What GPU do I need to run OpenGVLab/InternVL3-78B?
78.4B parameters, published in BF16. View on Hugging Face Full specs & deploy guide
Set up InternVL3-78BInternVL3-78B is published by OpenGVLab on Hugging Face, with 13,741 downloads and 239 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 | 146.0 GB | 175.3 GB | RTX 3090 | 8 | $1.18/hr |
| FP8 (quantized) | 73.0 GB | 87.6 GB | RTX PRO 6000 | 1 | $1.64/hr |
| cheaper alt. | RTX 4070 Super | 8 | $0.880/hr | ||
| INT4 (quantized) | 36.5 GB | 43.8 GB | RTX A6000 | 1 | $0.330/hr |
| cheaper alt. | RTX 3090 | 2 | $0.294/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 InternVL3-78B at its published (BF16) precision: 8× RTX 3090, at $0.147/hr per GPU ($1.18/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
InternVL3-78B: common questions
Can InternVL3-78B run on a single GPU?
No. At BF16 it needs 175.3 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 24.0 GB RTX 3090, and it takes 8 of them.
How many GPUs do I need to run InternVL3-78B?
8 at BF16. It needs 175.3 GB of VRAM and the cheapest capable live offer is a 24.0 GB RTX 3090, so 8 of them come to $1.18/hr in total.
Does quantizing InternVL3-78B lower the GPU bill?
Yes. At BF16 the cheapest live fit is 8 RTX 3090 cards at $1.18/hr. At INT4 (quantized) it drops to one RTX A6000 at $0.330/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More OpenGVLab models
- InternVL2-2B (2.2B, BF16)
- InternVL2-1B (938M, BF16)
- InternVL2_5-4B (3.7B, BF16)
- InternVL3-1B (938M, BF16)
- InternVL2-26B (25.5B, BF16)
- InternVL3-1B-hf (938M, BF16)
