DeepSeek R-1: Open-Source AI model
DeepSeek R-1 rivals OpenAI’s o1 at 13x less cost. A groundbreaking, open-source model reshaping AI innovation—open for all to explore.
Imagine an AI model that rivals OpenAI’s o1 but costs 13 times less to operate. That’s exactly what DeepSeek R-1 has accomplished. Developed by Liang Wenfeng’s team at High-Flyer, a Chinese quant-trading firm, this breakthrough is turning heads across the AI community.
Marc Andreessen sums it up best:
"DeepSeek R1 is one of the most amazing and impressive breakthroughs I’ve ever seen – and as open source, a profound gift to the world."
What Makes DeepSeek R-1 Special?
DeepSeek R-1 leverages techniques like model distillation and sparsity to achieve its performance edge. With a mere $5.6 million investment for its earlier V3 version, High-Flyer optimized leftover GPU capacity to produce what is now a serious contender in the AI space.
The implications are profound. OpenAI and Meta—leaders in closed and open-source AI respectively—are now looking over their shoulders. Meta, once at the top of the open-source game, has reportedly gone into panic mode. OpenAI may also feel the heat, as R-1 and other open-source efforts offer serious competition at a fraction of the cost.
Why Open-Source Matters
As Sebastien Bubeck of OpenAI notes, reasoning models are “extremely scalable”. Yet, open-source models like DeepSeek R-1 introduce a democratized dynamic to innovation. Anyone, anywhere in the world, can tinker, improve, and build upon them. The pace of discovery is accelerating as more researchers dive into these open projects.
ByteDance, the parent company of TikTok, recently released Doubao-1.5-pro, another remarkable model matching GPT-4o’s performance while being eight times cheaper. The race is on, and open-source is leading the charge.
Quick Demo: DeepSeek on iOS
Curious how all this translates to practical applications? Let’s take a look at the DeepSeek iOS app, which integrates reasoning models like DeepSeek R-1 into a sleek mobile experience.
Running DeepSeek Locally
For those interested in running DeepSeek R-1 locally, I tried it using Ollama on a Mac mini M2. Downloading and running the 14B model was straightforward with the following command:
ollama run deepseek-r1:14bOnce set up, I tested it by asking about cooking cod. The responses were quick and detailed, demonstrating the model’s impressive reasoning capabilities even on local hardware. Running it locally requires significant resources, but it’s a great option for experimentation or integrating into custom workflows.
The Road Ahead
While DeepSeek may be a fast follower rather than a true pioneer, its success proves one thing: the proliferation of performant models is inevitable. Businesses and developers now face a rapidly shifting landscape.
Open-source will continue to disrupt traditional business models while raising new questions about AI safety.
What’s your take on these developments? Could open-source breakthroughs like DeepSeek R-1 redefine the AI landscape? Let me know in the comments!
Rob Hoeijmakers
