GLM-5.2vsStep 3.7 Flash
Across 3 shared benchmarks, GLM-5.2 leads overall: GLM-5.2 wins 3, Step 3.7 Flash wins 0, with 0 ties and an average score difference of +11.60.
GLM-5.2
智谱AI · 2026-06-13 · Reasoning model
Step 3.7 Flash
StepFunAI · 2026-05-29 · Reasoning model
GLM-5.23 wins(100%)(0%)0 winsStep 3.7 Flash
Benchmark scores
Grouped by capability, sorted by largest gap within each. 3 shared benchmarks.
AI Agent - Tool Usage
GLM-5.2 1/1| Benchmark | GLM-5.2 | Step 3.7 Flash | Diff |
|---|---|---|---|
| Terminal-Bench 2.1 | 8117 / 44Thinking High (With Tools) | 59.5037 / 44Thinking (With Tools) | +21.50 |
Coding and Software Engineer
GLM-5.2 1/1| Benchmark | GLM-5.2 | Step 3.7 Flash | Diff |
|---|---|---|---|
| SWE-Bench Pro - Public | 62.109 / 57Thinking (With Tools) | 56.3025 / 57Thinking (With Tools) | +5.80 |
General Knowledge
GLM-5.2 1/1| Benchmark | GLM-5.2 | Step 3.7 Flash | Diff |
|---|---|---|---|
| HLE | 54.7015 / 181Thinking (With Tools) | 47.2039 / 181Thinking (With Tools) | +7.50 |
Specs
| Field | GLM-5.2 | Step 3.7 Flash |
|---|---|---|
| Publisher | 智谱AI | StepFunAI |
| Release date | 2026-06-13 | 2026-05-29 |
| Model type | Reasoning model | Reasoning model |
| Architecture | MoE | MoE |
| Parameters | 753.33B | 198B |
| Context length | 1M | 256K |
| Max output | 128K | Not available |
API pricing
Prices use DataLearner records when available; missing fields are not inferred.
| Item | GLM-5.2 | Step 3.7 Flash |
|---|---|---|
| Text input | $1.4 / 1M tokens | ¥1.35 / 1M tokens |
| Text output | $4.4 / 1M tokens | ¥8.1 / 1M tokens |
| Cache read | $0.26 / 1M tokens | ¥0.27 / 1M tokens |
Summary
- GLM-5.2leads in:AI Agent - Tool Usage (1/1), Coding and Software Engineer (1/1), General Knowledge (1/1)
On average across the 3 shared benchmarks, GLM-5.2 scores 11.60 higher.
Largest single-benchmark gap: Terminal-Bench 2.1 — GLM-5.2 81 vs Step 3.7 Flash 59.50 (+21.50).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.