# Kimi K2 (Jul 2025) vs Qwen3.8 Max

> Qwen3.8 Max is the stronger model overall, scoring 56.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 3.0× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/kimi-k2-vs-qwen3-8-max
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 0 categories and Qwen3.8 Max in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.8 Max leads 54.4 to 23.3.
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- Qwen3.8 Max accepts more context: 1M tokens versus 262K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.

## Snapshot

| | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 41.2 | 56.8 |
| Rank | 140 | 22 |
| Context | 262K | 1M |
| Input $/M | $0.57 | $2 |
| Output $/M | $2.30 | $6 |
| Weights | Open | Proprietary |

## Coding

- Kimi K2 (Jul 2025): 42.4 (#102)
- Qwen3.8 Max: 53.5 (#29)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Coding | 1399 | 1502 |
| DeepSWE | — | 57.5% |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| LMArena WebDev | — | 1674 |
| FrontierSWE | — | 17.8% |
| SciCode | — | 53.2% |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| ALE-Bench | 597.5 | — |

## Agentic & Tool Use

- Kimi K2 (Jul 2025): 32.4 (#64)
- Qwen3.8 Max: 45.4 (#14)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| APEX-Agents | — | 63.3% |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
| METR Time Horizons | 59.2% | — |

## Reasoning

- Kimi K2 (Jul 2025): 23.3 (#179)
- Qwen3.8 Max: 54.4 (#26)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1496 |
| Epoch Capabilities Index | 146.01 | 156.41 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| NYT Connections (extended) | — | 88.3% |
| CritPt | — | 20% |
| Chess Puzzles | — | 40% |
| Mystery Game Puzzles | — | 38% |
| DTBench | — | 92% |
| LMCA | — | 46.2% |
| ForecastBench | 60.2 | — |

## Math

- Kimi K2 (Jul 2025): 42.7 (#83)
- Qwen3.8 Max: 73.2 (#20)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Math | 1397 | 1499 |
| FrontierMath (Tiers 1-3) | — | 74.7% |
| FrontierMath Tier 4 | — | 46.3% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 58% |
| 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 Max: 61.7 (#27)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Expert | 1365 | 1507 |
| GPQA Diamond | — | 92.7% |
| SimpleQA Verified | — | 47.3% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |

## Multimodal

- Kimi K2 (Jul 2025): —
- Qwen3.8 Max: 37.2 (#75)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | — | 1314 |
| Furniture Assembly | — | 20% |

## Multilingual

- Kimi K2 (Jul 2025): 49.6 (#130)
- Qwen3.8 Max: 56.7 (#18)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1372 | 1472 |
| LMArena Chinese | 1415 | 1538 |
| LMArena French | 1379 | 1503 |
| LMArena German | 1387 | 1483 |
| LMArena Japanese | 1349 | 1467 |
| LMArena Korean | 1325 | 1461 |
| LMArena Russian | 1385 | 1481 |
| LMArena Spanish | 1386 | 1492 |

## Instruction Following

- Kimi K2 (Jul 2025): 71.1 (#156)
- Qwen3.8 Max: 77.6 (#17)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1348 | 1479 |
| IFEval | 85% | — |

## Long Context

- Kimi K2 (Jul 2025): 41.2 (#145)
- Qwen3.8 Max: 45.6 (#31)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1353 | 1489 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |

## Writing & Preference

- Kimi K2 (Jul 2025): 62.3 (#78)
- Qwen3.8 Max: 67.1 (#30)

| Benchmark | Kimi K2 (Jul 2025) | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1380 | 1483 |
| LMArena Creative Writing | 1350 | 1479 |
| LMArena Multi-Turn | 1371 | 1489 |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |

## FAQ

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

Qwen3.8 Max is the stronger model overall, scoring 56.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 3.0× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.

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

Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; Qwen3.8 Max lists at $2 and $6.

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

Qwen3.8 Max scores higher on coding benchmarks: 53.5 versus 42.4 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.8 Max does, with 1M tokens against 262K.

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

18 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Qwen3.8 Max has 39.