What GPU do I need to run Audio8/Audio8-TTS-Preview-0.1b?

170M parameters, published in BF16. View on Hugging Face

170M
Parameters
BF16
Native precision
ArkttsModel
Architecture
text-to-speech
Pipeline

Audio8-TTS-Preview-0.1b is published by Audio8 on Hugging Face, with 6,733 downloads and 198 likes to date. It's a ArkttsModel model built for text-to-speech, 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)
BF160.3 GB0.4 GBRTX 5060 Ti1$0.110/hr
FP8 (quantized)0.2 GB0.2 GBRTX 5060 Ti1$0.110/hr
INT4 (quantized)0.1 GB0.1 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 Audio8-TTS-Preview-0.1b 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.

Audio8-TTS-Preview-0.1b: common questions

How much VRAM does Audio8-TTS-Preview-0.1b need?

0.4 GB at BF16, 0.2 GB at FP8 (quantized), 0.1 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 0.3 GB of weights plus inference overhead is the whole requirement.

How many copies of Audio8-TTS-Preview-0.1b fit on one RTX 5060 Ti?

42, by VRAM alone. That card carries 16.0 GB and one copy needs 0.4 GB at BF16, on a live rate of $0.110/hr for the whole card. Throughput is not modelled here, so 42 copies is not 42 times the requests served.

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

More Audio8 models

All 2 Audio8 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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