#140 · Primary category: Inference & Local Deploy
infinity
Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali
Project last updated:03/24/26
GitHub Stars
2.9K
Forks
198
Contributors
35
License
MIT
Why we included this project
If you're building a retrieval or RAG pipeline and want embeddings served on your own hardware, Infinity is a REST server that handles the inference plumbing for you. It serves text-embedding and reranking models, plus multimodal ones like CLIP and ColPali, behind an OpenAI-compatible API, so swapping it in for a hosted embedding endpoint is fairly painless. The engine runs on PyTorch, ONNX/TensorRT, and CTranslate2 backends, letting you match the backend to your hardware, from NVIDIA or AMD GPUs down to CPU-only machines. Dynamic batching and tokenization in dedicated worker threads keep throughput high under load, and one process can serve several models at once. For teams that need low-latency self-hosted embeddings, rerankers, or vision-language vectors, this is a practical drop-in option.
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