# Kimi K2 (Jul 2025) vs o1-pro

> Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 31.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/kimi-k2-vs-o1-pro
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where Kimi K2 (Jul 2025) leads 37.3 to 29.7.
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $150 / $600 for o1-pro.
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 200K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.

## Snapshot

| | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| Provider | Moonshot AI | OpenAI |
| Noometry Index | 41.2 | 31.5 |
| Rank | 140 | 271 |
| Context | 262K | 200K |
| Input $/M | $0.57 | $150 |
| Output $/M | $2.30 | $600 |
| Weights | Open | Proprietary |

## Coding

- Kimi K2 (Jul 2025): 42.4 (#102)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| LMArena Coding | 1399 | — |
| ALE-Bench | 597.5 | — |

## Agentic & Tool Use

- Kimi K2 (Jul 2025): 32.4 (#64)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |

## Reasoning

- Kimi K2 (Jul 2025): 23.3 (#179)
- o1-pro: 20.4 (#239)

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1384 | — |
| Epoch Capabilities Index | 146.01 | — |
| ForecastBench | 60.2 | — |

## Math

- Kimi K2 (Jul 2025): 42.7 (#83)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| Omni-MATH | 65.4% | — |
| LMArena Math | 1397 | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- Kimi K2 (Jul 2025): 37.3 (#157)
- o1-pro: 29.7 (#234)

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| Humanity's Last Exam | — | 8.1% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
| LMArena Expert | 1365 | — |

## Multilingual

- Kimi K2 (Jul 2025): 49.6 (#130)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| LMArena Non-English | 1372 | — |
| LMArena Chinese | 1415 | — |
| LMArena French | 1379 | — |
| LMArena German | 1387 | — |
| LMArena Japanese | 1349 | — |
| LMArena Korean | 1325 | — |
| LMArena Russian | 1385 | — |
| LMArena Spanish | 1386 | — |

## Instruction Following

- Kimi K2 (Jul 2025): 71.1 (#156)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| IFEval | 85% | — |
| LMArena Instruction Following | 1348 | — |

## Long Context

- Kimi K2 (Jul 2025): 41.2 (#145)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
| LMArena Longer Query | 1353 | — |

## Writing & Preference

- Kimi K2 (Jul 2025): 62.3 (#78)
- o1-pro: —

| Benchmark | Kimi K2 (Jul 2025) | o1-pro |
|---|---|---|
| LMArena Text | 1380 | — |
| LMArena Creative Writing | 1350 | — |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
| LMArena Multi-Turn | 1371 | — |

## FAQ

### Is Kimi K2 (Jul 2025) better than o1-pro?

Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 31.5 on the Noometry Index.

### Which is cheaper, Kimi K2 (Jul 2025) or o1-pro?

Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; o1-pro lists at $150 and $600.

### Which has the bigger context window?

Kimi K2 (Jul 2025) does, with 262K tokens against 200K.

### How many benchmarks do Kimi K2 (Jul 2025) and o1-pro share?

0 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and o1-pro has 3.