Llama-4-Scout-17B-16E-Instruct
Llama-4-Scout-17B-16E-Instruct is an AI model published by Facebook AI研究实验室, released on 2025-04-05, for Multimodal model, with 109B parameters, and 1000K context length, requiring about 218GB storage, under the Llama4 License license, with a 74.30 score on MMLU Pro.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
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Open source & experience
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Benchmark Results
Llama 4 Scout Instruct currently shows benchmark results led by MMLU Pro (82 / 126, score 74.30), GPQA Diamond (146 / 179, score 57.20), LiveCodeBench (111 / 120, score 32.80). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
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Model Overview
Llama-4-Scout-17B-16E-Instruct is an AI model published by Facebook AI研究实验室, released on 2025-04-05, for Multimodal model, with 109B parameters, and 1000K context length, requiring about 218GB storage, under the Llama4 License license, with a 74.30 score on MMLU Pro.
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