DeepSeek also said it distilled the reasoning steps used in R1-0528 into Alibaba’s Qwen3 8B Base model. That process created a new, smaller model that surpassed Qwen3’s performance by more ...

For instance, in the AIME 2025 test, DeepSeek-R1-0528’s accuracy jumped from 70% to 87.5%, indicating deeper reasoning processes that now average 23,000 tokens per question compared to 12,000 in ...

China's free-for-all AI models, developed by firms like DeepSeek and Alibaba, present a viable alternative to US closed-source systems July 9, 2024, may be remembered as a day of humiliation for China ...

DeepSeek's updated R1 AI model is more censored than the AI lab's previously releases, one test found — in particular when it comes to criticism of the Chinese government.

DeepSeek released an updated version of their popular R1 reasoning model (version 0528) with – according to the company – increased benchmark performance, reduced hallucinations, and native support ...

The new version, DeepSeek-R1-0528, has a whopping 685 billion parameters, meaning it can perform on par with competitors such as o3 from OpenAI and Gemini 2.5 Pro from Google.

DeepSeek-R1-0528-Qwen3-8B also nearly matches Microsoft’s recently released Phi 4 reasoning plus model on another math skills test, HMMT. So-called distilled models like DeepSeek-R1-0528-Qwen3 ...

A new version of DeepSeek is DeepSeek-R1-0528. DeepSeek R1 has significantly improved its depth of reasoning and inference capabilities by leveraging increased computational resources and introducing ...

Most of the tech industry and investors greeted the launch with a giant shrug. This is a pretty stark contrast to early 2025 when DeepSeek's R1 model freaked everyone out.

DeepSeek R1T2 – 200% faster than R1-0528 & 20% faster than R1,” wrote Vaibhav (VB) Srivastav, a senior leader at Hugging Face, on X. “Significantly better than R1 on GPQA & AIME 24, made via ...

DeepSeek also introduced a distilled version of R1-0528 using Alibaba's Qwen3 8B model. This is an example of a lightweight model that is less capable but also requires less computing power.

When DeepSeek-R1 launched, the entire industry was taken aback by the research paper that claimed the highly sophisticated model was trained at a fraction of the cost of OpenAI's o1.