Qdrant Cloud Inference lets you generate embeddings for text, image, and sparse data directly inside your managed Qdrant cluster. Better latency, lower egress costs, simpler architecture, and no external APIs required.

We built FastEmbed to make local embedding fast and easy. But as customers moved to production, they needed something more scalable and integrated. Qdrant Cloud Inference brings that next step; embedding models that run inside your cluster with no external services. It supports dense, sparse, and image data, and runs on AWS, Azure, and GCP (US only for now). You can embed, store, and search with a single API call. Lower latency, fewer moving parts, and reduced egress costs.

Amazing work Qdrant team and congratulations on the launch @daniel_azoulai2 ,@andre_zayarni and @generall. This will help in managing embeddings and working with existing Qdrant more easier.

Amazing! I'm excited to see how you use this and how it helps your projects. Please let us know!

The best one yet, PrompX uses Qdrant for hybrid search and embedding.

Thanks Qdrant.

We evaluated a bunch of vector DBs—and Qdrant stood out for its blazing speed, filtering, and hybrid search. It's the unsung hero that lets our AI agents recall and reason across docs, CRMs, and conversations in milliseconds.

Vector database enabling fast semantic search and retrieval of coding memories.

We use Qdrant to store and search high-dimensional vector embeddings of malicious patterns, phishing URLs, and threat indicators. This empowers Truelink to compare new threats against known vectors instantly using semantic AI.

Vector database enabling fast semantic search and retrieval of coding memories.

Qdrant Cloud Inference

Unify embeddings and vector search across modalities

Unify embeddings and vector search across modalities

Qdrant Cloud Inference

Unify embeddings and vector search across modalities

Unify embeddings and vector search across modalities

Do you use Qdrant Cloud Inference?

Do you use Qdrant Cloud Inference?