GP @sparkcapital | prev: Partner @pearvc | Founder Flannel (Exit to @Plaid) | Founding team @robinhoodapp | @stanford | tweets are just my personal hottakes
Last week, we launched the RadixArk platform for beta testing and offered $200 credits to SGLang supporters who helped spread the word. A huge thank you to everyone who signed up and reposted. The response has been incredible. We're working hard to get everyone set up, and we appreciate your patience while we work through the queue.
Here's what's coming:
✅ Private Beta access rolling out in waves
✅ $200 in inference credits, pre-linked to your waitlist email
Credits will be available in your account as soon as your platform invite arrives.
Thanks for all the miles. Stay tuned for what comes next!
If you haven’t had an Indian mango and like mangoes, go have a kesar or Alfonso, your mind will be blown
Once you’ve done that, you can expand to others like langda, gulabkhaas etc etc. The sky is the limit
Indian people have perfected mangoes for over 4000 years of selective breeding. With 1k+ known variants, and key commercial ones like alfonso and kesar. The world barely knows about this because these mangoes are not exported. The greatest act of self care by a culture repeatedly colonized is keeping the mangoes for themselves.
Indian people have perfected mangoes for over 4000 years of selective breeding. With 1k+ known variants, and key commercial ones like alfonso and kesar. The world barely knows about this because these mangoes are not exported. The greatest act of self care by a culture repeatedly colonized is keeping the mangoes for themselves.
Real-time interaction requires a real-time engine. ⚡️
Huge congrats to @thinkymachines on this beautiful work on interaction models. AI that listens, watches, and thinks alongside people in real time.
SGLang is honored to be part of the stack, and grateful you upstreamed streaming sessions back to the project for everyone to build on. 🙏
Amazing work from the @sgl_project and @radixark team for their work optimizing DeepSeek V4 inference on B200, B300, and the recent 4x iso-interactivity throughput improvements on GB300 by @ChengWan17! As @elonmusk said, The GB300 is the best AI computer, and software optimizations like this show its true potential!
We've heard the community's feedback. Our intent was to make sure the credits reached the people who supported SGLang along the way, and we couldn't be here without you. We're updating the offer to better reflect that.
RadixArk's platform is open for beta, and we're offering $200 in compute credits to get you started
→ Sign up at https://t.co/MVDvcvkFGX and repost this so we can get you set up.
→ Limited spots, first come first serve. Open through May 13, 2026 (AoE).
→ Credits will be granted after we verify the repost.
(If you already reposted our earlier announcement, that counts too; no need to do it again.)
And if SGLang has been useful in your work, consider giving it a star on GitHub. It's a small gesture that means a lot to the people maintaining it. We're in this together, and we're grateful to be building it with you 🧡
Reliable, efficient, and correct AI infrastructure has been one of the biggest challenges in creating Periodic.
That’s why I’m excited to see RadixArk bring serious capital to open-source infrastructure like SGLang.
When that layer gets stronger in the open, companies like Periodic can move faster, and the new wave of companies can take on ambitious work that used to require a large-scale infra team from day one.
sglang is the best inference framework out there. RadixArk was formed to make it even better and to democratize more of the frontier AI stack. Very happy to support the team in their seed round.
RadixArk has raised $100 million at a $400 million valuation for a software engine and framework that make inference and training more efficient to run. https://t.co/0KVS87MDuh
For years, the most cutting-edge AI infrastructure has been concentrated inside a handful of frontier labs. Advances like test-time reasoning, reinforcement learning, and the rise of high-quality open source models are changing this dynamic.
This shift creates a new opportunity to build foundational infrastructure for operating AI models—an open inference engine combined with flexible systems that give developers full control over how models are trained and deployed. That's exactly what @radixark is building.
We are proud to back founders @ying11231 and @BanghuaZ, who have a long track record of creating and maintaining some of the most widely adopted open source projects in AI. Read more from Accel's @ivzhou and Joshua Fang, including what's next from RadixArk:
https://t.co/LuOzr6l6QN