# Kimi K2.5 vs Qwen2.5 32B Instruct

> Kimi K2.5 is the stronger model overall, scoring 48.1 to 30.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/kimi-k2-5-vs-qwen2-5-32b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Kimi K2.5 scores higher in 4 categories and Qwen2.5 32B Instruct in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.5 leads 51.8 to 16.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 92.2% for Kimi K2.5 and 7.4% for Qwen2.5 32B Instruct.
- Kimi K2.5 is cheaper at $0.45 / $2.25 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Kimi K2.5 accepts more context: 262K tokens versus 131K.

## Snapshot

| | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 48.1 | 30.1 |
| Rank | 57 | 297 |
| Context | 262K | 131K |
| Input $/M | $0.45 | $0.70 |
| Output $/M | $2.25 | $2.80 |
| Weights | Open | Open |

## Coding

- Kimi K2.5: 48.8 (#53)
- Qwen2.5 32B Instruct: 38.7 (#169)

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 70.8% | — |
| LMArena WebDev | 1437 | — |
| SWE-bench Multilingual | 67.3% | — |
| SciCode | 49% | — |
| WeirdML | 45.6% | — |
| BigCodeBench Instruct | — | 45% |
| LMArena Coding | 1474 | — |
| BigCodeBench Complete | — | 52.3% |
| ALE-Bench | 821.65 | — |

## Agentic & Tool Use

- Kimi K2.5: 34.2 (#48)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| Terminal-Bench | 43.2% | — |
| OSWorld | 63.3% | — |
| Vending-Bench 2 | 1,198 | — |

## Reasoning

- Kimi K2.5: 31.2 (#80)
- Qwen2.5 32B Instruct: 19.2 (#266)

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| Chess Puzzles | 12% | 0% |
| Epoch Capabilities Index | 148.03 | 128.52 |
| ARC-AGI-2 | 11.8% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 78.5% | — |
| NYT Connections (extended) | 69.9% | — |
| ARC-AGI-1 | 65.3% | — |
| CritPt | 3.1% | — |
| EnigmaEval | 3.4% | — |
| Thematic Generalization | 69.4% | — |
| LMArena Hard Prompts | 1453 | — |

## Math

- Kimi K2.5: 51.8 (#53)
- Qwen2.5 32B Instruct: 16.2 (#296)

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 92.2% | 7.4% |
| MathArena Final-Answer Competitions | 62.3% | — |
| LMArena Math | 1470 | — |
| MATH Level 5 | — | 56.1% |
| FrontierMath (Feb 2025 set) | 27.9% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Kimi K2.5: 53.6 (#56)
- Qwen2.5 32B Instruct: 24.9 (#266)

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 87.6% | 46.1% |
| Humanity's Last Exam | 24.4% | — |
| SimpleQA Verified | 34.3% | — |
| Vectara Hallucination Rate | 14.2% | — |
| LMArena Expert | 1466 | — |

## Multimodal

- Kimi K2.5: 41.1 (#39)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Vision | 1269 | — |
| LMArena Document | 1430 | — |

## Multilingual

- Kimi K2.5: 53.9 (#53)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1433 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1454 | — |
| LMArena German | 1441 | — |
| LMArena Japanese | 1421 | — |
| LMArena Korean | 1410 | — |
| LMArena Russian | 1435 | — |
| LMArena Spanish | 1450 | — |

## Instruction Following

- Kimi K2.5: 75.3 (#64)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Instruction Following | 1431 | — |

## Long Context

- Kimi K2.5: 52.1 (#7)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| Fiction.LiveBench | 86.1% | — |
| CL-bench | 19.3% | — |
| CL-bench Life | 13.2% | — |
| LMArena Longer Query | 1445 | — |

## Writing & Preference

- Kimi K2.5: 65.1 (#53)
- Qwen2.5 32B Instruct: —

| Benchmark | Kimi K2.5 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1445 | — |
| LMArena Creative Writing | 1423 | — |
| EQ-Bench Creative Writing | 1579 | — |
| LMArena Multi-Turn | 1444 | — |

## FAQ

### Is Kimi K2.5 better than Qwen2.5 32B Instruct?

Kimi K2.5 is the stronger model overall, scoring 48.1 to 30.1 on the Noometry Index.

### Which is cheaper, Kimi K2.5 or Qwen2.5 32B Instruct?

Kimi K2.5 is cheaper. It lists at $0.45 per million input tokens and $2.25 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.

### Is Kimi K2.5 or Qwen2.5 32B Instruct better for coding?

Kimi K2.5 scores higher on coding benchmarks: 48.8 versus 38.7 in the Noometry coding category.

### Which has the bigger context window?

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

### How many benchmarks do Kimi K2.5 and Qwen2.5 32B Instruct share?

4 benchmarks have published results for both models. Kimi K2.5 has 51 scored results on Noometry and Qwen2.5 32B Instruct has 7.