# Kimi K2.7 Code vs Qwen3.5 397B-A17B

> Qwen3.5 397B-A17B is the stronger model overall, scoring 45.7 to 43.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/kimi-k2-7-code-vs-qwen3-5-397b-a17b
- Last updated: 2026-10-10
- Shared benchmarks: 7

## Summary

- They share 7 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Qwen3.5 397B-A17B in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Qwen3.5 397B-A17B leads 33.2 to 23.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 54% for Kimi K2.7 Code and 31.2% for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.

## Snapshot

| | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 43.0 | 45.7 |
| Rank | 90 | 60 |
| Context | 262K | 262K |
| Input $/M | $0.95 | $0.60 |
| Output $/M | $4 | $3.60 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.4 (#92)
- Qwen3.5 397B-A17B: 41.7 (#108)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena WebDev | 1473 | 1400 |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| SciCode | 47.5% | — |
| WeirdML | 54.1% | — |
| LMArena Coding | — | 1464 |
| ALE-Bench | 886.23 | — |

## Agentic & Tool Use

- Kimi K2.7 Code: 23.9 (#115)
- Qwen3.5 397B-A17B: 33.2 (#51)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | 37.6% | 24.9% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 38.2 (#56)
- Qwen3.5 397B-A17B: 33.6 (#62)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| Chess Puzzles | 21% | 13% |
| Epoch Capabilities Index | 150.01 | 146.64 |
| SimpleBench | 57.9% | — |
| Kagi LLM Benchmark | — | 73.7% |
| NYT Connections (extended) | — | 58.9% |
| CritPt | 10% | — |
| Thematic Generalization | — | 65.1% |
| LMArena Hard Prompts | — | 1448 |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 87.5% |
| LMCA | — | 37.9% |
| Surface Evolver Bench | 48.8% | — |

## Math

- Kimi K2.7 Code: 52.6 (#39)
- Qwen3.5 397B-A17B: 44.9 (#64)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 54% | 31.2% |
| OTIS Mock AIME 2024-2025 | 95.6% | 88.9% |
| FrontierMath Tier 4 | 12.2% | — |
| LMArena Math | — | 1455 |

## Knowledge

- Kimi K2.7 Code: 53.6 (#51)
- Qwen3.5 397B-A17B: 53.3 (#53)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | 87.9% | 86.4% |
| SimpleQA Verified | 36.5% | — |
| LMArena Expert | — | 1461 |

## Multimodal

- Kimi K2.7 Code: —
- Qwen3.5 397B-A17B: 40.0 (#42)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | — | 1262 |

## Multilingual

- Kimi K2.7 Code: —
- Qwen3.5 397B-A17B: 54.0 (#56)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | — | 1431 |
| LMArena Chinese | — | 1501 |
| LMArena French | — | 1461 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1427 |
| LMArena Korean | — | 1382 |
| LMArena Russian | — | 1429 |
| LMArena Spanish | — | 1443 |

## Instruction Following

- Kimi K2.7 Code: —
- Qwen3.5 397B-A17B: 75.2 (#73)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | — | 1424 |

## Long Context

- Kimi K2.7 Code: —
- Qwen3.5 397B-A17B: 44.1 (#71)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | — | 1442 |

## Writing & Preference

- Kimi K2.7 Code: —
- Qwen3.5 397B-A17B: 62.5 (#74)

| Benchmark | Kimi K2.7 Code | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | — | 1438 |
| LMArena Creative Writing | — | 1401 |
| EQ-Bench Creative Writing | — | 1478 |
| LMArena Multi-Turn | — | 1447 |

## FAQ

### Is Kimi K2.7 Code better than Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is the stronger model overall, scoring 45.7 to 43.0 on the Noometry Index.

### Which is cheaper, Kimi K2.7 Code or Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is Kimi K2.7 Code or Qwen3.5 397B-A17B better for coding?

They score almost the same on coding (42.4 vs 41.7); test both on your own repository before choosing.

### Which has the bigger context window?

Both accept 262K tokens.

### How many benchmarks do Kimi K2.7 Code and Qwen3.5 397B-A17B share?

7 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Qwen3.5 397B-A17B has 36.