Model comparison
Kimi K2.7 Code vs Mistral Small 3.2
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.2 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.
Last verified . 4 shared benchmarks.
Mistral AISummary
- 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 knowledge, where Kimi K2.7 Code leads 53.5 to 26.7.
- 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.
Side by side
| Kimi K2.7 Code | Mistral Small 3.2 | |
|---|---|---|
| Provider | Moonshot AI | Mistral AI |
| Noometry Index | 43.3 | 31.2 |
| Released | 2026-06-12 | 2025-06-20 |
| Weights | Open | Open |
| Context window | 262K | 256K |
| Max output | 262K | 16K |
| Input $ / M tokens | $0.95 | $0.0938 |
| Output $ / M tokens | $4 | $0.25 |
| Results tracked | 19 | 6 |
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Category by category
Coding Not comparable
Kimi K2.7 Code: 42.9 (#95), 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 Not comparable
Kimi K2.7 Code: 24.0 (#122), 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 leads
Kimi K2.7 Code: 39.0 (#61), Mistral Small 3.2: 18.1 (#287)
| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| Chess Puzzles | 21% | 1% |
| Epoch Capabilities Index | 149.97 | 131.74 |
| SimpleBench | 57.9% | — |
| Kagi LLM Benchmark | — | 40.4% |
| CritPt | 10% | — |
| Surface Evolver Bench | 48.8% | — |
Math Kimi K2.7 Code leads
Kimi K2.7 Code: 52.9 (#48), Mistral Small 3.2: 26.3 (#260)
| 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 leads
Kimi K2.7 Code: 53.5 (#57), Mistral Small 3.2: 26.7 (#256)
| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 87.9% | 49.1% |
| SimpleQA Verified | 36.5% | — |
Writing & Preference Not comparable
Kimi K2.7 Code: —, Mistral Small 3.2: 45.0 (#224)
| Benchmark | Kimi K2.7 Code | Mistral Small 3.2 |
|---|---|---|
| EQ-Bench Creative Writing | — | 1255 |
Frequently asked questions
Is Kimi K2.7 Code better than Mistral Small 3.2?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.2 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.