NoLiMa

NoLiMa is a benchmark for reading and reasoning over very long inputs. The official description says: "NoLiMa - long context benchmark evaluating retrieval and reasoning without explicit long-context matching". Below we describe in simple words what benchmarks of this type generally examine.

NoLiMa measures reading and reasoning over very long inputs. In detail, it checks:

• finding relevant facts buried in documents hundreds of thousands of tokens long
• retrieving multiple needles hidden across the full context
• reasoning over whole books, codebases or conversation histories
• staying accurate near the context window limit (no 'lost in the middle' falloff)

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: NoLiMa - long context benchmark evaluating retrieval and reasoning without explicit long-context matching.

What is the NoLiMa benchmark?

NoLiMa is a benchmark for reading and reasoning over very long inputs. The official description says: 'NoLiMa - long context benchmark evaluating retrieval and reasoning without explicit long-context matching'. Below we describe in simple words what benchmarks of this type generally examine.

What does NoLiMa test?

NoLiMa mainly measures reading and reasoning over very long inputs. Concretely, it checks: finding relevant facts buried in documents hundreds of thousands of tokens long; retrieving multiple needles hidden across the full context; reasoning over whole books, codebases or conversation histories.

How is the NoLiMa score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get NoLiMa data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/nolima/scores) or pull it directly from the Open LLM Radar API with any HTTP client.