What GPU do I need to run ibm-granite/granite-speech-3.3-2b?
3.0B parameters, published in BF16. View on Hugging Face
Set up granite-speech-3.3-2bgranite-speech-3.3-2b is published by ibm-granite on Hugging Face, with 152,648 downloads and 55 likes to date. It's a GraniteSpeechForConditionalGeneration model built for automatic-speech-recognition, published natively in BF16.
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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 5.6 GB | 6.7 GB | RTX 5060 Ti | 1 | $0.110/hr |
| FP8 (quantized) | 2.8 GB | 3.4 GB | RTX 5060 Ti | 1 | $0.110/hr |
| INT4 (quantized) | 1.4 GB | 1.7 GB | RTX 5060 Ti | 1 | $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 granite-speech-3.3-2b 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.
granite-speech-3.3-2b: common questions
Does granite-speech-3.3-2b fit on a 8 GB GPU?
Yes. At BF16 it needs 6.7 GB of VRAM, so an 8 GB card holds it with 1.3 GB to spare. A 6 GB card is not enough for it at BF16.
How many copies of granite-speech-3.3-2b fit on one RTX 5060 Ti?
2, by VRAM alone. That card carries 16.0 GB and one copy needs 6.7 GB at BF16, on a live rate of $0.110/hr for the whole card. Throughput is not modelled here, so 2 copies is not 2 times the requests served.
What is the least VRAM granite-speech-3.3-2b can run in?
1.7 GB, at INT4 (quantized), which fits a 6 GB card, against 6.7 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 Granite 3 models
- granite-speech-3.2-8b (8.5B, BF16)
- granite-speech-3.3-8b (8.6B, BF16)
- granite-3.3-2b-instruct (2.5B, BF16)
- granite-3.1-2b-instruct (2.5B, BF16)
- granite-3.0-1b-a400m-base (1.4B, F32)
Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.
