What GPU do I need to run deepseek-ai/DeepSeek-V3.1-Base?
684.5B parameters, published in F8_E4M3. View on Hugging Face
DeepSeek-V3.1-Base is published by deepseek-ai on Hugging Face, with 34,112 downloads and 1,010 likes to date. It's a DeepseekV3ForCausalLM model built for text-generation, published natively in F8_E4M3.
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 DeepSeek-V3.1-Base at its published (F8_E4M3) precision: 8× RTX PRO 6000 on runpod, at $1.64/hr per GPU ($13.12/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 deepseek-ai models
- DeepSeek-OCR (3.3B, BF16)
- DeepSeek-R1 (684.5B, F8_E4M3)
- DeepSeek-V3.2 (685.4B, F8_E4M3)
- DeepSeek-V3-0324 (684.5B, F8_E4M3)
- DeepSeek-V3 (684.5B, F8_E4M3)
- DeepSeek-OCR-2 (3.4B, BF16)
