What sets it apart from other AI models is its ‘test-time scaling,’ a technique that allows it to iterate its responses by dynamically using additional computational resources during testing. Reportedly,

It's cheap to copy already built models from their outputs, but likely still expensive to train new models that push the boundaries.

AI researchers at Stanford and the University of Washington were able to train an AI "reasoning" model for under $50 in cloud compute credits, according

A team of researchers at Stanford and the University of Washington have developed an AI reasoning model, s1, for less than $50. This is a massive achievement, given the notion that significant financial resources are essential for developing AI reasoning models.

Researchers at Stanford and the University of Washington have developed a model that performs comparably to OpenAI o1 and DeepSeek R1 models in math and coding — for less than $50 of cloud compute credits.

A team of researchers from Stanford University and the University of Washington have developed a new reasoning model, dubbed s1, that could beat OpenAI’s o1 and DeepSeek’s R1, all for less than $50 in cloud computing costs.

The AI takes on OpenAI's o1 reasoning variant. The model, dubbed s1, was trained using a dataset of 1,000 questions for under $50.

AI researchers from Stanford and the University of Washington have developed a reasoning model, s1, for less than $50 using cloud compute credits. The

Researchers from Stanford and Washington developed an AI model for $50, rivaling top models like OpenAI's o1 and DeepSeek.