DeepSeek-R1
DeepSeek-R1 is an AI model published by DeepSeek-AI, released on 2025-01-20, for Reasoning model, and 128K tokens context length, requiring about 134GB storage, under the MIT License license, with a 97.30 score on MATH-500.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
DeepSeek-R1 currently shows benchmark results led by MMLU (8 / 65, score 90.80), MMLU Pro (37 / 126, score 84), MATH-500 (13 / 44, score 97.30). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
DeepSeek-R1 is an AI model published by DeepSeek-AI, released on 2025-01-20, for Reasoning model, and 128K tokens context length, requiring about 134GB storage, under the MIT License license, with a 97.30 score on MATH-500.
Follow DataLearner on WeChat for AI model updates and research notes.
No curated comparisons for this model yet.
Want a custom combination? Open the compare tool
