What GPU do I need to run HuggingFaceTB/SmolLM3-3B-Base?
3.1B parameters, published in BF16. View on Hugging Face
Set up SmolLM3-3B-BaseSmolLM3-3B-Base is published by HuggingFaceTB on Hugging Face, with 761,202 downloads and 172 likes to date. It's a SmolLM3ForCausalLM 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 | 5.7 GB | 6.9 GB | RTX 3070 | 1 | $0.088/hr |
| FP8 (quantized) | 2.9 GB | 3.4 GB | RTX 4070 | 1 | $0.121/hr |
| INT4 (quantized) | 1.4 GB | 1.7 GB | RTX 3070 | 1 | $0.088/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 SmolLM3-3B-Base at its published (BF16) precision: 1× RTX 3070, at $0.088/hr per GPU ($0.088/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
SmolLM3-3B-Base: common questions
Does SmolLM3-3B-Base fit on a 8 GB GPU?
Yes. At BF16 it needs 6.9 GB of VRAM, so an 8 GB card holds it with 1.1 GB to spare. A 6 GB card is not enough for it at BF16.
What is the least VRAM SmolLM3-3B-Base can run in?
1.7 GB, at INT4 (quantized), which fits a 6 GB card, against 6.9 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 HuggingFaceTB models
- SmolLM2-135M (135M, BF16)
- SmolVLM2-500M-Video-Instruct (507M, F32)
- SmolLM2-135M-Instruct (135M, BF16)
- SmolLM3-3B (3.1B, BF16)
- SmolVLM-256M-Instruct (256M, BF16)
- SmolLM2-360M (362M, BF16)
Related reading: RTX 3070 pricing and specs, The NVIDIA Inception program, explained, Google Colab alternatives for dedicated GPU access, Free GPU credits for students and researchers, and RunPod volume disk vs. network volume, compared.
