Table 1 | Template for DeepSeek-R1-Zero.

January 22, 2025 - To support the research community, we open-source DeepSeek-R1-Zero, DeepSeek-R1, and six dense models (1.5B, 7B, 8B, 14B, 32B, 70B) distilled from DeepSeek-R1 based on Qwen and Llama. From: Wenfeng Liang [view email] [v1] Wed, 22 Jan 2025 15:19:35 UTC (928 KB) ... View a PDF of the paper titled DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning, by DeepSeek-AI and 199 other authors

DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen.

DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen.

Deepseek-v3 · technical report. arXiv preprint arXiv:2412.19437, 2024. Liu, Z., Chen, C., Du, C., Lee, W. S., and Lin, M. Oat: A research-friendly framework for llm online alignment. ... Liu, Z., Chen, C., Li, W., Pang, T., Du, C., and Lin, M. There may not be aha moment in r1-zero-like training

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DeepSeek-R1-Zero (R1-Zero).

DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen.

Zhang, R., Xu, Q., ... & Li, S. S. (2025). DeepSeek-R1:

📄 More details: https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf · 🌐 API Access & Pricing · ⚙️ Use DeepSeek-R1 by setting model=deepseek-reasoner · 💰 $0.14 / million input tokens (cache hit) 💰 $0.55 / million input tokens (cache miss) 💰 $2.19 / million output tokens ·

January 20, 2025 - PDF | The paper "DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning" introduces DeepSeek-R1-Zero and DeepSeek-R1, two... | Find, read and cite all the research you need on ResearchGate

DeepSeek-R1 has received a minor version upgrade to DeepSeek-R1-0528 for the 8 billion parameter distilled model and the full 671 billion parameter model. In this update, DeepSeek R1 has significantly improved its reasoning and inference capabilities. The model has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic.

March 5, 2025 - They intend to replicate the R1-distil models, by extracting a high-quality reasoning corpus from DeepSeek- R1, reproduce the pure reinforcement learning pipeline used to create R1-Zero model, and demonstrate the

January 20, 2025 - I got a bunch of such requests but declined all of them because I do not want to help them train a model to replace myself and achieve a short AGI timeline. But it is less relevant now because R1 Zero told the world you can just use outcome based RL and skip the expensive human annotation. Continue this thread Continue this thread Continue this thread Continue this thread ... The DeepSeek R1 paper is out.

July 3, 2025 - Cold Start (Phase 1): Starting with the pre-trained model DeepSeek-V3-Base, the model undergoes supervised fine-tuning on a small dataset of results collected from DeepSeek-R1-Zero. These results were validated as high-quality and readable. This dataset contains thousands of samples, making it relatively small.

DeepSeek-R1: Building on R1-Zero, this version incorporates a small amount of high-quality "cold-start" data alongside iterative reinforcement learning and supervised fine-tuning to produce more coherent, user-friendly outputs while maintaining state-of-the-art reasoning performance.

September 17, 2025 - We believe that these instruction-tuned versions will also greatly contribute to the research community by providing a valuable resource for understanding the mechanisms underlying long CoT reasoning models and for promoting the development of more powerful reasoning models. We release DeepSeek-R1-Zero, DeepSeek-R1, data samples and distilled models to the public as described in the ‘Code availability’ section.

DeepSeek R1 vs DeepSeek V3 vs DeepSeek ... and reinforcement learning to boost · performance. DeepSeek R1-Zero: • Similar architecture but prioritizes zero-shot capabilities without fine- tuning....

February 14, 2025 - DeepSeek-R1-Zero struggles with challenges like poor readability, and language mixing.