What GPU do I need to run nvidia/parakeet-ctc-1.1b?
1.1B parameters, published in F32. View on Hugging Face
parakeet-ctc-1.1b is published by nvidia on Hugging Face, with 1,849,810 downloads and 58 likes to date. It's a ParakeetForCTC model built for automatic-speech-recognition, published natively in F32.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for activations and allocator fragmentation. Speech models don't build the same growing KV-cache a text model does — memory scales primarily with input audio length. 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 parakeet-ctc-1.1b at its published (F32) precision: 1× P4 on akash, at $0.032/hr per GPU ($0.032/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 nvidia models
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- nemotron-3.5-asr-streaming-0.6b (638M, F32)
- NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 (31.6B, BF16)
- NVIDIA-Nemotron-3-Super-120B-A12B-BF16 (123.6B, BF16)
- parakeet-tdt-0.6b-v3 (627M, F32)
- NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 (31.6B, F8_E4M3)
