What GPU do I need to run OBLITERATUS/gemma-4-E4B-it-OBLITERATED?
8.0B parameters, published in F16. View on Hugging Face
gemma-4-E4B-it-OBLITERATED is published by OBLITERATUS on Hugging Face, with 39,237 downloads and 767 likes to date. It's a Gemma4ForConditionalGeneration model built for text-generation, published natively in F16.
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 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run gemma-4-E4B-it-OBLITERATED at its published (F16) precision: 1× P40 on akash, at $0.137/hr per GPU ($0.137/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 OBLITERATUS models
- Qwen3.8-27B-OBLITERATED (27.8B, BF16)
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- Gemma-4-12B-OBLITERATED (12.0B, BF16)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
- Qwen3-8B (8.2B, BF16)
