# Gemini 3.7 Flash vs Kimi K2 (Jul 2025)

> Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 41.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-3-7-flash-vs-kimi-k2
- Last updated: 2026-10-11
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 9 categories and Kimi K2 (Jul 2025) in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.7 Flash leads 70.0 to 23.3.
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.7 Flash.
- Gemini 3.7 Flash accepts more context: 1.05M tokens versus 262K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| Provider | Google | Moonshot AI |
| Noometry Index | 59.8 | 41.2 |
| Rank | 14 | 140 |
| Context | 1.05M | 262K |
| Input $/M | $0.75 | $0.57 |
| Output $/M | $3.75 | $2.30 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3.7 Flash: 56.2 (#22)
- Kimi K2 (Jul 2025): 42.4 (#102)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Coding | 1497 | 1399 |
| ALE-Bench | 904.3 | 597.5 |
| DeepSWE | 65.5% | — |
| FrontierCode | 43.6% | — |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| LMArena WebDev | 1592 | — |
| FrontierSWE | 20.3% | — |
| SciCode | 59.8% | — |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |

## Agentic & Tool Use

- Gemini 3.7 Flash: 42.1 (#19)
- Kimi K2 (Jul 2025): 32.4 (#64)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| APEX-Agents | 67.8% | — |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| Remote Labor Index | 5% | — |
| GDP.pdf | 23.8% | — |
| METR Time Horizons | — | 59.2% |

## Reasoning

- Gemini 3.7 Flash: 70.0 (#15)
- Kimi K2 (Jul 2025): 23.3 (#179)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Hard Prompts | 1494 | 1384 |
| Epoch Capabilities Index | 157.27 | 146.01 |
| ARC-AGI-2 | 84.6% | — |
| SimpleBench | — | 26.3% |
| Kagi LLM Benchmark | — | 64.4% |
| NYT Connections (extended) | 94% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | 47% | — |
| Mystery Game Puzzles | 37% | — |
| DTBench | 96.8% | — |
| LMCA | 50.4% | — |
| ForecastBench | — | 60.2 |

## Math

- Gemini 3.7 Flash: 69.6 (#23)
- Kimi K2 (Jul 2025): 42.7 (#83)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1507 | 1397 |
| FrontierMath (Tiers 1-3) | 71.6% | — |
| FrontierMath Tier 4 | 36.6% | — |
| OTIS Mock AIME 2024-2025 | 97.2% | — |
| ProofBench | 58% | — |
| Omni-MATH | — | 65.4% |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- Gemini 3.7 Flash: 69.7 (#5)
- Kimi K2 (Jul 2025): 37.3 (#157)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Expert | 1508 | 1365 |
| GPQA Diamond | 94.8% | — |
| SimpleQA Verified | 69.2% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| Vectara Hallucination Rate | — | 17.9% |
| GPQA (HELM) | — | 65.3% |

## Multimodal

- Gemini 3.7 Flash: 37.3 (#73)
- Kimi K2 (Jul 2025): —

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 26.7% | — |

## Multilingual

- Gemini 3.7 Flash: 57.6 (#7)
- Kimi K2 (Jul 2025): 49.6 (#130)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1484 | 1372 |
| LMArena Chinese | 1548 | 1415 |
| LMArena French | 1505 | 1379 |
| LMArena German | 1498 | 1387 |
| LMArena Japanese | 1512 | 1349 |
| LMArena Korean | 1483 | 1325 |
| LMArena Russian | 1516 | 1385 |
| LMArena Spanish | 1503 | 1386 |

## Instruction Following

- Gemini 3.7 Flash: 77.7 (#15)
- Kimi K2 (Jul 2025): 71.1 (#156)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1483 | 1348 |
| IFEval | — | 85% |

## Long Context

- Gemini 3.7 Flash: 45.7 (#30)
- Kimi K2 (Jul 2025): 41.2 (#145)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1492 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |

## Writing & Preference

- Gemini 3.7 Flash: 71.2 (#20)
- Kimi K2 (Jul 2025): 62.3 (#78)

| Benchmark | Gemini 3.7 Flash | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1486 | 1380 |
| LMArena Creative Writing | 1490 | 1350 |
| EQ-Bench Creative Writing | 1723 | 1666 |
| LMArena Multi-Turn | 1489 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |

## FAQ

### Is Gemini 3.7 Flash better than Kimi K2 (Jul 2025)?

Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 41.2 on the Noometry Index.

### Which is cheaper, Gemini 3.7 Flash or Kimi K2 (Jul 2025)?

Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; Gemini 3.7 Flash lists at $0.75 and $3.75.

### Is Gemini 3.7 Flash or Kimi K2 (Jul 2025) better for coding?

Gemini 3.7 Flash scores higher on coding benchmarks: 56.2 versus 42.4 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.7 Flash does, with 1.05M tokens against 262K.

### How many benchmarks do Gemini 3.7 Flash and Kimi K2 (Jul 2025) share?

20 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and Kimi K2 (Jul 2025) has 42.