GLM-5.2vsGLM-5
Across 4 shared benchmarks, GLM-5.2 leads overall: GLM-5.2 wins 4, GLM-5 wins 0, with 0 ties and an average score difference of +6.12.
GLM-5.24 wins(100%)(0%)0 winsGLM-5
Benchmark scores
Grouped by capability, sorted by largest gap within each. 4 shared benchmarks.
General Knowledge
GLM-5.2 2/2| Benchmark | GLM-5.2 | GLM-5 | Diff |
|---|---|---|---|
| GPQA Diamond | 91.2015 / 179Thinking (No Tools) | 8644 / 179Thinking (No Tools) | +5.20 |
| HLE | 54.708 / 159Thinking (With Tools) | 50.4019 / 159 | +4.30 |
Math and Reasoning
GLM-5.2 2/2| Benchmark | GLM-5.2 | GLM-5 | Diff |
|---|---|---|---|
| IMO-AnswerBench | 911 / 20Thinking (No Tools) | 82.5014 / 20Thinking (No Tools) | +8.50 |
| AIME 2026 | 99.201 / 15Thinking (No Tools) | 92.708 / 15Thinking (No Tools) | +6.50 |
Specs
| Field | GLM-5.2 | GLM-5 |
|---|---|---|
| Publisher | 智谱AI | 智谱AI |
| Release date | 2026-06-13 | 2026-02-11 |
| Model type | Reasoning model | Chat model |
| Architecture | MoE | MoE |
| Parameters | 753.33B | 744B |
| Context length | 1M | 200K |
| Max output | 128K | 128K |
API pricing
Prices use DataLearner records when available; missing fields are not inferred.
| Item | GLM-5.2 | GLM-5 |
|---|---|---|
| Text input | $1.4 / 1M tokens | $1 / 1M tokens |
| Text output | $4.4 / 1M tokens | $3.2 / 1M tokens |
| Cache read | $0.26 / 1M tokens | Not public |
| Cache write | Not public | $0.2 / 1M tokens |
Summary
- GLM-5.2leads in:General Knowledge (2/2), Math and Reasoning (2/2)
On average across the 4 shared benchmarks, GLM-5.2 scores 6.12 higher.
Largest single-benchmark gap: IMO-AnswerBench — GLM-5.2 91 vs GLM-5 82.50 (+8.50).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.