Building everyone's favorite AI infrastructure platform @modal

Joined February 2013
675 Photos and videos
One way to think about @modal in the limit is that we're an aggregator of compute on a global scale and resource manager for that. Basically a very large global computer.
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My cat is celebrating America’s 250th birthday in the most American way: taking risks
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A bit funny how FTX continues to make money from all the weird holdings. They bought a cube of tungsten for $200k in 2021 and tungsten prices are up 10x since then.
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It should be more widely discussed how annoying it is that “Tier 1” means top notch for almost everything except for data centers where it has the opposite meaning
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Erik Bernhardsson reposted
Huge congrats to @modal on Modal Auto Endpoints! 🎉 Owning your inference means owning the code that runs it, and we love seeing that philosophy in action🫡Honored that SGLang powers part of the stack, alongside the work on DFlash speculative decoding 🧡
It is not too late to _actually_ own your inference. Introducing: Modal Auto Endpoints.
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Managed private LLM endpoints, now available for everyone in @modal. Deploy in a few clicks with the UI or a few keystrokes with our CLI. The coolest thing is that these are not black boxes – customers have full access to the code underneath.
It is not too late to _actually_ own your inference. Introducing: Modal Auto Endpoints.
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At the same time, open source LLM inference is moving super fast – with amazing projects like vLLM, SGLang, FA4, etc. We're actively contributing to those because we think everyone benefits from moving the frontier.
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This is why we're taking a different approach with LLM inference. We want customers to have full control over the serving code. When you're running Modal Auto Endpoints, you run the best open source models with the best open source engines, and you have full access to the code.
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Modal is about having the best building blocks and it's easy to forget in the era of the cloud that they are actual physical objects. Luckily I was able to tour the blocks factory the other day.
“Let me give you a tour. Isn’t this place so cool!?!” dear god pls don’t ask me what anything costs
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If you want to use LLMs in production for serious stuff, you should probably use open source models
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Erik Bernhardsson reposted
Speculation Is All You Need. In this blog post, we announce the co-release (w/ Z Lab) of six more state-of-the-art DFlash speculators for @Alibaba_Qwen 3.x. Over 1k output tps for 3.5 122B-A10B on a B200. Read the blog for why we're all-in on spec dec. modal.com/blog/spec-is-all-u…
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Running 100k sandboxes is a hard scaling problem that's not for everyone – @modal is very excited to be one of a small set of providers that can handle this. In fact, @modal was the only one to nail every single iteration of this test leading up to the final results.
🚨 Benchmark Friday 🚨 After weeks of work from us and the participants, today we are excited to release the results of the 2026 100k Scale Invitational. Over the next hour we'll be releasing each set of results. Huge shoutout to @namespacelabs for powering our benchmarks!
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What's our secret? That this is business as usual for us, and has been for a long time. We have many customers running 100k or even 1M sandboxes with us on a regular basis. Large RL runs for instance. Looking forward to the 1M sandbox challenge – we are ready any time!
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Want to set your agents loose on Microsoft Word (or Minesweeper, Notepad, Diablo 4, or whatever?) Your prayers have been answered! github.com/modal-projects/wi…
on the day of modal's series c announcement i am ... getting microsoft word to run in a modal sandbox
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Our sandbox team has been on a crusade against every millisecond of latency and it's paying off. More cool results coming very soon!
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67% now x.com/jolandgraf/status/2065…
There’s like 6-7 NYC infra founders I occasionally get drinks with and ~50% of them just got acquired: - @graphite - @astral_sh - @StainlessAPI Congrats!! 🍻
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I have had a weird theory for years that Uber fits their ETA model using mean absolute error regression instead of ordinary least squares. Since wait-times have a long right tail, this will cause a bias that underestimates mean wait times (median < mean).
Standard experience booking an Uber “5 minutes away” I order it “Finding your driver…” “Pickup in 7 minutes” I open my timer 9 minutes and 21 seconds later, it arrives This is so tedious and I am tired of being deceived at the margin
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