# DeepSeek-V2.5 (Sep 2024) vs Kimi K2.6

> Kimi K2.6 is the stronger model overall, scoring 47.7 to 37.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-kimi-k2-6
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 0 categories and Kimi K2.6 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.6 leads 57.0 to 35.9.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 37.6 | 47.7 |
| Rank | 200 | 60 |
| Context | — | 262K |
| Input $/M | — | $0.95 |
| Output $/M | — | $4 |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- Kimi K2.6: 50.7 (#43)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Coding | 1309 | 1488 |
| SWE-bench Verified | — | 76.7% |
| Aider Polyglot | 17.8% | — |
| LMArena WebDev | — | 1509 |
| SciCode | — | 53.5% |
| WeirdML | — | 55.9% |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| ALE-Bench | — | 1,093 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Agentic & Tool Use

- DeepSeek-V2.5 (Sep 2024): —
- Kimi K2.6: 21.9 (#137)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| OSWorld 2.0 | — | 4.6% |
| ExploitBench | — | 18.4% |
| GBAEval | — | 0.9% |
| GDP.pdf | — | 12% |
| Vending-Bench 2 | — | 6,205 |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)
- Kimi K2.6: 40.5 (#55)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1470 |
| NYT Connections (extended) | — | 87.2% |
| CritPt | — | 8% |
| Chess Puzzles | — | 26% |
| EBR-Bench | — | 2.4% |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 90.9% |
| LMCA | — | 37.3% |
| Epoch Capabilities Index | — | 151.05 |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- Kimi K2.6: 57.0 (#41)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Math | 1288 | 1475 |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 25.6% |
| MathArena Final-Answer Competitions | — | 72.9% |
| OTIS Mock AIME 2024-2025 | — | 96.1% |
| ProofBench | — | 16% |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- Kimi K2.6: 54.0 (#54)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Expert | 1266 | 1491 |
| GPQA Diamond | — | 90.8% |
| SimpleQA Verified | — | 34.9% |
| Vectara Hallucination Rate | — | 10.8% |

## Multimodal

- DeepSeek-V2.5 (Sep 2024): —
- Kimi K2.6: 31.6 (#103)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Vision | — | 1283 |
| Blueprint-Bench 2 | — | 3.9% |
| Furniture Assembly | — | 21.7% |
| LMArena Document | — | 1451 |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- Kimi K2.6: 54.9 (#37)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Non-English | 1273 | 1446 |
| LMArena Chinese | 1318 | 1521 |
| LMArena French | 1289 | 1471 |
| LMArena German | 1258 | 1450 |
| LMArena Japanese | 1228 | 1443 |
| LMArena Korean | 1209 | 1427 |
| LMArena Russian | 1289 | 1446 |
| LMArena Spanish | 1248 | 1464 |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- Kimi K2.6: 76.3 (#43)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Instruction Following | 1280 | 1451 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- Kimi K2.6: 44.9 (#52)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Longer Query | 1301 | 1468 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- Kimi K2.6: 68.5 (#26)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Kimi K2.6 |
|---|---|---|
| LMArena Text | 1294 | 1455 |
| LMArena Creative Writing | 1285 | 1434 |
| LMArena Multi-Turn | 1297 | 1453 |
| EQ-Bench Creative Writing | — | 1725 |
| EQ-Bench 4 | — | 1202 |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Kimi K2.6?

Kimi K2.6 is the stronger model overall, scoring 47.7 to 37.6 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or Kimi K2.6 better for coding?

Kimi K2.6 scores higher on coding benchmarks: 50.7 versus 31.7 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Kimi K2.6 share?

17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Kimi K2.6 has 51.