Cloud baseline

glm-5.3-flashx — 0.6303 on Gauntlet 7.2

z-ai/glm-5.3-flashx · scorer sb-7.2

z-ai/glm-5.3-flashx, single model via OpenRouterz-ai/glm-5.3-flashx · single agentOct 4, 2026
Overall
0.6303
Excellent
no
Benchmark
Gauntlet 7.2
Model build
49m 53s
Prompt tok
25.1M
Gen tok
226.9k

Tier breakdown

A · structure & runtime1.00
B · behaviour1.00
C · vendor contract0.95
D · finesse0.93

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 × 0.8614 core + 0.12 × 0.99 gate × 1.00 excellence) × 0.9429 critical = 0.8268

Critical defects compound a multiplier on the whole score (pre-severity 0.8769):

j_workflow_journey 0.86 → ×0.94

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 0.7580 + excellence 0.1189.

j_first_use 1.00j_workflow_journey 0.86j_error_state 1.00j_empty_state 1.00console_clean 0.00v_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 0.827 · Admission ceiling 0.639 · Final score 0.630

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

Visible: passedMatching: not metGood: not metVisual excellence: not metBackend excellence: passed

Tower structure, currency mapping and scene truth: s_tower_geometry, t_height_pixels, t_vs7dbg_truth (maximum 0.639)

3D interaction and overview legibility: t_camera_math, t_labels_culling, t_brush_link, t_stream_diff, q_overview_legibility, q_inspector_framing (maximum 0.699)

Event animation and backend recovery: m_committed_event_replay (maximum 0.899)

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
gemini19725909.3138.9
z14125,073,026226,89147422.5140.6
fleet14225,073,998226,89647403.3140.6

Graded browser recording

Loading duration…

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 / —:—
Open recording file

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

Graded browser recording re-encoded to 766x478 at 25 fps to fit 4 MiB, same 124.6 s; graded original sha256 f5e7002fb1d234496a589bd661f0d2118e565750596ab63fced2e2040dcdaf71

Screenshots

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

1Initial app view
2Error state
3Payment workflow
4First captured render
5Latest captured render

Run details

Model
z-ai/glm-5.3-flashx
Engine events
0
Repair rounds
0
Started
Oct 3, 2026, 02:57 AM
Finished
Oct 3, 2026, 03:55 AM
Re-scored
Oct 4, 2026, 05:27 AM (same build, corrected scorer)

How the benchmark is scored