GPT-6.1 Sol vs Kimi K3.1 Pro (Venice)
On the 7 use cases both models ran, GPT-6.1 Sol won 7 to 0 (better outcome first, then lower cost).
Pass rate: GPT-6.1 Sol 100% (7 runs) vs Kimi K3.1 Pro (Venice) 100% (7 runs). Average cost per run: $0.05 vs $0.16.
| Metric | GPT-6.1 Sol | Kimi K3.1 Pro (Venice) |
|---|---|---|
| Runs on shared use cases | 7 | 7 |
| Pass rate | 100% (7/7) | 100% (7/7) |
| Avg cost per run | $0.05 | $0.16 |
| Avg wall time | 1m | 5m |
| Step-ins per run | 0.00 | 0.00 |
| Use cases won | 7 | 0 |
Use case by use case
- Backtest a moving-average crossover on a bundled synthetic price file: GPT-6.1 Sol better (pass 100% vs 100%)
- Life-like automaton from RLE with a Klein-bottle grid and a playable animated page: GPT-6.1 Sol better (pass 100% vs 100%)
- Model a game-ready low-poly 3D prop from a one-line brief, within a tight triangle budget: GPT-6.1 Sol better (pass 100% vs 100%)
- Progressive tax on fictional brackets, and pre-tax vs after-tax savings comparison: GPT-6.1 Sol better (pass 100% vs 100%)
- Read a synthetic annual-report excerpt and compute financial ratios: GPT-6.1 Sol better (pass 100% vs 100%)
- Seeded Monte Carlo retirement odds against a stated success threshold: GPT-6.1 Sol better (pass 100% vs 100%)
- Work backward from a retirement budget to a savings target, contributions and earliest retirement age: GPT-6.1 Sol better (pass 100% vs 100%)
Only use cases both models ran are compared; all settings of each model are grouped. How we score.