# GLM-4.7-Flash vs Kimi K2.7 Code

> Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 12× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-kimi-k2-7-code
- Last updated: 2026-10-11
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and Kimi K2.7 Code in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 20.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 95.6% for Kimi K2.7 Code.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 200K.

## Snapshot

| | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| Provider | Z.ai (Zhipu) | Moonshot AI |
| Noometry Index | 38.8 | 43.3 |
| Rank | 180 | 94 |
| Context | 200K | 262K |
| Input $/M | $0.06 | $0.95 |
| Output $/M | $0.40 | $4 |
| Weights | Open | Open |

## Coding

- GLM-4.7-Flash: 40.6 (#135)
- Kimi K2.7 Code: 42.9 (#95)

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| LMArena WebDev | — | 1473 |
| SciCode | — | 47.5% |
| WeirdML | — | 54.1% |
| LMArena Coding | 1383 | — |
| ALE-Bench | — | 886.23 |

## Agentic & Tool Use

- GLM-4.7-Flash: —
- Kimi K2.7 Code: 24.0 (#122)

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |

## Reasoning

- GLM-4.7-Flash: 20.9 (#229)
- Kimi K2.7 Code: 39.0 (#61)

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| Chess Puzzles | 0% | 21% |
| SimpleBench | — | 57.9% |
| CritPt | — | 10% |
| LMArena Hard Prompts | 1356 | — |
| Surface Evolver Bench | — | 48.8% |
| Epoch Capabilities Index | — | 149.97 |

## Math

- GLM-4.7-Flash: 36.1 (#173)
- Kimi K2.7 Code: 52.9 (#48)

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 95.6% |
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| LMArena Math | 1355 | — |

## Knowledge

- GLM-4.7-Flash: 35.5 (#184)
- Kimi K2.7 Code: 53.5 (#57)

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 60.5% | 87.9% |
| SimpleQA Verified | — | 36.5% |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |

## Multilingual

- GLM-4.7-Flash: 46.5 (#158)
- Kimi K2.7 Code: —

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1330 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |

## Instruction Following

- GLM-4.7-Flash: 70.1 (#167)
- Kimi K2.7 Code: —

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1327 | — |

## Long Context

- GLM-4.7-Flash: 40.9 (#148)
- Kimi K2.7 Code: —

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1345 | — |

## Writing & Preference

- GLM-4.7-Flash: 47.4 (#210)
- Kimi K2.7 Code: —

| Benchmark | GLM-4.7-Flash | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1297 | — |
| EQ-Bench Creative Writing | 1125 | — |
| LMArena Multi-Turn | 1342 | — |

## FAQ

### Is GLM-4.7-Flash better than Kimi K2.7 Code?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 12× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7-Flash or Kimi K2.7 Code?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is GLM-4.7-Flash or Kimi K2.7 Code better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 40.6 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-4.7-Flash and Kimi K2.7 Code share?

3 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Kimi K2.7 Code has 19.