Overview
Infinity running on the GPU AMI
Infinity 0.0.77 serving embeddings on an NVIDIA T4: health open, /embeddings gated by a per-instance password, model served on the GPU.
This is a repackaged open source software product wherein additional charges apply for cloudimg support services.
Overview Infinity is a high-throughput, low-latency server for serving text embedding and reranking models. It serves models such as BGE, GTE, E5, Sentence Transformers and mixedbread with dynamic batching and an OpenAI-compatible embeddings API, so existing OpenAI SDK code works unchanged. This image delivers Infinity fully installed and configured as a system service on an NVIDIA GPU instance, so a private, self-hosted embeddings endpoint is running within minutes of launch. The current release available is Infinity 0.0.77.
GPU Accelerated This image is built and shipped for NVIDIA GPU instances (g4dn, g5, g6 families). The NVIDIA datacenter driver is preinstalled and verified on real hardware during the build, and Infinity runs on the GPU for fast, batched embedding generation out of the box.
Application Stack Infinity runs in a dedicated Python virtual environment as an unprivileged service account on the loopback address, with an nginx reverse proxy fronting it on port 80. A systemd service starts the server on boot and restarts it on failure. The embedding model lives on a dedicated, independently resizable storage volume kept separate from the operating system disk, and a small open-weights model is pre-downloaded so the API responds immediately.
Secure By Default Access is gated by HTTP Basic Authentication at the nginx reverse proxy. This image generates a fresh password, unique to your instance, on its first boot and writes it to a root only file. The public health endpoint stays open for load balancers; the embedding and reranking endpoints require the password. No shared or default credentials ship in the image.
Ready To Use Generate embeddings from the OpenAI SDK or the native API, and feed them into a vector database such as Weaviate or Chroma for retrieval augmented generation. Serve a different embedding or reranking model by editing the model name in the service environment file.
cloudimg Support 24/7 technical support by email and chat. Help with Infinity deployment, model selection, GPU sizing, batching and throughput tuning, the OpenAI-compatible API, TLS termination and scaling.
Use Cases The embeddings backend of a private, self-hosted RAG pipeline in your own VPC. High-throughput batch embedding of documents. Reranking for search and retrieval. A drop-in OpenAI-compatible embeddings endpoint for teams with data residency or compliance requirements.
All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.
Highlights
- Infinity, the high-throughput GPU server for text embeddings and reranking with an OpenAI-compatible API, preinstalled as a systemd service behind an nginx reverse proxy on port 80, ready to use with no manual setup
- GPU accelerated: NVIDIA datacenter driver preinstalled and verified on real hardware, with embeddings generated on the GPU out of the box on g4dn, g5 and g6 instances
- Secure by default: HTTP Basic Authentication with a unique password generated for every instance on first boot and stored in a root only file, plus 24/7 cloudimg support
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Dimension | Description | Cost/hour |
|---|---|---|
g4dn.xlarge Recommended | g4dn.xlarge | $0.12 |
t2.micro | t2.micro instance type | $0.04 |
t3.micro | t3.micro instance type | $0.04 |
m5a.8xlarge | m5a.8xlarge instance type | $0.24 |
t3.2xlarge | t3.2xlarge instance type | $0.24 |
g6.48xlarge | g6.48xlarge instance type | $0.24 |
r5dn.metal | r5dn.metal instance type | $0.24 |
r6id.2xlarge | r6id.2xlarge instance type | $0.24 |
f2.12xlarge | f2.12xlarge instance type | $0.24 |
r5n.xlarge | r5n.xlarge instance type | $0.12 |
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Refunds available on request.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Initial release of Infinity 0.0.77 for GPU-accelerated, OpenAI-compatible text embeddings and reranking.
Additional details
Usage instructions
Launch on an NVIDIA GPU instance type (g4dn.xlarge or larger). Connect via SSH on port 22 as the default login user for your operating system variant (the user guide lists it per variant; on Ubuntu it is 'ubuntu'). Infinity is served by nginx on port 80. Retrieve the generated password with: sudo cat /root/infinity-credentials.txt. The health endpoint is open at http://<instance-public-ip>/health; everything else is gated by HTTP Basic Authentication (user 'admin' + the password). Generate embeddings: curl -u admin:<password> http://<instance-public-ip>/embeddings -H 'Content-Type: application/json' -d '{"model":"BAAI/bge-base-en-v1.5","input":["your text"]}'. The endpoint is OpenAI-compatible. The server runs on loopback 127.0.0.1:7997 and is managed with systemctl (infinity.service, nginx.service). Serve a different model by editing MODEL in /etc/infinity/infinity.env and restarting infinity.service. The user guide covers the OpenAI SDK, feeding a vector database, reranking, model selection and enabling HTTPS.
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Support
Vendor support
cloudimg provides 24/7 technical support for this product by email and live chat. Our engineers help with deployment, configuration, updates, performance tuning and troubleshooting; critical issues receive a one hour average response. Contact support@cloudimg.co.uk .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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