What GPU do I need to run arcee-ai/Trinity-Nano-Preview?

6.1B parameters, published in BF16. View on Hugging Face

6.1B
Parameters
BF16
Native precision
AfmoeForCausalLM
Architecture
text-generation
Pipeline

Trinity-Nano-Preview is published by arcee-ai on Hugging Face, with 16,172 downloads and 78 likes to date. It's a AfmoeForCausalLM 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.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
BF1611.4 GB13.7 GBRTX 5060 Ti1$0.110/hr
FP8 (quantized)5.7 GB6.8 GBRTX 5060 Ti1$0.110/hr
INT4 (quantized)2.8 GB3.4 GBRTX 5060 Ti1$0.110/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 Trinity-Nano-Preview at its published (BF16) precision: 1× RTX 5060 Ti, at $0.110/hr per GPU ($0.110/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Trinity-Nano-Preview: common questions

Does Trinity-Nano-Preview fit on a 16 GB GPU?

Yes. At BF16 it needs 13.7 GB of VRAM, so a 16 GB card holds it with 2.3 GB to spare. A 12 GB card is not enough for it at BF16.

What is the least VRAM Trinity-Nano-Preview can run in?

3.4 GB, at INT4 (quantized), which fits a 6 GB card, against 13.7 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.

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

More Trinity models

All 3 Trinity 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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