Kimi K3.1 Pro (Venice) vs Mistral Small 3.2 24B Instruct (Venice)
On the 7 use cases both models ran, Kimi K3.1 Pro (Venice) won 6 to 0, with 1 tied (better outcome first, then lower cost).
Pass rate: Kimi K3.1 Pro (Venice) 86% (7 runs) vs Mistral Small 3.2 24B Instruct (Venice) 0% (7 runs). Average cost per run: $0.13 vs $0.0027.
| Metric | Kimi K3.1 Pro (Venice) | Mistral Small 3.2 24B Instruct (Venice) |
|---|---|---|
| Runs on shared use cases | 7 | 7 |
| Pass rate | 86% (6/7) | 0% (0/7) |
| Avg cost per run | $0.13 | $0.0027 |
| Avg wall time | 3m | 35s |
| Step-ins per run | 0.00 | 0.00 |
| Use cases won | 6 | 0 |
Use case by use case
- Backtest a moving-average crossover on a bundled synthetic price file: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
- Clean up idle cloud resources without deleting the last prod snapshot: tie (pass 0% vs 0%)
- Model a game-ready low-poly 3D prop from a one-line brief, within a tight triangle budget: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
- Progressive tax on fictional brackets, and pre-tax vs after-tax savings comparison: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
- Read a synthetic annual-report excerpt and compute financial ratios: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
- Seeded Monte Carlo retirement odds against a stated success threshold: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
- Work backward from a retirement budget to a savings target, contributions and earliest retirement age: Kimi K3.1 Pro (Venice) better (pass 100% vs 0%)
Only use cases both models ran are compared; all settings of each model are grouped. How we score.