It is a next-generation reasoning model designed to run locally in your browser with WebGPU acceleration, enabling advanced AI capabilities without sending data to external servers.
It is a next-generation reasoning model designed to run locally in your browser with WebGPU acceleration, enabling advanced AI capabilities without sending data to external servers. DeepSeek R1 is powered by **DeepSeek-R1-Distill-Qwen-1.5B**, a 1.5-billion-parameter reasoning model optimized for in-browser inference using **🤗 Transformers.js** and **ONNX Runtime Web**. Once loaded, it can operate entirely offline, making it a privacy-focused solution for AI tasks.
Built on a **Mixture of Experts (MoE)** architecture with **37 billion active parameters** and **671 billion total parameters**, DeepSeek R1 supports a **128K context length** and implements advanced reinforcement learning for self-verification, multi-step reflection, and human-aligned reasoning. It excels in complex problem-solving, multilingual understanding, and production-grade code generation, achieving **97.3% accuracy on MATH-500**, outperforming **96.3% of Codeforces participants** in coding, and achieving a **79.8% pass rate on AIME 2024**, positioning it among the top-performing AI models globally.
DeepSeek R1 is available in multiple variants, including a **base model (R1-Zero)**, an **enhanced model (R1)**, and **six lightweight distilled models** ranging from 1.5B to 70B parameters. It is optimized for tasks like mathematical reasoning, code generation, and natural language understanding, with continuous upgrades for multimodal support, conversational enhancement, and distributed inference optimization.
The model is **open-source** under the MIT license, offering commercial use of its distilled variants. It also provides an **OpenAI-compatible API endpoint** at **$0.14 per million tokens**, making it **90-95% more cost-effective** than OpenAI o1. Additionally, its intelligent caching system reduces costs for repeated queries by up to **90%**.
DeepSeek R1 is the **world’s first pure reinforcement learning-developed reasoning model** with an open-source implementation. Its **32B lightweight version** achieves **GPT-4-level math performance at 90% lower cost** and features **Chain-of-Thought visualization** to address AI “black box” challenges. This makes it a groundbreaking, cost-efficient alternative for developers and enterprises seeking state-of-the-art AI capabilities.
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