What GPU do I need to run Featherless-Chat-Models/llama2-13b-chat-hf?
13.0B parameters, published in F16. View on Hugging Face
Set up llama2-13b-chat-hfllama2-13b-chat-hf is published by Featherless-Chat-Models on Hugging Face, with 22,837 downloads and 0 likes to date. It's a LlamaForCausalLM model built for text-generation, published natively in F16.
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) |
|---|---|---|---|---|---|
| FP16 | 24.2 GB | 29.1 GB | V100 | 1 | $0.187/hr |
| cheaper alt. | V100 | 2 | $0.176/hr | ||
| FP8 (quantized) | 12.1 GB | 14.5 GB | RTX 5060 Ti | 1 | $0.188/hr |
| INT4 (quantized) | 6.1 GB | 7.3 GB | RTX 3060 | 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 llama2-13b-chat-hf at its published (F16) precision: 1× V100, at $0.187/hr per GPU ($0.187/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
llama2-13b-chat-hf: common questions
Does llama2-13b-chat-hf fit on a 32 GB GPU?
Yes. At FP16 it needs 29.1 GB of VRAM, so a 32 GB card holds it with 2.9 GB to spare. A 24 GB card is not enough for it at FP16.
What is the least VRAM llama2-13b-chat-hf can run in?
7.3 GB, at INT4 (quantized), which fits an 8 GB card, against 29.1 GB at FP16. 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 llama2-13b-chat-hf lower the GPU bill?
Yes. At FP16 the cheapest live fit is one V100 at $0.187/hr. At INT4 (quantized) it drops to one RTX 3060 at $0.110/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More Llama 2 models
- Llama-2-13b-chat-hf (13.0B, F16)
- Llama-2-13b-hf (13.0B, F16)
- HarmBench-Llama-2-13b-cls (13.0B, BF16)
- Llama-2-7b-hf (6.7B, F16)
- Llama-2-7b-chat-hf (6.7B, F16)
Related reading: V100 pricing and specs, and The best GPUs for AI, ranked.
