Reported Scores
| Model | Score | Source paper | Year |
|---|---|---|---|
| DeepSeek-R1 | 97.3% | Quantitative Analysis of Performance Drop in DeepSeek Model Quantization / arxiv.org | 2025 |
| DeepSeek-R1 | 79.8% | LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems / openalex.org | 2026 |
| DeepSeek-R1 | 72.2% | Benchmarking LLMs' Mathematical Reasoning with Unseen Random Variables Questions / arxiv.org | 2025 |
| DeepSeek-R1 | 30.0% | Token-Hungry, Yet Precise: DeepSeek R1 Highlights the Need for Multi-Step Reasoning Over Speed in MATH / arxiv.org | 2025 |
Interpretation
This page groups score claims extracted from papers for the same model and benchmark label. A nonzero spread means the public literature reports different values for this cluster.
Differences are not automatically errors. They may come from prompt choices, dataset versions, evaluation protocol, scoring rule, preprocessing, fine-tuning, or reporting convention. Source papers remain authoritative for their own claims. See the quality guide for how to read evidence links, manifests, and automated assessment fields.
Source coverage is a conservative count of distinct public paper URLs or titles in the cluster. It measures coverage breadth, not correctness.
Source profile reports public URL domains and publication years when they are available in extracted records. It is included for auditability only.