How much GPU memory does multi-qa-distilbert-cos-v1 need?

About 1.4 GB: 0.27 GB of weights and the runtime's own memory.

What is the cheapest GPU to run multi-qa-distilbert-cos-v1?

Right now one GTX 1650 at $0.06 an hour; RTX 5090 at $0.56 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.

Can multi-qa-distilbert-cos-v1 run on an RTX 4090?

Yes: it needs about 1.4 GB and an RTX 4090 has 24 GB.

Models / multi-qa-distilbert-cos

sentence-transformers/multi-qa-distilbert-cos-v1

Embeddings · served with ONNX Runtime · ↓ 30.8K downloads a month · View on Hugging Face

sentence-transformers/multi-qa-distilbert-cos-v1 needs about 1.4 GB of GPU memory. It runs on one GTX 1650 from $0.06/h right now; best value: RTX 5090 at $0.56/h.

Weights: 270 MB
GPU memory needed: about 1.4 GB
Memory · disk: 8 GB · 30 GB
Licence: not stated

Versions

Smaller versions (8-bit, 4-bit) need less GPU memory and answer a little less precisely.

full precisiononnx/model.onnx270 MB · 1.4 GB GPU full precisiononnx/model_O1.onnx270 MB · 1.4 GB GPU full precisiononnx/model_O2.onnx270 MB · 1.4 GB GPU full precisiononnx/model_O3.onnx270 MB · 1.4 GB GPU full precisiononnx/model_O4.onnx130 MB · 1.2 GB GPU 8-bitonnx/model_qint8_arm64.onnx70 MB · 1.1 GB GPU 8-bitonnx/model_qint8_avx512.onnx70 MB · 1.1 GB GPU 8-bitonnx/model_qint8_avx512_vnni.onnx70 MB · 1.1 GB GPU

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 multi-qa-distilbert-cos-v1 need?: About 1.4 GB: 0.27 GB of weights and the runtime's own memory.
What is the cheapest GPU to run multi-qa-distilbert-cos-v1?: Right now one GTX 1650 at $0.06 an hour; RTX 5090 at $0.56 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can multi-qa-distilbert-cos-v1 run on an RTX 4090?: Yes: it needs about 1.4 GB and an RTX 4090 has 24 GB.

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