Cloud baseline

muse-wonder — 0.7638 on Gauntlet 7.2

meta/muse-wonder · scorer sb-7.2

meta/muse-wonder Build1meta/muse-wonder · single agentOct 15, 2026
Overall
0.7638
Excellent
no
Benchmark
Gauntlet 7.2
Model build
21m 1s
Prompt tok
3.4M
Gen tok
60.8k

Tier breakdown

A · structure & runtime1.00
B · behaviour0.98
C · vendor contract0.91
D · finesse0.90

Scoring detail

How this score was built

Per-check scorer output, as posted by the app. Expand a section to inspect its checks.

Earned credit before admission

(0.88 × 0.9052 core + 0.12 × 0.94 gate × 0.90 excellence) × 1.0000 critical = 0.8978

The core (88% of the total) is the weighted mean of the thirteen measured tiers. The last 12% is the excellence slice: it unlocks in proportion to the perfection conditions below (15 of 16 met here), then pays out at the excellence tier's own measured mean. Core 0.7966 + excellence 0.1012.

j_first_use 1.00j_workflow_journey 1.00j_error_state 1.00j_empty_state 1.00console_clean 1.00v_responsive_375 1.00v_dates_readable 1.00t_scene_binding 1.00x_conservation_residual 1.00r_no_row_loss 1.00p_drag_frames 1.00p_idle_flatness 1.00p_stream_apply 1.00p_under_stream 1.00p_api_latency 1.00p_sync_wall 1.00

Earned score 0.898 · Admission ceiling 0.769 · Final score 0.764

Final score is the lower of earned credit and the admission ceiling. Passing admission adds no points.

Visible: passedMatching: passedGood: not metVisual excellence: not metBackend excellence: not met

3D interaction and overview legibility: q_overview_legibility, q_inspector_framing (maximum 0.769)

Event animation and backend recovery: m_committed_event_replay, x_l5_group_atomicity (maximum 0.869)

Run notes and corrections

Native billed summary: USD 3.2491017 lower bound, incomplete (6 generation IDs have no billed record and some counted tokens are unmatched). Source: native OpenRouter generation usage recovery. Requested reasoning: medium; provider-effective effort unmeasured.

Token rates

Measured by the engine itself, one record per completed model call: prefill rate is prompt tokens over time-to-first-token, generation rate is completion tokens over the decode window. Medians per node.

NodeCallsPrompt tokGen tokPrefill tok/sGen tok/s
gemini19725861.742.7
muse613,414,66260,77811105.2317.2
fleet623,415,63460,78310987.0253.2

Graded browser recording

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Watch the full graded browser recording at its original speed: the payment field, structure inspection, committed updates and replay. The check results and screenshots on this page provide the wider evidence. Pause or scrub to inspect a view.

Each tower represents a payment: height encodes its amount, cap color its status, and the collar its currency. The selected detailed tower is expected to animate its collar after a committed backend update or replay. These are the task requirements; the check results show what this app actually achieved.

Ready to play0:00 / —:—
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Drag the timeline to seek. Keyboard: arrow keys move 5 seconds; Home and End jump to the start and end.

Full graded browser recording: payment field, structure inspection, committed updates and replay

Screenshots

Captured from the built application during browser grading. Captions identify the recorded views and checks; these images do not represent repair rounds.

1First captured render
2Latest captured render
3After sync
4Error state
5Mobile · 375px

Run details

Model
meta/muse-wonder
Engine events
0
Repair rounds
0
Started
Oct 15, 2026, 03:41 PM
Finished
Oct 15, 2026, 04:10 PM

How the benchmark is scored