@svpino: Serveless, but for models, is here! I stopped renting servers 12 years ago. I mostly moved everything to serverless fun…
Summary
Runpod announces FlashBoot, a serverless approach for AI models that moves idle models to cheaper storage and pages them back to GPU, achieving cold starts under 200ms and cutting costs by 90% compared to traditional clouds.
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Cached at: 07/21/26, 06:41 AM
Serveless, but for models, is here!
I stopped renting servers 12 years ago. I mostly moved everything to serverless functions.
It’s taken a long time for this idea to work with AI models.
The issue was simple: You can start a simple function in milliseconds and scale it down to zero for free, but loading a 20GB model into memory takes quite a bit of time.
And once the model was loaded, forget about shutting it down. You’d better pay for an idle GPU than force the next user to wait while everything reloads.
So you have two options:
- Optimize for low-latency answers and pay for an idle GPU, or
- Optimize for lower costs by scaling to zero and making users wait
Both are bad, and fortunately, we don’t need to choose anymore.
Runpod, the new AI developer cloud, is doing something really clever to solve this problem:
• They don’t shut down idle models • Instead, they move them to somewhere cheaper • When traffic returns, they page the model back to the GPU
This whole process is extremely fast: cold starts drop below 200ms for busy endpoints. They call this technique “FlashBoot”.
On top of that, to deploy your models, they ditched Docker because they don’t want you spending time rebuilding a massive image every time you change a line. Instead, you get a Python function with a line for the GPU you need. You can deploy in seconds with this.
The first run is always the slowest because you’re installing dependencies, but after that, you can run very large models very quickly.
In summary:
- Serverless is here for models
- You don’t need a better GPU
- It’s actually 90% cheaper than 90% of what big clouds give you
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