What GPU do I need to run openbmb/MiniCPM-V-4.6-Thinking?
1.3B parameters, published in BF16. View on Hugging Face
MiniCPM-V-4.6-Thinking is published by openbmb on Hugging Face, with 94,009 downloads and 29 likes to date. It's a MiniCPMV4_6ForConditionalGeneration model built for image-text-to-text, 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 MiniCPM-V-4.6-Thinking 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 openbmb models
- MiniCPM5-1B (1.1B, BF16)
- MiniCPM-V-4.6 (1.3B, BF16)
- MiniCPM-V-4_5 (8.7B, BF16)
- MiniCPM4.1-8B (8.2B, BF16)
- MiniCPM4-0.5B (434M, BF16)
- MiniCPM4-8B (8.2B, BF16)
