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embeddinggemma-2-ONNX: GPU requirements and price to run | GridPup

Models / embeddinggemma-2

onnx-community/embeddinggemma-2-ONNX

Embeddings (features) · served with ONNX Runtime · ↓ 197.8K downloads a month · View on Hugging Face

Weights: 1.2 GB
GPU memory needed: about 2.8 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/audio_encoder.onnx1.2 GB · 2.8 GB GPU float16onnx/audio_encoder_fp16.onnx590 MB · 1.9 GB GPU 4-bitonnx/audio_encoder_q4.onnx190 MB · 1.3 GB GPU 4-bit, float16onnx/audio_encoder_q4f16.onnx170 MB · 1.3 GB GPU 8-bitonnx/audio_encoder_quantized.onnx340 MB · 1.5 GB GPU full precisiononnx/model.onnx1.1 GB · 2.6 GB GPU float16onnx/model_fp16.onnx540 MB · 1.8 GB GPU 4-bitonnx/model_q4.onnx170 MB · 1.3 GB GPU 4-bit, float16onnx/model_q4f16.onnx160 MB · 1.2 GB GPU 8-bitonnx/model_quantized.onnx310 MB · 1.5 GB GPU full precisiononnx/vision_encoder.onnx670 MB · 2 GB GPU float16onnx/vision_encoder_fp16.onnx340 MB · 1.5 GB GPU 4-bitonnx/vision_encoder_q4.onnx110 MB · 1.2 GB GPU 4-bit, float16onnx/vision_encoder_q4f16.onnx100 MB · 1.1 GB GPU 8-bitonnx/vision_encoder_quantized.onnx200 MB · 1.3 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.

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.