Dedicated model · Available as managed deployment
BAAI's BGE-M3 — a multilingual embedding model with dense, sparse and multi-vector retrieval in one, an 8,192-token input window, under MIT. Validated on AxForge hardware and deployed on a dedicated DGX Spark for your traffic only — an OpenAI-compatible endpoint on hardware only you use, operated by AxForge in the EU.
Why AxForge
| Three retrieval modes in one | Dense vectors, sparse lexical weights and ColBERT-style multi-vectors from a single model — hybrid search without three models. |
|---|---|
| 100+ languages, 8k tokens | Long documents and multilingual corpora embedded in one pass. |
| MIT licence | Permissive — commercial use, no licence conversation. |
Specifications
| Model | BGE-M3 — BAAI |
|---|---|
| Modalities | Text → vector (embeddings) |
| Context window | 8,194 tokens |
| Licence | Open weights — mit; commercial use permitted |
| Hardware | NVIDIA DGX Spark (GB10, 128 GB unified memory) — owned and operated by AxForge |
| Rental term | Hour, week, month or year |
| Hardware pricing | €0.69/hour on demand · €0.66/hour by the week · €0.62/hour by the month · €0.55/hour by the year, excl. VAT |
| Managed service | Quoted per deployment |
| Region | Málaga, Spain (eu-es-1) |
Full details, benchmarks and FAQ on the BGE-M3 page. Prices exclude VAT.
How it works
| 1 | Request deployment — describe your traffic, context needs and rental term. |
|---|---|
| 2 | You receive the configuration, hardware rental and managed-service price in writing before anything is billed. |
| 3 | AxForge deploys BGE-M3 on a dedicated DGX Spark reserved for you. |
| 4 | Point your OpenAI SDK at your own endpoint with the model name you receive. |
| 5 | Adjust the term — hour, week, month or year — as your workload settles. |
Request deployment or sign in to start.
FAQ
Not on the serverless API — it is available as a managed deployment: validated on AxForge hardware and deployed on a dedicated DGX Spark for your traffic only. The serverless API serves Qwen3.8 27B.
Qwen3 Embedding is what AxForge serves per token; BGE-M3 is the choice for a dedicated deployment when you want hybrid (dense + sparse) retrieval or its multilingual coverage.
A dedicated DGX Spark embedding your documents behind an OpenAI-compatible /v1/embeddings endpoint — millions of chunks a day, in the EU.
AxForge publishes only numbers it measures itself, and has not benchmarked this model on its nodes yet. For quality benchmarks, see the official model card.
Hardware by the hour, week, month or year; the managed service is quoted per deployment — both confirmed in writing before anything is billed.