# GLM-5.1 vs Kimi K2.7 Code

> GLM-5.1 is the stronger model overall, scoring 47.8 to 43.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-1-vs-kimi-k2-7-code
- Last updated: 2026-10-11
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. GLM-5.1 scores higher in 4 categories and Kimi K2.7 Code in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5.1 leads 48.7 to 42.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 36.8% for GLM-5.1 and 54% for Kimi K2.7 Code.
- Kimi K2.7 Code is cheaper at $0.95 / $4 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- Kimi K2.7 Code accepts more context: 262K tokens versus 200K.

## Snapshot

| | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| Provider | Z.ai (Zhipu) | Moonshot AI |
| Noometry Index | 47.8 | 43.3 |
| Rank | 59 | 94 |
| Context | 200K | 262K |
| Input $/M | $1.40 | $0.95 |
| Output $/M | $4.40 | $4 |
| Weights | Open | Open |

## Coding

- GLM-5.1: 48.7 (#55)
- Kimi K2.7 Code: 42.9 (#95)

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| LMArena WebDev | 1508 | 1473 |
| SciCode | 43.8% | 47.5% |
| WeirdML | 57.1% | 54.1% |
| ALE-Bench | 887.1 | 886.23 |
| SWE-bench Verified | 74.2% | — |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| LMArena Coding | 1485 | — |

## Agentic & Tool Use

- GLM-5.1: 24.9 (#113)
- Kimi K2.7 Code: 24.0 (#122)

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | 40.9% | 37.6% |
| GBAEval | 0% | 0.9% |
| Vending-Bench 2 | 5,634 | 5,083 |
| ExploitBench | 18.1% | — |

## Reasoning

- GLM-5.1: 39.1 (#60)
- Kimi K2.7 Code: 39.0 (#61)

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| SimpleBench | 55.1% | 57.9% |
| CritPt | 4.6% | 10% |
| Chess Puzzles | 19% | 21% |
| Epoch Capabilities Index | 149.84 | 149.97 |
| NYT Connections (extended) | 77.7% | — |
| Thematic Generalization | 69.8% | — |
| LMArena Hard Prompts | 1472 | — |
| Surface Evolver Bench | — | 48.8% |

## Math

- GLM-5.1: 49.7 (#60)
- Kimi K2.7 Code: 52.9 (#48)

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | 36.8% | 54% |
| OTIS Mock AIME 2024-2025 | 93.3% | 95.6% |
| FrontierMath Tier 4 | — | 12.2% |
| MathArena Final-Answer Competitions | 67.1% | — |
| ProofBench | 22.2% | — |
| LMArena Math | 1473 | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |

## Knowledge

- GLM-5.1: 54.9 (#50)
- Kimi K2.7 Code: 53.5 (#57)

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 89.9% | 87.9% |
| SimpleQA Verified | 34% | 36.5% |
| LMArena Expert | 1476 | — |

## Multilingual

- GLM-5.1: 55.0 (#36)
- Kimi K2.7 Code: —

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1447 | — |
| LMArena Chinese | 1515 | — |
| LMArena French | 1474 | — |
| LMArena German | 1465 | — |
| LMArena Japanese | 1434 | — |
| LMArena Korean | 1418 | — |
| LMArena Russian | 1454 | — |
| LMArena Spanish | 1469 | — |

## Instruction Following

- GLM-5.1: 76.3 (#42)
- Kimi K2.7 Code: —

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1451 | — |

## Long Context

- GLM-5.1: 44.9 (#53)
- Kimi K2.7 Code: —

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1466 | — |

## Writing & Preference

- GLM-5.1: 66.9 (#31)
- Kimi K2.7 Code: —

| Benchmark | GLM-5.1 | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1453 | — |
| EQ-Bench Creative Writing | 1592 | — |
| LMArena Multi-Turn | 1472 | — |

## FAQ

### Is GLM-5.1 better than Kimi K2.7 Code?

GLM-5.1 is the stronger model overall, scoring 47.8 to 43.3 on the Noometry Index.

### Which is cheaper, GLM-5.1 or Kimi K2.7 Code?

Kimi K2.7 Code is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.

### Is GLM-5.1 or Kimi K2.7 Code better for coding?

GLM-5.1 scores higher on coding benchmarks: 48.7 versus 42.9 in the Noometry coding category.

### Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 200K.

### How many benchmarks do GLM-5.1 and Kimi K2.7 Code share?

15 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Kimi K2.7 Code has 19.