What GPU do I need to run z-lab/LLaMA3.1-8B-Instruct-DFlash-UltraChat?
1.0B parameters, published in BF16. View on Hugging Face
LLaMA3.1-8B-Instruct-DFlash-UltraChat is published by z-lab on Hugging Face, with 13,193 downloads and 3 likes to date. It's a DFlashDraftModel model built for text-generation, published natively in BF16.
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 LLaMA3.1-8B-Instruct-DFlash-UltraChat at its published (BF16) precision: 1× RTX 3070 on simplepod, at $0.050/hr per GPU ($0.050/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 z-lab models
- Qwen3.6-35B-A3B-DFlash (386M, BF16)
- Qwen3.8-27B-DFlash2 (1.9B, BF16)
- Qwen3.6-27B-DFlash (1.7B, BF16)
- Qwen3.5-9B-DFlash (1.3B, BF16)
- Qwen3-8B-DFlash-b16 (1.0B, BF16)
- gemma-4-26B-A4B-it-DFlash (430M, BF16)
