# Kimi K2.7 Code vs Mistral Small 3.2

> Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 13× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/kimi-k2-7-code-vs-mistral-small-3-2
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Kimi K2.7 Code scores higher in 3 categories and Mistral Small 3.2 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.6 to 24.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 30.3% for Mistral Small 3.2.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 256K.

## Snapshot

| | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 43.0 | 30.8 |
| Rank | 90 | 271 |
| Context | 262K | 256K |
| Input $/M | $0.95 | $0.0938 |
| Output $/M | $4 | $0.25 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.4 (#92)
- Mistral Small 3.2: —

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| SciCode | 47.5% | — |
| WeirdML | 54.1% | — |
| ALE-Bench | 886.23 | — |

## Agentic & Tool Use

- Kimi K2.7 Code: 23.9 (#115)
- Mistral Small 3.2: —

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| APEX-Agents | 37.6% | — |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 38.2 (#56)
- Mistral Small 3.2: 17.5 (#282)

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| Chess Puzzles | 21% | 1% |
| Epoch Capabilities Index | 150.01 | 131.73 |
| SimpleBench | 57.9% | — |
| Kagi LLM Benchmark | — | 40.4% |
| CritPt | 10% | — |
| Surface Evolver Bench | 48.8% | — |

## Math

- Kimi K2.7 Code: 52.6 (#39)
- Mistral Small 3.2: 24.9 (#251)

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 30.3% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |

## Knowledge

- Kimi K2.7 Code: 53.6 (#51)
- Mistral Small 3.2: 26.8 (#249)

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 87.9% | 49.1% |
| SimpleQA Verified | 36.5% | — |

## Writing & Preference

- Kimi K2.7 Code: —
- Mistral Small 3.2: 45.1 (#219)

| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| EQ-Bench Creative Writing | — | 1255 |

## FAQ

### Is Kimi K2.7 Code better than Mistral Small 3.2?

Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 13× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

### Which is cheaper, Kimi K2.7 Code or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 256K.

### How many benchmarks do Kimi K2.7 Code and Mistral Small 3.2 share?

4 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Mistral Small 3.2 has 6.