Analysis Intelligence Index",
        "score": 52,
        "metric": "index score",
        "variant": "max effort",
        "version": "4.3",
        "source": "https://research.meta.ai/static/muse-wonder-model-card"
      }
    ]
  },
  "usage": null
}