Rank #4
Model result · rank #4
GLM‑5.2
OpenRouter · z-ai/glm-5.2 · maximum reasoning · Full + SWE + Hard measured. Public result card with the model’s overall score, lane measurements, runtime/cost telemetry, and ranking formula.
Full rank #6
SWE rank #1
Hard rank #6
100.0% reliability
All-around publication view
Score83.68
Formulamean(Full, SWE, Hard Intelligence)
BasisOpenRouter · z-ai/glm-5.2 · maximum reasoning · Full + SWE + Hard measured
The overall score averages the measured major lanes while keeping each source measurement visible.
Full / Agentic benchmark
Final86.87
Capability99.37
Agentic96.24
Pass rate100.0%
Prompts43
This lane captures instruction following, structured behavior, tool discipline, and general agentic reliability.
Software engineering MVP
SWE score89.58
Focused final72.41
Capability89.58
Daily driver65.89
Prompts24
This lane is closer to implementation usefulness: source handling, architecture cleanliness, and deliverable quality.
Hard Intelligence diagnostic
Hard score74.58
Active inquiry17.50
Online adaptation98.13
Self-repair82.71
Authority integrity100.00
Hard Intelligence measures active inquiry, online adaptation, evidence-driven self-repair, and authority/salience integrity.
Runtime economics
Total cost$2.768
Cost / scored item$0.037
Seconds / timed item91.19s
Runtime coverage100.0%
Recorded tokens / item22.4k
Token coverage100.0%
Cost, time, and token basis are normalized telemetry. They explain tradeoffs; they do not overwrite the capability score yet.
Interpretation
Why this result lands here.
The result is best read as a balanced benchmark entry: one overall score plus the lane measurements that produced it. Hard Intelligence score is 74.58 and contributes to the overall score alongside Full/Agentic and SWE. GLM‑5.2 used OpenRouter maximum reasoning across the public benchmark suites. SWE score reflects all prompt outcomes from the public software-engineering suite.