DeepSeek-R1 opens a new reasoning model to developers

DeepSeek released DeepSeek-R1 today, publishing model weights under an MIT license alongside a technical report. The Chinese laboratory says the system is designed for reasoning tasks and can show extended intermediate work before delivering an answer.

Its training uses reinforcement learning to develop behaviors such as checking and revising a line of reasoning, followed by supervised examples and further alignment. DeepSeek also released six smaller models distilled from R1 using Qwen and Llama foundations, widening the range of hardware that can experiment with the approach.

Open weights allow researchers to inspect outputs, adapt the model and operate it without sending every prompt to a hosted provider. They do not disclose the complete training data or make answers inherently reliable. Reported mathematics and coding benchmarks are promising, but independent tests must examine accuracy, safety, cost and language coverage. R1 gives the field a substantial new artifact to reproduce and challenge rather than only an interface to query.