Unveiling DeepSeek-R1: The New-Generation LLM Shaking Up the Global AI Community — Accessible via NetMind Power

DeepSeek-R1 is the latest open-source large language model (LLM) from DeepSeek, following the success of DeepSeek-V3. It introduces a novel training method called R1-Zero, which uses pure reinforcement learning (RL) without supervised fine-tuning. This approach allows the model to develop authentic reasoning capabilities, including self-correction and extended chain-of-thought, while maintaining exceptional cost-efficiency. DeepSeek-R1 is available via NetMind Power’s Model API, offering high performance at a fraction of the cost of proprietary models like OpenAI’s o1.

Key Ideas

Pure RL for Reasoning: R1-Zero trains using simple reward signals—accuracy and formatting—without pre-defined examples, enabling the model to discover its own reasoning strategies.
Cost-Effective Performance: DeepSeek-R1 delivers near state-of-the-art results at just $2.19 per million output tokens, compared to $60.00 for OpenAI’s o1, making it nearly 30x cheaper.

Why It Matters?

Developers have chances to experiment with GRPO-based RL workflows and build reasoning-intensive applications using DeepSeek-R1’s open-source checkpoints. They should explore the model’s tag formatting and cold-start data structure to create interpretable outputs for math, code, and logic tasks.

Entrepreneurs can leverage DeepSeek-R1’s low-cost API to develop AI products that require deep reasoning—such as tutoring bots, coding assistants, or financial analysis tools. A lean pricing model enables competitive offerings in markets traditionally dominated by expensive closed-source models.