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What is DeepSeek R1

Deepseek is a Chinese company founded in 2023 that specializes in artificial intelligence (AI) and the development of artificial general intelligence (AGI). One of its flagship products, Deepseek R1, offers cutting-edge AI technology designed to enhance user productivity and creativity. With Deepseek R1, users can experience advanced reasoning and problem-solving capabilities, helping them achieve better results across various tasks.

The applications of Deepseek R1 are incredibly versatile, ranging from code generation to natural language understanding, making it suitable for a wide array of intelligent processing needs. It provides real-time information processing, delivering quick and efficient responses that significantly boost work efficiency. Additionally, users can easily export and share their results, further driving innovation and exploring new possibilities.

Through Deepseek R1, Deepseek aims to push the boundaries of AI technology, allowing more people to benefit from intelligent, adaptable, and transformative AI solutions.

Feature Of DeepSeek R1 Online

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Architecture

DeepSeek R1 is designed using a Mixture of Experts (MoE) framework, featuring 37 billion active parameters and a total of 671 billion parameters, with a context length of 128K. It employs advanced reinforcement learning techniques to enable self-verification, multi-step reflection, and reasoning that aligns with human thought processes.

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Performance

DeepSeek R1 showcases impressive performance metrics: it achieves 97.3% accuracy on the MATH-500 benchmark, outperforms 96.3% of participants on Codeforces, and has a 79.8% pass rate on AIME 2024, positioning it among the top AI models globally.

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Deployment

DeepSeek R1 provides an OpenAI-compatible API endpoint priced at $0.14 per million tokens. It is open source, with MIT-licensed model weights and distilled variants ranging from 1.5B to 70B parameters available for commercial use. You can find it in the GitHub repository.

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Model Ecosystem

DeepSeek R1 offers various model variants, including the base model (R1-Zero), an enhanced version (R1), and six lightweight distilled models. It is optimized for complex problem-solving, multilingual understanding, and production-grade code generation.

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Roadmap

The development roadmap includes continuous upgrades for multimodal support, enhancements in conversational capabilities, and optimizations for distributed inference, all driven by collaboration within the open-source community.

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Open Source

DeepSeek R1 is the world's first reasoning model developed purely through reinforcement learning, featuring an open-source implementation. Its 32B lightweight version achieves GPT-4-level performance in mathematics at 90% lower cost, along with chain-of-thought visualization capabilities to address the challenges of AI's 'black box' nature.

Frequently Asked Questions

DeepSeek R1 utilizes a MoE system with 37B active parameters and 671B total parameters, supporting 128K context, optimized through pure reinforcement learning without the need for supervised fine-tuning.

DeepSeek R1 costs 90-95% less, at $0.14 per million input tokens, compared to OpenAI O1's $15, while offering equivalent reasoning capabilities.

Yes, DeepSeek R1 supports local deployment via vLLM/SGLang and provides 6 distilled models (ranging from 1.5B to 70B parameters) suitable for resource-constrained environments.

DeepSeek R1 achieves state-of-the-art results in benchmarks such as MATH-500 (97.3%), Codeforces (96.3rd percentile), and AIME 2024 (79.8%), outperforming most commercial models.

Yes, DeepSeek R1 is MIT-licensed, with full model weights available on GitHub, allowing for commercial use and modification.

DeepSeek R1 features self-verification and multi-step reflection, enabling it to solve complex problems through visible chain-of-thought reasoning.

DeepSeek R1 is ideal for AI research, enterprise code generation, mathematical modeling, and multilingual NLP applications that require advanced reasoning.

It offers OpenAI-compatible API endpoints with 128K context support and intelligent caching, priced at $0.14 per million tokens for cache hits.

DeepSeek R1 includes built-in repetition control (temperature set between 0.5 and 0.7) and alignment mechanisms to prevent common infinite loops found in RL-trained models.

Technical documentation can be found on the official DeepSeek R1 website or its GitHub page.

DeepSeek-R1-Distill Models (download online)

ModelBase ModelDownload
DeepSeek-R1-Distill-Qwen-1.5BQwen2.5-Math-1.5B🤗 HuggingFace
DeepSeek-R1-Distill-Qwen-7BQwen2.5-Math-7B🤗 HuggingFace
DeepSeek-R1-Distill-Llama-8BLlama-3.1-8B🤗 HuggingFace
DeepSeek-R1-Distill-Qwen-14BQwen2.5-14B🤗 HuggingFace
DeepSeek-R1-Distill-Qwen-32BQwen2.5-32B🤗 HuggingFace
DeepSeek-R1-Distill-Llama-70BLlama-3.3-70B-Instruct🤗 HuggingFace

More DeepSeek r1 Models Download >>>

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