cashcrown // Models

BGE-M3

embeddings

// 01Measured parameters

A local embeddings model (1024-dim) — runs on your hardware, off the cloud.

// 02Best for

semantic search, RAG, data privacy — the foundation of any AI knowledge base

// 03Where in our routing

This model is not the default primary for any task — we pick it by measurement in the arena when the task profile suits it.

// 04Where it works

// 06What we build with it

ProductBGE-M3 Search RecipeConcierge RAG ServiceDane i SEO

// 07FAQ

What is BGE-M3 best for?

A local embeddings model — turns your knowledge into vectors without sending data to the cloud. Best for: semantic search, RAG, data privacy — the foundation of any AI knowledge base.

Do you use BGE-M3 in production?

It is a local embeddings model — it runs on your hardware and is the foundation of any RAG deployment. Data never leaves for the cloud.

// //Other models

DeepSeek-V4 Mistral Large 3 Qwen3 / Qwen3-Coder GLM-5 / GLM-4.7

← model atlas Build with us

cashcrown // Models

BGE-M3

embeddings

// 01Measured parameters

A local embeddings model (1024-dim) — runs on your hardware, off the cloud.

// 02Best for

semantic search, RAG, data privacy — the foundation of any AI knowledge base

// 03Where in our routing

This model is not the default primary for any task — we pick it by measurement in the arena when the task profile suits it.

// 04Where it works

// 06What we build with it

ProductBGE-M3 Search RecipeConcierge RAG ServiceDane i SEO

// 07FAQ

What is BGE-M3 best for?

A local embeddings model — turns your knowledge into vectors without sending data to the cloud. Best for: semantic search, RAG, data privacy — the foundation of any AI knowledge base.

Do you use BGE-M3 in production?

It is a local embeddings model — it runs on your hardware and is the foundation of any RAG deployment. Data never leaves for the cloud.

// //Other models

DeepSeek-V4 Mistral Large 3 Qwen3 / Qwen3-Coder GLM-5 / GLM-4.7

← model atlas Build with us