What GPU do I need to run deepseek-community/deepseek-vl-1.3b-chat?
2.0B parameters, published in F16. View on Hugging Face
deepseek-vl-1.3b-chat is published by deepseek-community on Hugging Face, with 22,211 downloads and 3 likes to date. It's a DeepseekVLForConditionalGeneration model built for image-text-to-text, 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 deepseek-vl-1.3b-chat at its published (F16) precision: 1× P4 on akash, at $0.032/hr per GPU ($0.032/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-community models
- Janus-Pro-1B (2.1B, BF16)
- deepseek-vl-7b-chat (7.3B, F16)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
- Qwen3-8B (8.2B, BF16)
- Qwen3.6-35B-A3B-FP8 (36.0B, F8_E4M3)
