What GPU do I need to run allenai/Olmo-3-1125-32B?
32.2B parameters, published in BF16. View on Hugging Face
Set up Olmo-3-1125-32BOlmo-3-1125-32B is published by allenai on Hugging Face, with 43,481 downloads and 127 likes to date. It's a Olmo3ForCausalLM 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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 60.0 GB | 72.0 GB | A100 | 1 | $1.21/hr |
| cheaper alt. | RTX 5060 Ti | 5 | $0.550/hr | ||
| FP8 (quantized) | 30.0 GB | 36.0 GB | RTX 4090 | 1 | $0.441/hr |
| cheaper alt. | RTX 5060 Ti | 3 | $0.330/hr | ||
| INT4 (quantized) | 15.0 GB | 18.0 GB | RTX A5000 | 1 | $0.176/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 Olmo-3-1125-32B at its published (BF16) precision: 1× A100, at $1.21/hr per GPU ($1.21/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Olmo-3-1125-32B: common questions
Can Olmo-3-1125-32B run on a single GPU?
Yes, but not on a desktop card. At BF16 it needs 72.0 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest live single-card fit is a 80.0 GB A100 at $1.21/hr.
What is the least VRAM Olmo-3-1125-32B can run in?
18.0 GB, at INT4 (quantized), which fits a 24 GB card, against 72.0 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.
Does quantizing Olmo-3-1125-32B lower the GPU bill?
Yes. At BF16 the cheapest live fit is one A100 at $1.21/hr. At INT4 (quantized) it drops to one RTX A5000 at $0.176/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More Olmo 3 models
- Olmo-3.1-32B-Instruct (32.2B, BF16)
- Olmo-3-7B-Instruct (7.3B, BF16)
- Olmo-3-1025-7B (7.3B, BF16)
- Olmo-3-7B-Think (7.3B, BF16)
- Olmo-3-7B-Instruct-SFT (7.3B, BF16)
Related reading: A100 pricing and specs, and The best GPUs for AI, ranked.
