# Vals LiveCodeBench → CursorBench 3.2

Calibration · https://benchgap.net/calibration/1577 · data retrieved 2026-10-29

CursorBench 3.2 is estimated from Vals LiveCodeBench with a offset logistic curve fitted on 16 models measured on both: y = 0.5910 + (0.7302 − 0.5910) / (1 + exp(−200.00·(x − 0.8875))), R² = 0.40, cross-validated error 7.2 pp. It is used for 5 estimates.

| Estimated model | Vals LiveCodeBench | CursorBench 3.2 | Source |
|---|---|---|---|
| [GPT-5.1-Codex](https://benchgap.net/model/gpt-5-1-codex.md) | 85.6% | 59.1% | estimated ± 7.2 pp, low confidence |
| [GPT-5.1-Codex-Max](https://benchgap.net/model/gpt-5-1-codex-max.md) | 83.6% | 59.1% | estimated ± 7.2 pp, low confidence |
| [GLM-4.6](https://benchgap.net/model/glm-4-6.md) | 81.0% | 59.1% | estimated ± 7.2 pp, low confidence |
| [GLM-4.5](https://benchgap.net/model/glm-4-5.md) | 67.4% | 59.1% | estimated ± 7.2 pp, low confidence |
| [Grok Code Fast 1](https://benchgap.net/model/grok-code-fast-1.md) | 62.0% | 59.1% | estimated ± 7.2 pp, low confidence |

## Fitted on

| Model | Vals LiveCodeBench | CursorBench 3.2 |
|---|---|---|
| [Claude Fable 5](https://benchgap.net/model/claude-fable.md) | 89.8% | 70.5% |
| [Claude Fable 5.1](https://benchgap.net/model/claude-fable-5-1.md) | 90.5% | 73.4% |
| [Claude Opus 4.8](https://benchgap.net/model/claude-opus-4-8.md) | 87.8% | 62.3% |
| [Claude Opus 5](https://benchgap.net/model/claude-opus-5.md) | 89.0% | 70.0% |
| [Claude Sonnet 5](https://benchgap.net/model/claude-sonnet-5.md) | 82.4% | 61.5% |
| [Gemini 3.5 Flash](https://benchgap.net/model/gemini-3-5-flash.md) | 87.6% | 48.8% |
| [Gemini 3.6 Flash](https://benchgap.net/model/gemini-3-6-flash.md) | 88.1% | 53.5% |
| [Gemini 3.8 Flash](https://benchgap.net/model/gemini-3-8-flash.md) | 89.5% | 69.2% |
| [GLM-5.2](https://benchgap.net/model/glm-5-2.md) | 69.5% | 55.0% |
| [GPT-5.5](https://benchgap.net/model/gpt-5-5.md) | 85.3% | 58.4% |
| [GPT-5.6 Sol](https://benchgap.net/model/gpt-5-6-sol.md) | 82.6% | 67.2% |
| [GPT-5.6 Terra](https://benchgap.net/model/gpt-5-6-terra.md) | 85.9% | 64.9% |
| [Grok 4.5](https://benchgap.net/model/grok-4-5.md) | 87.4% | 66.7% |
| [Grok 4.6](https://benchgap.net/model/grok-4-6.md) | 88.2% | 70.8% |
| [Kimi K2.7 Code](https://benchgap.net/model/kimi-k2-7-code.md) | 82.1% | 49.7% |
| [Kimi K3](https://benchgap.net/model/kimi-k3.md) | 87.2% | 60.8% |