# Gemma 3 27B vs Kimi K2.5

> Kimi K2.5 is the stronger model overall, scoring 47.8 to 30.5 on the Noometry Index. Gemma 3 27B costs 9.0× less per token, which makes it the better buy when Kimi K2.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemma-3-27b-vs-kimi-k2-5
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and Kimi K2.5 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.5 leads 53.6 to 25.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 22.5% for Gemma 3 27B and 92.2% for Kimi K2.5.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.45 / $2.25 for Kimi K2.5.
- Kimi K2.5 accepts more context: 262K tokens versus 131K.

## Snapshot

| | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| Provider | Google | Moonshot AI |
| Noometry Index | 30.5 | 47.8 |
| Rank | 277 | 50 |
| Context | 131K | 262K |
| Input $/M | $0.08 | $0.45 |
| Output $/M | $0.16 | $2.25 |
| Weights | Open | Open |

## Coding

- Gemma 3 27B: 22.1 (#329)
- Kimi K2.5: 48.7 (#48)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| SciCode | 21.2% | 49% |
| LMArena Coding | 1322 | 1474 |
| SWE-bench Verified | — | 73.8% |
| SWE-bench Verified (bash only) | — | 70.8% |
| Aider Polyglot | 4.9% | — |
| LMArena WebDev | — | 1436 |
| SWE-bench Multilingual | — | 67.3% |
| WeirdML | — | 45.6% |
| LiveBench Coding | 39.9% | — |
| ALE-Bench | — | 821.65 |

## Agentic & Tool Use

- Gemma 3 27B: 24.9 (#105)
- Kimi K2.5: 34.0 (#44)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| Terminal-Bench | — | 43.2% |
| Berkeley Function Calling Leaderboard | 29.5% | — |
| OSWorld | — | 63.3% |
| Vending-Bench 2 | — | 1,198 |

## Reasoning

- Gemma 3 27B: 16.3 (#297)
- Kimi K2.5: 31.2 (#74)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| Kagi LLM Benchmark | 40.4% | 78.5% |
| CritPt | 0% | 3.1% |
| Chess Puzzles | 0% | 12% |
| LMArena Hard Prompts | 1340 | 1454 |
| Epoch Capabilities Index | 130.04 | 148.05 |
| ARC-AGI-2 | — | 11.8% |
| SimpleBench | — | 46.8% |
| NYT Connections (extended) | — | 69.9% |
| ARC-AGI-1 | — | 65.3% |
| EnigmaEval | — | 3.4% |
| Thematic Generalization | — | 69.4% |
| LiveBench Reasoning | 43.8% | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| LiveBench | 50% | — |

## Math

- Gemma 3 27B: 24.4 (#261)
- Kimi K2.5: 50.3 (#46)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 92.2% |
| LMArena Math | 1312 | 1470 |
| MathArena Final-Answer Competitions | — | 62.3% |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
| FrontierMath (Feb 2025 set) | — | 27.9% |
| FrontierMath Tier 4 (v1) | — | 4.2% |

## Knowledge

- Gemma 3 27B: 25.4 (#256)
- Kimi K2.5: 53.6 (#52)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| GPQA Diamond | 47.7% | 87.6% |
| Vectara Hallucination Rate | 7.4% | 14.2% |
| LMArena Expert | 1303 | 1466 |
| Humanity's Last Exam | — | 24.4% |
| SimpleQA Verified | — | 34.3% |
| Confabulations | 40.3% | — |

## Multimodal

- Gemma 3 27B: 32.0 (#94)
- Kimi K2.5: 40.4 (#37)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| LMArena Vision | 1165 | 1269 |
| GeoBench | 52% | — |
| LMArena Document | — | 1430 |

## Multilingual

- Gemma 3 27B: 47.0 (#150)
- Kimi K2.5: 54.1 (#50)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| LMArena Non-English | 1334 | 1433 |
| LMArena Chinese | 1347 | 1495 |
| LMArena French | 1368 | 1454 |
| LMArena German | 1362 | 1441 |
| LMArena Japanese | 1287 | 1422 |
| LMArena Korean | 1308 | 1412 |
| LMArena Russian | 1349 | 1436 |
| LMArena Spanish | 1348 | 1450 |

## Instruction Following

- Gemma 3 27B: 70.8 (#155)
- Kimi K2.5: 75.5 (#60)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| LMArena Instruction Following | 1321 | 1431 |
| LiveBench Instruction Following | 74.9% | — |

## Long Context

- Gemma 3 27B: 27.6 (#288)
- Kimi K2.5: 52.1 (#7)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| Fiction.LiveBench | 33.3% | 86.1% |
| LMArena Longer Query | 1333 | 1445 |
| CL-bench | — | 19.3% |
| CL-bench Life | — | 13.2% |

## Writing & Preference

- Gemma 3 27B: 52.7 (#161)
- Kimi K2.5: 65.3 (#51)

| Benchmark | Gemma 3 27B | Kimi K2.5 |
|---|---|---|
| LMArena Text | 1358 | 1445 |
| LMArena Creative Writing | 1346 | 1423 |
| EQ-Bench Creative Writing | 1266 | 1579 |
| LMArena Multi-Turn | 1344 | 1444 |
| Short-Story Creative Writing | 79.9% | — |
| LiveBench Language | 34.6% | — |

## FAQ

### Is Gemma 3 27B better than Kimi K2.5?

Kimi K2.5 is the stronger model overall, scoring 47.8 to 30.5 on the Noometry Index. Gemma 3 27B costs 9.0× less per token, which makes it the better buy when Kimi K2.5's lead doesn't matter for your workload.

### Which is cheaper, Gemma 3 27B or Kimi K2.5?

Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; Kimi K2.5 lists at $0.45 and $2.25.

### Is Gemma 3 27B or Kimi K2.5 better for coding?

Kimi K2.5 scores higher on coding benchmarks: 48.7 versus 22.1 in the Noometry coding category.

### Which has the bigger context window?

Kimi K2.5 does, with 262K tokens against 131K.

### How many benchmarks do Gemma 3 27B and Kimi K2.5 share?

28 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and Kimi K2.5 has 51.