What GPU do I need to run PerceptronAI/Isaac-0.5?
35.7B parameters, published in F32. View on Hugging Face
Set up Isaac-0.5Isaac-0.5 is published by PerceptronAI on Hugging Face, with 312 downloads and 30 likes to date. It's a Isaac05ForConditionalGeneration model built for robotics, published natively in F32.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run Isaac-0.5 at its published (F32) precision: 5× V100 on simplepod, at $0.170/hr per GPU ($0.850/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More PerceptronAI models
- bert-base-uncased (110M, F32)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
- Qwen3-8B (8.2B, BF16)
- Qwen3.6-35B-A3B-FP8 (36.0B, F8_E4M3)
- Qwen3.5-9B (9.7B, BF16)
