How much GPU memory does jina-reranker-v1-turbo-en need?

About 1.2 GB: 0.15 GB of weights and the runtime's own memory.

What is the cheapest GPU to run jina-reranker-v1-turbo-en?

Right now one GTX 1660 SUPER at $0.07 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 jina-reranker-v1-turbo-en run on an RTX 4090?

Yes: it needs about 1.2 GB and an RTX 4090 has 24 GB.

Models / jina-reranker-v1-turbo-en

jinaai/jina-reranker-v1-turbo-en

Reranking · served with ONNX Runtime · ↓ 23.7K downloads a month · View on Hugging Face

jinaai/jina-reranker-v1-turbo-en needs about 1.2 GB of GPU memory. It runs on one GTX 1660 SUPER from $0.07/h right now; best value: RTX 5070 Ti at $0.19/h.

Weights: 150 MB
GPU memory needed: about 1.2 GB
Memory · disk: 8 GB · 30 GB
Licence: apache-2.0

Versions

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

full precisiononnx/model.onnx150 MB · 1.2 GB GPU 4-bit (bnb)onnx/model_bnb4.onnx100 MB · 1.2 GB GPU float16onnx/model_fp16.onnx80 MB · 1.1 GB GPU 8-bitonnx/model_int8.onnx40 MB · 1.1 GB GPU 4-bitonnx/model_q4.onnx100 MB · 1.2 GB GPU 8-bitonnx/model_quantized.onnx40 MB · 1.1 GB GPU 8-bitonnx/model_uint8.onnx40 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 jina-reranker-v1-turbo-en need?: About 1.2 GB: 0.15 GB of weights and the runtime's own memory.
What is the cheapest GPU to run jina-reranker-v1-turbo-en?: Right now one GTX 1660 SUPER at $0.07 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 jina-reranker-v1-turbo-en run on an RTX 4090?: Yes: it needs about 1.2 GB and an RTX 4090 has 24 GB.

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