openai/mrcr

OpenAI MRCR: Long context multiple needle in a haystack benchmark OpenAI MRCR (Multi-round co-reference resolution) is a long context dataset for benchmarking an LLM's ability to distinguish between multiple needles hidden in context. This eval is inspired by the MRCR eval first introduced by Gemini (https://arxiv.org/pdf/2409.12640v2). OpenAI MRCR expands the tasks's difficulty and provides opensource data for reproducing results. The task is as follows: The model is given a long… See the full description on the dataset page: https://huggingface.co/datasets/openai/mrcr.

<iframe src="https://silytics.si/embed/item/6169c2e3-a11b-43cf-ab77-e3560a1fd17f" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.