DeepSeek-R1 is an open-source language design developed on DeepSeek-V3-Base that’s been making waves in the AI community. Not just does it match-or even surpass-OpenAI’s o1 model in numerous criteria, but it likewise comes with totally MIT-licensed weights. This marks it as the very first non-OpenAI/Google model to deliver strong reasoning capabilities in an open and available manner.

What makes DeepSeek-R1 particularly interesting is its openness. Unlike the less-open methods from some industry leaders, DeepSeek has released a detailed training method in their paper. The model is also incredibly affordable, with input tokens costing simply $0.14-0.55 per million (vs o1’s $15) and output tokens at $2.19 per million (vs o1’s $60).

Until ~ GPT-4, the common wisdom was that better designs needed more information and compute. While that’s still valid, models like o1 and R1 demonstrate an option: inference-time scaling through thinking.

The Essentials

The DeepSeek-R1 paper provided numerous models, however main among them were R1 and photorum.eclat-mauve.fr R1-Zero. Following these are a series of distilled designs that, [forum.batman.gainedge.org](https://forum.batman.gainedge.org/index.php?action=profile