Models / Zhipu AI

GLM-5.3-Flash

Zhipu AI · Open Weight

Recent snapshotData snapshot cf-1.3
Cheese Index60.5cf-1.3
Input / output—Price unknown
Measured dimensions7 / 13Evidence
Context window1,048,576tokens · conditions unverified

Decision brief

Start by investigating Multimodal and Reasoning workloads. These are observed strengths in the dataset; validate them on your own tasks.

Coverage counts measured dimensions, not confidence. Benchmark conditions and public source links may be missing. Missing: Instructions, Multilingual, swe, terminal, gpqa, mcp.

View evidence ↓

Measured task dimensions

Coding
48.4
Agent workflows
55.3
Mathematics
60.4
Knowledge
59.2
Instructions
—
Multimodal
84.0
Multilingual
—
Reasoning
80.8
swe
—
terminal
—
gpqa
—
hle
55.3
mcp
—

Normalized dimensions. A dash means unknown, not zero.

Input / output

Price unknown

Listed dataset prices; provider terms and dates need verification. Zero without explicit free-price evidence is treated as unknown.

Cache, batch, tool fees and self-hosting costs: not verified.

Index variability stability

91.9 · 7 days of history

band

This is index variability, not API uptime or reliability.

Before deployment

  • Confirm provider endpoint, license and version.
  • Test your prompts, tool calls and failure recovery.
  • Verify prices and latency with real usage.

Evidence

These are source categories published by the dataset. Original public links, sample sizes and harness details remain incomplete.

Source categoryProvenance typeAs ofOriginal public link
Codingcore / official_json2026-10-14Not published
Agent workflowscore / official_json2026-10-14Not published
Long workflowshorizon / official_json2026-10-14Not published
opscross / official_json2026-10-14Not published
depthcore+cross / official_json2026-10-14Not published
Published index inputs · cf-1.3
Coding40.3
Agent workflows55.3
Long workflows63.4
Overall—

The method includes overall, but this snapshot does not expose that input. The total cannot be fully reproduced from these displayed axes.

Method: median of available axes, with an 8% Ops blend when present. Source scores are displayed without recalculation or imputation.

Method →
Index history
As ofCheese Index
2026-10-0857.8
2026-10-0957.3
2026-10-1058.4
2026-10-1158.7
2026-10-1258.8
2026-10-1359.5
2026-10-1460.5

Only recorded dates are shown. Missing days are not filled.