# Unified Multi-task Language Understanding and Instruction Following on Open LLM Leaderboard Source: [Unified Multi-task Language Understanding and Instruction Following on Open LLM Leaderboard]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:50:02.463Z Comprehensive evaluation suite for large language models on the Open LLM Leaderboard, specifically targeting unified multi-task understanding, advanced reasoning (MATH, BBH), expert knowledge (GPQA), and instruction following capabilities (IFE). A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Unified Multi-task Language Understanding and Instruction Following | | Dataset (including any stated split) | Open LLM Leaderboard | | Metric | MMLU-P (Accuracy) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 0 of 0 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [MMLU-P (Accuracy)](): Higher is better; unit: PERCENT. - [GPQA (Accuracy)](): Higher is better; unit: PERCENT. - [BBH (Accuracy)](): Higher is better; unit: PERCENT. - [MATH (Exact Match)](): Higher is better; unit: PERCENT. - [MuSR (Accuracy)](): Higher is better; unit: PERCENT. - [IFE-I (Strict Accuracy)](): Higher is better; unit: PERCENT. - [IFE-P (Strict Accuracy)](): Higher is better; unit: PERCENT. ## Recorded results | Method | MMLU-P (Accuracy) | Result date | Report paper | | --- | --- | --- | --- | Page 1 of 1. This is an index page, not the full collection.