Embeddings · served with vLLM · ↓ 17.4K downloads a month · View on Hugging Face
ai-sage/Giga-Embeddings-instruct-10B-A1.8B-0826 needs about 26.6 GB of GPU memory. It runs on one RTX A6000 from $0.54/h right now; best value: RTX 5090 at $0.68/h.
Weights
21 GB
GPU memory needed
about 26.6 GB
Model allows
262,144 tokens
Memory · disk
35.4 GB · 64 GB
Architecture
DeepseekV3BidirectionalModel
Licence
mit
Hardware and deploy
$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 Giga-Embeddings-instruct-10B-A1.8B-0826 need?
About 26.6 GB: 20.95 GB of weights and the runtime's own memory.
What is the cheapest GPU to run Giga-Embeddings-instruct-10B-A1.8B-0826?
Right now one RTX A6000 at $0.54 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 Giga-Embeddings-instruct-10B-A1.8B-0826 run on an RTX 4090?
Not on one: it needs about 26.6 GB and an RTX 4090 has 24 GB. An RTX 5090 (32 GB) is enough.
How do I deploy Giga-Embeddings-instruct-10B-A1.8B-0826 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.
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.