What GPU do I need to run thinkingmachines/Inkling-Small?

266.0B parameters, published in BF16. View on Hugging Face

266.0B
Parameters
BF16
Native precision
InklingForConditionalGeneration
Architecture
image-text-to-text
Pipeline

Inkling-Small is published by thinkingmachines on Hugging Face, with 184,510 downloads and 392 likes to date. It's a InklingForConditionalGeneration 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.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
BF16495.4 GB594.5 GBRTX PRO 60007$9.63/hr
FP8 (quantized)247.7 GB297.2 GBRTX 40907$3.39/hr
INT4 (quantized)123.8 GB148.6 GBRTX A50007$1.23/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 Inkling-Small at its published (BF16) precision: 7× RTX PRO 6000, at $1.38/hr per GPU ($9.63/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Inkling-Small: common questions

Can Inkling-Small run on a single GPU?

No. At BF16 it needs 594.5 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 95.0 GB RTX PRO 6000, and it takes 7 of them.

How many GPUs do I need to run Inkling-Small?

7 at BF16. It needs 594.5 GB of VRAM and the cheapest capable live offer is a 95.0 GB RTX PRO 6000, so 7 of them come to $9.63/hr in total.

Does quantizing Inkling-Small lower the GPU bill?

Yes. At BF16 the cheapest live fit is 7 RTX PRO 6000 cards at $9.63/hr. At INT4 (quantized) it drops to 7 RTX A5000 cards at $1.23/hr, provided a quantized checkpoint exists for it.

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

More thinkingmachines models

All 2 thinkingmachines models: VRAM and GPU requirements

Related reading: RTX PRO 6000 pricing and specs, The NVIDIA Inception program, explained, Google Colab alternatives for dedicated GPU access, Free GPU credits for students and researchers, and RunPod volume disk vs. network volume, compared.

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