Dedicated model · Available as managed deployment
BAAI's BGE-M3 is a multilingual embedding model with dense, sparse and multi-vector retrieval in one, an 8,192-token input window, under MIT. Available as a managed deployment: validated on AxForge hardware and deployed on a DGX Spark for your traffic only, as an OpenAI-compatible endpoint on hardware only you use, hosted in the EU.
Why BGE-M3
| Three retrieval modes in one | Dense vectors, sparse lexical weights and ColBERT-style multi-vectors from a single model, for 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 by BAAI |
|---|---|
| Modalities | Text → vector (embeddings) |
| Context window | 8,194 tokens |
| Released | 2024-01 |
| Popularity | 37.1M downloads / month on HuggingFace |
| Licence | Open weights (MIT); commercial use permitted |
| Availability | Available as managed deployment, operated by AxForge on hardware reserved for you |
| Hardware | NVIDIA DGX Spark (GB10, 128 GB unified memory), owned and operated by AxForge |
| Region | Málaga, Spain (eu-es-1) |
| Pricing | Hardware from €0.85/hour, rental term: Hour, week, month or year. Managed service quoted per deployment. Request deployment and we confirm both in writing. |
We publish only numbers we measure ourselves, and we haven't benchmarked this model on our nodes yet. For quality benchmarks, see the model card in the catalogue and the official card on HuggingFace.
Deployment
| System | A dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory), reserved for you |
|---|---|
| Commercial model | Hour, week, month or year. Hardware from €0.85/hour, managed service quoted per deployment |
| Endpoint | OpenAI-compatible /v1 on your own machine, only your traffic |
| Location | Hosted in the EU: Málaga, Spain (eu-es-1) |
| Data handling | Zero prompt retention, same policy as the serverless API |
The model is validated on AxForge hardware and deployed on your system. After deployment, your endpoint speaks the OpenAI API with the model name you receive with the deployment.
Data & privacy
Prompts and completions are processed in memory in the EU, not written to disk, not logged, not retained, and never used to train anything. We keep only request metadata (token counts, timestamps, status) for billing and operations. The full policy is at axforge.ai/privacy.
FAQ
Not on the serverless API. It is available as a managed deployment: validated on AxForge hardware and deployed on a 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.
We publish only numbers we measure ourselves, and we haven't benchmarked this model on our nodes yet. For quality benchmarks, see the official model card.
A dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory) rented by the hour, week, month or year, running BGE-M3 behind an OpenAI-compatible endpoint on your own machine, hosted in the EU with zero prompt retention.
Hardware from €0.85/hour, by the hour, week, month or year; the managed service is quoted per deployment. Request deployment and we confirm both in writing.
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