GLM-5.2vsKimi K2.7 Code
Across 3 shared benchmarks, GLM-5.2 leads overall: GLM-5.2 wins 3, Kimi K2.7 Code wins 0, with 0 ties and an average score difference of +10.44.
GLM-5.2
智谱AI · 2026-06-13 · Reasoning model
Kimi K2.7 Code
Moonshot AI · 2026-06-12 · Coding model
GLM-5.23 wins(100%)(0%)0 winsKimi K2.7 Code
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 | Kimi K2.7 Code | Diff |
|---|---|---|---|
| TerminalBench 2.1 | 814 / 14Thinking High (With Tools) | 67.0410 / 14Thinking (With Tools) | +13.96 |
Coding and Software Engineer
GLM-5.2 1/1| Benchmark | GLM-5.2 | Kimi K2.7 Code | Diff |
|---|---|---|---|
| DeepSWE | 445 / 9Deep Thinking (With Tools) | 317 / 9Normal (With Tools) | +13 |
General Knowledge
GLM-5.2 1/1| Benchmark | GLM-5.2 | Kimi K2.7 Code | Diff |
|---|---|---|---|
| LiveBench | 76.249 / 115Normal (No Tools) | 71.8930 / 115Normal (No Tools) | +4.35 |
Specs
| Field | GLM-5.2 | Kimi K2.7 Code |
|---|---|---|
| Publisher | 智谱AI | Moonshot AI |
| Release date | 2026-06-13 | 2026-06-12 |
| Model type | Reasoning model | Coding model |
| Architecture | MoE | MoE |
| Parameters | 753.33B | 1T |
| 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 | Kimi K2.7 Code |
|---|---|---|
| Text input | $1.4 / 1M tokens | $0.95 / 1M tokens |
| Text output | $4.4 / 1M tokens | $4 / 1M tokens |
| Cache read | $0.26 / 1M tokens | $0.19 / 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 10.44 higher.
Largest single-benchmark gap: TerminalBench 2.1 — GLM-5.2 81 vs Kimi K2.7 Code 67.04 (+13.96).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.