Text generation · served with vLLM · ↓ 266 downloads a month · View on Hugging Face
anon8231489123/vicuna-13b-GPTQ-4bit-128g needs about 12.4 GB of GPU memory for conversations of up to 2,048 tokens. It runs on one RTX A4000 from $0.11/h right now; best value: RTX 5090 at $0.69/h.
Weights
7.5 GB
GPU memory needed
about 12.4 GB
Conversation length
2,048 tokens
Model allows
2,048 tokens
Memory · disk
16 GB · 49 GB
Architecture
LlamaForCausalLM
Licence
not stated
Hardware and deploy
$0.69/h from your balance while it runs, billed by the hour; stop it from its page. GridPup rents the machine, which downloads the model from Hugging Face (usually ready in 10 to 15 minutes), and gives you an https address, keys and a Playground.
Questions
How much GPU memory does vicuna-13b-GPTQ-4bit-128g need?
About 12.4 GB for conversations of up to 2,048 tokens: 7.45 GB of weights, the cache for one full-length conversation and the runtime's own memory.
What is the cheapest GPU to run vicuna-13b-GPTQ-4bit-128g?
Right now one RTX A4000 at $0.11 an hour; RTX 5090 at $0.69 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can vicuna-13b-GPTQ-4bit-128g run on an RTX 4090?
Yes: it needs about 12.4 GB and an RTX 4090 has 24 GB.
How do I deploy vicuna-13b-GPTQ-4bit-128g as an API?
Pick a machine on its GridPup page and press Deploy: GridPup rents the GPU, downloads the model from Hugging Face and serves it at an https address with keys and OpenAI's chat API, billed by the hour.
Prices are per hour for the whole machine and its disk, right now. Speed is Vast's DLPerf score of the machine, relative to the cheapest. Best value: the most speed per dollar. Only machines with a Vast reliability above 95% that download at 400 Mbit/s or more are offered: the machine fetches the model itself.