What GPU do I need to run deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B?
1.8B parameters, published in BF16. View on Hugging Face
DeepSeek-R1-Distill-Qwen-1.5B is published by deepseek-ai on Hugging Face, with 599,903 downloads and 1,548 likes to date. It's a Qwen2ForCausalLM 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 DeepSeek-R1-Distill-Qwen-1.5B 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 deepseek-ai models
- DeepSeek-R1 (684.5B, F8_E4M3)
- DeepSeek-R1-0528-Qwen3-8B (8.2B, BF16)
- DeepSeek-V2-Lite-Chat (15.7B, BF16)
- DeepSeek-V3.2 (685.4B, F8_E4M3)
- DeepSeek-V3 (684.5B, F8_E4M3)
- DeepSeek-V3-0324 (684.5B, F8_E4M3)
