How much GPU memory does elephant-embeddings-v1-text-small need?

About 2.2 GB: 0.61 GB of weights and the runtime's own memory.

What is the cheapest GPU to run elephant-embeddings-v1-text-small?

Right now one RTX 3060 at $0.09 an hour; RTX 5090 at $0.65 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.

Can elephant-embeddings-v1-text-small run on an RTX 4090?

Yes: it needs about 2.2 GB and an RTX 4090 has 24 GB.

How do I deploy elephant-embeddings-v1-text-small 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.

Models / mmbert-32k-yarn / mmbert-32k-yarn ~307M

vllm-sr/elephant-embeddings-v1-text-small

Embeddings · served with vLLM · ↓ 532 downloads a month · View on Hugging Face

vllm-sr/elephant-embeddings-v1-text-small needs about 2.2 GB of GPU memory. It runs on one RTX 3060 from $0.09/h right now; best value: RTX 5090 at $0.65/h.

Weights: 610 MB
GPU memory needed: about 2.2 GB
Model allows: 32,768 tokens
Memory · disk: 8 GB · 41 GB
Architecture: ModernBertModel
Licence: apache-2.0

Versions of mmbert-32k-yarn ~307M

The same model packaged differently: a quantized version needs less GPU memory and runs on a cheaper machine.

Version	Runtime	Weights	GPU memory	Cheapest machine now
mmbert embed 32k 2d matryoshkavllm-sr/mmbert-embed-32k-2d-matryoshka	vLLM	610 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k factcheck classifier mergedvllm-sr/mmbert32k-factcheck-classifier-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k jailbreak detector mergedvllm-sr/mmbert32k-jailbreak-detector-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k intent classifier mergedvllm-sr/mmbert32k-intent-classifier-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k feedback detector mergedvllm-sr/mmbert32k-feedback-detector-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k modality router merged

Hardware and deploy

Endpoint name

$0.65/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 elephant-embeddings-v1-text-small need?: About 2.2 GB: 0.61 GB of weights and the runtime's own memory.
What is the cheapest GPU to run elephant-embeddings-v1-text-small?: Right now one RTX 3060 at $0.09 an hour; RTX 5090 at $0.65 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can elephant-embeddings-v1-text-small run on an RTX 4090?: Yes: it needs about 2.2 GB and an RTX 4090 has 24 GB.
How do I deploy elephant-embeddings-v1-text-small 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.

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vllm-sr/elephant-embeddings-v1-text-small

Embeddings · served with vLLM · ↓ 532 downloads a month · View on Hugging Face

vllm-sr/elephant-embeddings-v1-text-small needs about 2.2 GB of GPU memory. It runs on one RTX 3060 from $0.09/h right now; best value: RTX 5090 at $0.65/h.

Weights

610 MB

GPU memory needed

about 2.2 GB

Model allows

32,768 tokens

Memory · disk

8 GB · 41 GB

Architecture

ModernBertModel

Licence

apache-2.0

Versions of mmbert-32k-yarn ~307M

The same model packaged differently: a quantized version needs less GPU memory and runs on a cheaper machine.

Version	Runtime	Weights	GPU memory	Cheapest machine now
mmbert embed 32k 2d matryoshkavllm-sr/mmbert-embed-32k-2d-matryoshka	vLLM	610 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k factcheck classifier mergedvllm-sr/mmbert32k-factcheck-classifier-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k jailbreak detector mergedvllm-sr/mmbert32k-jailbreak-detector-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k intent classifier mergedvllm-sr/mmbert32k-intent-classifier-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k feedback detector mergedvllm-sr/mmbert32k-feedback-detector-merged	vLLM	620 MB	2.2 GB	$0.09/h RTX 3060
mmbert32k modality router merged

Hardware and deploy

Endpoint name

Questions

How much GPU memory does elephant-embeddings-v1-text-small need?: About 2.2 GB: 0.61 GB of weights and the runtime's own memory.
What is the cheapest GPU to run elephant-embeddings-v1-text-small?: Right now one RTX 3060 at $0.09 an hour; RTX 5090 at $0.65 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can elephant-embeddings-v1-text-small run on an RTX 4090?: Yes: it needs about 2.2 GB and an RTX 4090 has 24 GB.
How do I deploy elephant-embeddings-v1-text-small 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.