DeepSeek has launched an upgrade to its AI model, DeepSeek-R1, which brings significant enhancements to its capabilities. The update is now live on the web, app, and API, and boasts deeper insights and stronger reasoning.
The DeepSeek-R1 model uses reinforcement learning to achieve reasoning capabilities comparable to OpenAI's o1. Its Mixture of Experts (MoE) architecture features 671B total parameters, but activates only 37B for each forward pass, making it efficient. Additionally, smaller distilled versions of the model are available, enabling deployment on consumer hardware.
DeepSeek-R1 has demonstrated impressive performance, matching or exceeding OpenAI's o1 in various benchmarks. The model's training pipeline combines pure reinforcement learning with cold-start data and iterative fine-tuning, and its reward function prioritizes both accuracy and format adherence.
This update positions DeepSeek as a leader in the open-source AI landscape, narrowing the gap with proprietary models. By making smaller, distilled models available, DeepSeek is democratizing access to reasoning-capable AI, enabling widespread deployment on consumer hardware.
