When DeepSeek released R1 in January 2025, it sent a shockwave through the AI industry that briefly wiped $600 billion from Nvidia’s market cap. The claim was extraordinary: a reasoning model that matched OpenAI’s o1 on key benchmarks, trained at roughly 5% of the compute cost. We spent three weeks testing those claims.
The Reasoning Capability
On mathematics, formal logic, and complex coding tasks, DeepSeek R1 is genuinely impressive. Chain-of-thought reasoning is not just a headline feature — it is visible in the output, which shows the model’s step-by-step working before arriving at an answer. This transparency makes it easier to catch errors and understand the model’s approach.
Coding Performance
We tested R1 on a range of coding tasks: bug identification in Python, algorithm implementation, SQL query optimisation, and React component generation. Across these categories, performance was competitive with GPT-4o and in some cases superior — particularly on algorithmic problem-solving where the chain-of-thought approach proves most useful.
The Privacy Question
The elephant in the room is data handling. DeepSeek is a Chinese company subject to Chinese law. For enterprise use cases involving sensitive data, the cloud-hosted version raises legitimate concerns that the GPT-4-equivalent performance does not override. The self-hosted open-source version removes this concern entirely for technically capable teams.
DeepSeek R1 Review: The Open-Source AI That Shook Silicon Valley
DeepSeek R1 is the most important open-source AI release since Llama 2. For coding, mathematics, and reasoning tasks, it genuinely competes with paid frontier models. The privacy implications of the Chinese-hosted version require attention.
