# huggingface/text-embeddings-inference

A blazing fast inference solution for text embeddings models

Repository: https://github.com/huggingface/text-embeddings-inference
Canonical: https://ross.abutalabs.com/products/text-embeddings-inference
Homepage: https://huggingface.co/docs/text-embeddings-inference/quick_tour
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: ai, embeddings, huggingface, llm, ml
Last push: 2026-07-24T13:47:50+00:00

## Health v2 (maintenance only)
Score: 84/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 94, release rhythm 76, longevity 75
- inputs: {"age_days": 1055, "days_push": 40, "days_rel": 163, "gap_med": 26, "n_releases_24m": 16}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5028, forks 426 (observed 2026-08-28T04:09:04.938000+00:00)

## What it is
Text Embeddings Inference (TEI) is a Rust-based toolkit from Hugging Face for deploying and serving open-source text embedding, re-ranker, and sequence classification models at high performance. It supports dynamic batching, Flash Attention, Safetensors/ONNX weight loading, and production features like Prometheus metrics and OpenTelemetry tracing.

## Use cases
- serve embedding models for a RAG pipeline
- host a fast embeddings API endpoint for semantic search
- deploy re-ranker models behind an HTTP or gRPC API
- run embeddings inference on GPU, CPU, or Apple Silicon locally
- self-host embeddings instead of paying per-token API costs
- batch-embed large document collections efficiently

## When to choose
- you need production-grade, low-latency serving of supported embedding models like BGE, GTE, E5, Qwen3, or Nomic
- you want small Docker images, fast boot times, and serverless-friendly deployment
- you need dynamic batching, tracing, and metrics out of the box
- you want to serve private or gated Hugging Face models on your own infrastructure

## When to avoid
- you need to serve embedding model architectures not on the supported list
- you only need occasional embeddings and prefer a hosted API without infrastructure
- you need text generation inference rather than embeddings (use TGI instead)
- you want a Python-native stack for experimentation rather than a Rust server

## Facets
- artifact type: service
- maturity: active
- function: llm-inference, http-server, machine-learning, rag
- domain: machine-learning, large-language-models, artificial-intelligence, developer-tools
- platform: rust, self-hosted
- tags: embeddings, huggingface, rerankers, sequence-classification, flash-attention, safetensors, onnx, grpc, prometheus, open-telemetry, retrieval-augmented-generation, docker, linux, macos, gpu, web-server

## Member repositories
- huggingface/text-embeddings-inference (main) score 84

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:04.938000+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:17:28.280292+00:00, confidence not recorded.
  - readme: https://github.com/huggingface/text-embeddings-inference (fetched 2026-08-28T04:09:04.938000+00:00, sha a752b8732804)
  - homepage: https://huggingface.co/docs/text-embeddings-inference/quick_tour (fetched 2026-08-29T08:58:10.727783+00:00, sha c8d318cfef15)
  - site_page: https://huggingface.co/docs (fetched 2026-08-29T08:58:10.736976+00:00, sha bdec26667b98)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/index (fetched 2026-08-29T08:58:10.740972+00:00, sha 258947bb5df4)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/supported_models (fetched 2026-08-29T08:58:10.742966+00:00, sha a299924ec629)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/local_cpu (fetched 2026-08-29T08:58:10.744784+00:00, sha f8fc18d6d5d6)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/local_metal (fetched 2026-08-29T08:58:10.746503+00:00, sha 3060e91b11c1)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/local_gpu (fetched 2026-08-29T08:58:10.748037+00:00, sha f95a39ec6f64)
  - site_page: https://huggingface.co/docs/text-embeddings-inference/private_models (fetched 2026-08-29T08:58:10.749522+00:00, sha 4e7c87089927)
  - site_page: https://huggingface.co/pricing (fetched 2026-08-29T08:58:10.738786+00:00, sha de6b7a178be5)
- Data as of 2026-08-30T08:39:29.467469+00:00.