Show HN: 1.32 Petaflops hardware for local prototyping (autonomous.ai)

5 points by brody_slade_ai ↗ HN
I’ve been working on Vanta, a scalable AI hardware solution powered by 2–8 NVIDIA RTX 4090s, delivering up to 1.32 petaflops FP32 in a compact form factor.

It’s built for startups, developers and researchers to prototype, fine-tune and run models up to 70B parameters locally. So you can own your computer instead of renting.

- A 2-GPU setup costs $9k and breaks even in 9 months vs. cloud rental at $0.69/hr (ex: RunPod).

- The 8-GPU at $40k saves $12k in year one compared to $48k in cloud costs.

This can handle different AI framework: TensorFlow, PyTorch, ONNX, CUDA-optimized libraries, VLLM, SGLANG, llama.cpp...

I can get it built in a day and shipped out quick. Let me know what you think!

3 comments

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(comment deleted)
I’m not really sure about this but would love to undestand how can this run multiple different workloads at once? How fast?
I'm sure it looks better in person, but the images kind of make it look like a wicker basket. Totally superficial take, I know.