# Kimi K2.5 vs Qwen3.5-9B

> Kimi K2.5 is the stronger model overall, scoring 48.1 to 33.8 on the Noometry Index. Qwen3.5-9B costs 8.0× 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/kimi-k2-5-vs-qwen3-5-9b
- Last updated: 2026-10-12
- Shared benchmarks: 8

## Summary

- They share 8 benchmarks with published results for both. Kimi K2.5 scores higher in 5 categories and Qwen3.5-9B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Kimi K2.5 leads 34.2 to 14.5.
- The biggest single-benchmark swing is Terminal-Bench: 43.2% for Kimi K2.5 and 9.2% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.45 / $2.25 for Kimi K2.5.

## Snapshot

| | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 48.1 | 33.8 |
| Rank | 57 | 236 |
| Context | 262K | 262K |
| Input $/M | $0.45 | $0.10 |
| Output $/M | $2.25 | $0.15 |
| Weights | Open | Open |

## Coding

- Kimi K2.5: 48.8 (#53)
- Qwen3.5-9B: 35.9 (#217)

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| SciCode | 49% | 27.5% |
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 70.8% | — |
| LMArena WebDev | 1437 | — |
| SWE-bench Multilingual | 67.3% | — |
| WeirdML | 45.6% | — |
| LMArena Coding | 1474 | — |
| ALE-Bench | 821.65 | — |

## Agentic & Tool Use

- Kimi K2.5: 34.2 (#48)
- Qwen3.5-9B: 14.5 (#151)

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | 43.2% | 9.2% |
| OSWorld | 63.3% | — |
| Vending-Bench 2 | 1,198 | — |

## Reasoning

- Kimi K2.5: 31.2 (#80)
- Qwen3.5-9B: 23.1 (#182)

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| CritPt | 3.1% | 0.3% |
| Chess Puzzles | 12% | 12% |
| Epoch Capabilities Index | 148.03 | 139.46 |
| ARC-AGI-2 | 11.8% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 78.5% | — |
| NYT Connections (extended) | 69.9% | — |
| ARC-AGI-1 | 65.3% | — |
| EnigmaEval | 3.4% | — |
| Thematic Generalization | 69.4% | — |
| LMArena Hard Prompts | 1453 | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |

## Math

- Kimi K2.5: 51.8 (#53)
- Qwen3.5-9B: 34.8 (#192)

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | 62.3% | 48.5% |
| OTIS Mock AIME 2024-2025 | 92.2% | 61.7% |
| LMArena Math | 1470 | — |
| FrontierMath (Feb 2025 set) | 27.9% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Kimi K2.5: 53.6 (#56)
- Qwen3.5-9B: 46.0 (#84)

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | 87.6% | 79% |
| 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)
- Qwen3.5-9B: —

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1269 | — |
| LMArena Document | 1430 | — |

## Multilingual

- Kimi K2.5: 53.9 (#53)
- Qwen3.5-9B: —

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| 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)
- Qwen3.5-9B: —

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1431 | — |

## Long Context

- Kimi K2.5: 52.1 (#7)
- Qwen3.5-9B: —

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| 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)
- Qwen3.5-9B: —

| Benchmark | Kimi K2.5 | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1445 | — |
| LMArena Creative Writing | 1423 | — |
| EQ-Bench Creative Writing | 1579 | — |
| LMArena Multi-Turn | 1444 | — |

## FAQ

### Is Kimi K2.5 better than Qwen3.5-9B?

Kimi K2.5 is the stronger model overall, scoring 48.1 to 33.8 on the Noometry Index. Qwen3.5-9B costs 8.0× less per token, which makes it the better buy when Kimi K2.5's lead doesn't matter for your workload.

### Which is cheaper, Kimi K2.5 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Kimi K2.5 lists at $0.45 and $2.25.

### Is Kimi K2.5 or Qwen3.5-9B better for coding?

Kimi K2.5 scores higher on coding benchmarks: 48.8 versus 35.9 in the Noometry coding category.

### Which has the bigger context window?

Both accept 262K tokens.

### How many benchmarks do Kimi K2.5 and Qwen3.5-9B share?

8 benchmarks have published results for both models. Kimi K2.5 has 51 scored results on Noometry and Qwen3.5-9B has 10.