What GPU do I need to run OpenGVLab/InternVL2_5-4B?
3.7B parameters, published in BF16. View on Hugging Face
Set up InternVL2_5-4BInternVL2_5-4B is published by OpenGVLab on Hugging Face, with 230,912 downloads and 58 likes to date. It's a InternVLChatModel model built for image-text-to-text, 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 | 6.9 GB | 8.3 GB | RTX 4070 Super | 1 | $0.121/hr |
| FP8 (quantized) | 3.5 GB | 4.1 GB | RTX 4070 Super | 1 | $0.121/hr |
| INT4 (quantized) | 1.7 GB | 2.1 GB | RTX 4070 Super | 1 | $0.121/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 InternVL2_5-4B at its published (BF16) precision: 1× RTX 4070 Super, at $0.121/hr per GPU ($0.121/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
InternVL2_5-4B: common questions
Does InternVL2_5-4B fit on a 12 GB GPU?
Yes. At BF16 it needs 8.3 GB of VRAM, so a 12 GB card holds it with 3.7 GB to spare. An 8 GB card is not enough for it at BF16.
What is the least VRAM InternVL2_5-4B can run in?
2.1 GB, at INT4 (quantized), which fits a 6 GB card, against 8.3 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 InternVL2 models
- InternVL2-2B (2.2B, BF16)
- InternVL2-1B (938M, BF16)
- InternVL2-26B (25.5B, BF16)
Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.
