KayaTechAI/BGE-M3-0.56B-Fine-Tuned-Telecom-Technical-Documents-Retrieval-Embedding-Generalization-Baseline: GPU requirements and price to run | GridPup
Embeddings · served with Text Embeddings Inference · ↓ 151 downloads a month · View on Hugging Face
KayaTechAI/BGE-M3-0.56B-Fine-Tuned-Telecom-Technical-Documents-Retrieval-Embedding-Generalization-Baseline needs about 3 GB of GPU memory. It runs on one GTX 1660 SUPER from $0.06/h right now; best value: RTX 5070 Ti at $0.19/h.
Weights
1.1 GB
GPU memory needed
about 3 GB
Model allows
8,194 tokens
Memory · disk
8 GB · 22 GB
Architecture
XLMRobertaModel
Licence
apache-2.0
Hardware and deploy
Deploying ONNX models from the catalog is coming soon. Today, download the files from Hugging Face and upload them in Inference.
Questions
How much GPU memory does BGE-M3-0.56B-Fine-Tuned-Telecom-Technical-Documents-Retrieval-Embedding-Generalization-Baseline need?
About 3 GB: 1.14 GB of weights and the runtime's own memory.
What is the cheapest GPU to run BGE-M3-0.56B-Fine-Tuned-Telecom-Technical-Documents-Retrieval-Embedding-Generalization-Baseline?
Right now one GTX 1660 SUPER at $0.06 an hour; RTX 5070 Ti at $0.19 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can BGE-M3-0.56B-Fine-Tuned-Telecom-Technical-Documents-Retrieval-Embedding-Generalization-Baseline run on an RTX 4090?
Yes: it needs about 3 GB and an RTX 4090 has 24 GB.
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.