“For a voice agent company, they want to control their own model so that it can make sure the model actually responds by the required time. So the customer, when they're on the phone, they can ensure the agent is responding according to a SLA. And this sometimes is only you can do with your controlled intelligence because you know the whole hardware you're running and the whole system you're monitoring versus signing up for relying on your critical infrastructure with a proprietary API where they might go down anytime.”
Source→“vLLM is an inference engine. That means its job is to turn available GPUs into a running endpoint for intelligence... we support more than a thousand model architectures up to today.”
Source→“Yang as a co-founder, he has always been thinking about open source and where how do you support open source better. And then now with experience from Databricks and AnyScale and even Arena...”
Source→“A lot of our developers are retreating from using Claude 5 because you have a two-hour job and you trigger the red line which is false positive and then you have to lose all of your work. So a lot of our developers are using Kimi K3 today because it's similar quality and it has a guardrail that makes sense to us.”
Source→“Users are able to get the maximum benefit out of this model when they enable fast mode... getting up to 400 and 500 tokens per second, because it is really a big step change... especially when developers are interacting with the model, they can see, oh, I can really just get my task done faster here.”
Source→“If it's a large company, it's very easy to bring their original biases or positions, making it hard to integrate the community. Other large companies won't follow them... A startup that is the project's founding team, having gone through wind and rain together with the community — their convening power, their neutrality and fairness, everyone recognizes.”
Source→“Like a16z — they provided a grant to the vLLM project back in 2023. In 2024, Sequoia and Zhenfund also donated money to us in the form of an open-source community. When we finally told them we had decided to start a company, they were quite straightforwardly ready — 'My money is already prepared. You've finally decided.'”
Source→“Ion Stoica (Yang Stoica) — UC Berkeley professor, co-founder of Databricks, founder of the RISELab/SkyLab lineage, vLLM advisor and co-founder of Infract.”
Source→“Like a16z — they provided a grant to the vLLM project back in 2023.”
Source→“We asked him: if you don't co-found with us, you'll earn a lot of money, but ten years later if the vLLM project fails, will you be happy or not? ... The hardest person to recruit to the founding team — had offers from XAI, Thinking Machine Labs, and Google DeepMind.”
Source→“Simon had also spent some time at Character AI, so he tried through Character AI to help support vLLM's development. ... He had already participated in some startups. He had experience from Character AI.”
Source→“Roger has also been working with us on the vLLM project for many years.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.