What GPU do I need to run lightonai/LightOnOCR-1B-1025?

1.2B parameters, published in BF16. View on Hugging Face

1.2B
Parameters
BF16
Native precision
LightOnOCRForConditionalGeneration
Architecture
image-to-text
Pipeline

LightOnOCR-1B-1025 is published by lightonai on Hugging Face, with 93,438 downloads and 256 likes to date. It's a LightOnOCRForConditionalGeneration model built for image-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.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
BF162.2 GB2.6 GBRTX 4070 Super1$0.121/hr
FP8 (quantized)1.1 GB1.3 GBRTX 4070 Super1$0.121/hr
INT4 (quantized)0.5 GB0.6 GBRTX 4070 Super1$0.121/hr

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 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run LightOnOCR-1B-1025 at its published (BF16) precision: 1× RTX 4070 Super, at $0.121/hr per GPU ($0.121/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

LightOnOCR-1B-1025: common questions

How much VRAM does LightOnOCR-1B-1025 need?

2.6 GB at BF16, 1.3 GB at FP8 (quantized), 0.6 GB at INT4 (quantized). All of those sit under 6 GB, the smallest capacity this page reasons about, so VRAM is not what limits where this model runs. The 2.2 GB of weights plus inference overhead is the whole requirement.

How many copies of LightOnOCR-1B-1025 fit on one RTX 4070 Super?

4, by VRAM alone. That card carries 12.0 GB and one copy needs 2.6 GB at BF16, on a live rate of $0.121/hr for the whole card. Throughput is not modelled here, so 4 copies is not 4 times the requests served.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

More lightonai models

All 3 lightonai models: VRAM and GPU requirements

Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.

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