AI open models ready to use. Private inference with flat rate. Own your models with privacy, zero logs and EU compliance
Community & builders at nan.builders
Today we’re featured in @LaVanguardia talking about AI, data sovereignty, and why the EU is competing in one of the most important races of our time and how at @helmcode we’re working to help meet that challenge.
👀 @Revolut has reduced its AI coding costs by 90% by self-hosting open models.
And I think their story is worth paying attention to.
At @aiDotEngineer NYC, David Abitbol shared how Revolut went from being skeptical about the ROI of closed models to making open-weight models a
A coding agent can send 100,000 tokens in a single request. Conversation history, files, tool outputs… And it keeps sending much of that context with every new request.
Cristian Gutiérrez (@crstiax) has been digging into what happens when you serve these workloads with vLLM,
🐳 How DeepSeek’s inference engine works.
A deep dive into how experts spread across GPUs, a scheduler that keeps them busy, and how they cut prefill compute nearly in half.
This is a technical piece about how to serve inference for a MoE
We like predictable AI bills.
Not because we're obsessed with saving money, but because we've seen how much easier it is to build when you know what something is going to cost.
That's why we offer flat-rate access to the open models we operate.
Use the models, test your ideas,
