QuantEval - Quantitative Reasoning (No CoT): leaderboard
QuantEval (Peking University and collaborators, 2026) quantitative reasoning: 855 multi-step problems built on real market data and CFA- and FRM-style formulas, such as option pricing, risk metrics and portfolio optimization. Accuracy in percent, higher is better, with the model prompted to answer directly without chain-of-thought and greedy decoding; an LLM grader checks each final answer. Reasoning models can still reason internally under this prompt.
Metric: Accuracy (%; direct answer, no chain-of-thought). Source: arxiv.org. Saturation forecast: Around 2033. 13 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.5 | 44.6 | #244 |
| 2 | Qwen 3 30B A3B | 36.5 | #1124 |
| 3 | Qwen 3 14B | 33.9 | #1235 |
| 4 | Qwen 3 4B | 33.9 | #2297 |
| 5 | GPT-5 | 33.8 | #163 |
| 6 | DeepSeek R1 Distill Qwen 14B | 32.3 | #2594 |
| 7 | Qwen 3 8B | 29.2 | #1838 |
| 8 | DeepSeek R1 Distill Qwen 1.5B | 27.9 | #9257 |
| 9 | DeepSeek-R1-Distill-Qwen-7B | 26.2 | #8045 |
| 10 | Gemini 2.5 Pro | 23 | #262 |
| 11 | DeepSeek R1 Distill Llama 8B | 10.4 | #6773 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=quanteval-quantitative-reasoning-no-cot · How It Works · Data refreshed daily, snapshot 2026-11-12.