How much GPU memory does gte_hard need?

About 1.6 GB: 0.07 GB of weights and the runtime's own memory.

What is the cheapest GPU to run gte_hard?

Right now one RTX 3060 at $0.09 an hour; RTX 5090 at $0.68 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.

Can gte_hard run on an RTX 4090?

Yes: it needs about 1.6 GB and an RTX 4090 has 24 GB.

How do I deploy gte_hard 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 embeddings API, billed by the hour.

Models / gte_hard

sucharush/gte_hard

Embeddings · served with vLLM · ↓ 147 downloads a month · View on Hugging Face

sucharush/gte_hard needs about 1.6 GB of GPU memory. It runs on one RTX 3060 from $0.09/h right now; best value: RTX 5090 at $0.68/h.

Weights: 70 MB
GPU memory needed: about 1.6 GB
Model allows: 512 tokens
Memory · disk: 8 GB · 41 GB
Architecture: BertModel
Licence: mit

Hardware and deploy

Endpoint name

$0.68/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 gte_hard need?: About 1.6 GB: 0.07 GB of weights and the runtime's own memory.
What is the cheapest GPU to run gte_hard?: Right now one RTX 3060 at $0.09 an hour; RTX 5090 at $0.68 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can gte_hard run on an RTX 4090?: Yes: it needs about 1.6 GB and an RTX 4090 has 24 GB.
How do I deploy gte_hard 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 embeddings API, billed by the hour.

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