# Kimi K2 (Jul 2025) vs Qwen3.8 27B

> Qwen3.8 27B is the stronger model overall, scoring 46.0 to 41.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/kimi-k2-vs-qwen3-8-27b
- Last updated: 2026-10-12
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 1 category and Qwen3.8 27B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 23.3.
- Qwen3.8 27B is cheaper at $0.04 / $2.30 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).

## Snapshot

| | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 41.2 | 46.0 |
| Rank | 140 | 68 |
| Context | 262K | 262K |
| Input $/M | $0.57 | $0.04 |
| Output $/M | $2.30 | $2.30 |
| Weights | Open | Open |

## Coding

- Kimi K2 (Jul 2025): 42.4 (#102)
- Qwen3.8 27B: 50.5 (#44)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Coding | 1399 | 1482 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| LMArena WebDev | — | 1593 |
| SciCode | — | 46.6% |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| ALE-Bench | 597.5 | — |

## Agentic & Tool Use

- Kimi K2 (Jul 2025): 32.4 (#64)
- Qwen3.8 27B: 32.9 (#57)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| APEX-Agents | — | 47.5% |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |

## Reasoning

- Kimi K2 (Jul 2025): 23.3 (#179)
- Qwen3.8 27B: 41.0 (#54)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1460 |
| Epoch Capabilities Index | 146.01 | 149.38 |
| ARC-AGI-2 | — | 42.4% |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| NYT Connections (extended) | — | 54.5% |
| ARC-AGI-1 | — | 87.5% |
| CritPt | — | 5.4% |
| DTBench | — | 88% |
| LMCA | — | 41.4% |
| Surface Evolver Bench | — | 45% |
| ForecastBench | 60.2 | — |

## Math

- Kimi K2 (Jul 2025): 42.7 (#83)
- Qwen3.8 27B: 37.1 (#161)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Math | 1397 | 1456 |
| ProofBench | — | 16% |
| Omni-MATH | 65.4% | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- Kimi K2 (Jul 2025): 37.3 (#157)
- Qwen3.8 27B: 41.6 (#109)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | 1365 | 1482 |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |

## Multimodal

- Kimi K2 (Jul 2025): —
- Qwen3.8 27B: 41.3 (#37)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | — | 1271 |

## Multilingual

- Kimi K2 (Jul 2025): 49.6 (#130)
- Qwen3.8 27B: 53.7 (#60)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | 1372 | 1430 |
| LMArena Chinese | 1415 | 1504 |
| LMArena French | 1379 | 1465 |
| LMArena German | 1387 | 1438 |
| LMArena Japanese | 1349 | 1384 |
| LMArena Korean | 1325 | 1393 |
| LMArena Russian | 1385 | 1415 |
| LMArena Spanish | 1386 | 1448 |

## Instruction Following

- Kimi K2 (Jul 2025): 71.1 (#156)
- Qwen3.8 27B: 75.8 (#53)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | 1348 | 1439 |
| IFEval | 85% | — |

## Long Context

- Kimi K2 (Jul 2025): 41.2 (#145)
- Qwen3.8 27B: 44.3 (#70)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | 1353 | 1450 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |

## Writing & Preference

- Kimi K2 (Jul 2025): 62.3 (#78)
- Qwen3.8 27B: 65.8 (#43)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 27B |
|---|---|---|
| LMArena Text | 1380 | 1441 |
| LMArena Creative Writing | 1350 | 1384 |
| EQ-Bench Creative Writing | 1666 | 1671 |
| LMArena Multi-Turn | 1371 | 1441 |
| Short-Story Creative Writing | 85.6% | — |
| WildBench | 86.2% | — |

## FAQ

### Is Kimi K2 (Jul 2025) better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 41.2 on the Noometry Index.

### Which is cheaper, Kimi K2 (Jul 2025) or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.04 per million input tokens and $2.30 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.

### Is Kimi K2 (Jul 2025) or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 42.4 in the Noometry coding category.

### Which has the bigger context window?

Both accept 262K tokens.

### How many benchmarks do Kimi K2 (Jul 2025) and Qwen3.8 27B share?

19 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3.8 27B has 31.