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Muse Spark 1.3 native video via OpenRouter — twelve attempts, MP4 re-encode with exact frames

Observed outcomes from sealed evaluation records. Failed attempts and non-model errors remain visible.

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Outcomes by AI exam

AI examAI agentPassed / attemptsTechnical errorsWithheldInvalid
Robot catch temporal and tracking annotationmeta/muse-spark-1.34/10 + 2 lane errors200

Campaign coverage

12 of 12 planned attempts recorded. All planned attempts are recorded.

Video · meta/muse-spark-1.3

74.86/100 · Grader quality score

12 attempts; 4 passed; 6 failed. Quality measures answer accuracy; passing also requires the exam’s declared minimums.

Input: native video with supplied exact-frame images; provider-side processing is not independently observed; video re-encoded to MP4 H.264 CRF 18 because the provider accepts MP4 only; frame count, frame rate and timing preserved; exact inspection frames delivered as lossless PNG from the original file.

Measured quality · scale 0–1
MeasureScore
Classification accuracy1.00
Event matching (F1)0.90
Segment matching (F1)1.00
Box matching (F1)0.70
Track consistency on matched boxes1.00

Interpretation and limits

  • Repeated attempts on these fixed tasks only; not a broad capability score.
  • All outcomes are retained; lane errors, withheld and invalid attempts are not model failures.
  • Quality is the existing grader measurement, separate from the pass gate.
  • Video delivery is stated per model from recorded receipts; native files and sampled frames are distinct. Provider-side sampling is not independently observed.
  • Provider token usage is recorded where available. Monetary usage is not an invoice, and requested seeds do not establish deterministic replay.
  • Private references, submissions, exact geometry, frame timestamps and raw sessions are withheld.
Technical evidence and detailed report

Detailed technical report (PDF) · Results and record digests (JSON) · Attempt counts and commitments (JSON)

These optional files provide the full audit detail behind this result.

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