The other awesome thing about R1: they've released Llama3- and Qwen2.5-based distilled versions of R1 ranging from 1.5B to 70B parameters which are supported in the latest version of llama.cpp. These show great performance, with the 35B and 70B specifically performing as good or better than o1-mini in a number of areas. https://github.com/deepseek-ai/DeepSeek-R1 More on reddit.com

I have tried it on "Azure AI foundry" through their serverless API with a paid subscription · It takes 80s to answer a basic question that was answered in 7s by OpenAI gpt-4o. And there was not that much thought process, it was just super slow to output each token More on news.ycombinator.com

What is the price for Deepseek R1 deployed? API calls in 1mil tokens fro output and input? I cant find it in prices/calculator? thanks! More on learn.microsoft.com

Nebius trains on your data. It's right there in their TOS: b. By default, the Company collects and processes Input and Output for the purpose of training Models solely for Speculative Decoding. Speculative Decoding is a Draft-then-Verify decoding paradigm that utilizes smaller models to efficiently draft multiple output tokens and then verifies all these tokens in parallel using the target Model to speed up inference. Speculative Decoding improves inference speed without sacrificing model quality. If you do not want Us to collect Your Input and Output to train Models for Speculative Decoding, You can opt out any time by indicating Your preference through the opt-out mechanism provided in the onboarding form or by submitting a request to the Company’s support team via email [email protected] . Please note that in some cases this may limit the ability of our Service to better address Your specific use case. You might not care about training draft models. But they still have all your data and can change their minds in the future. More on reddit.com