AxForge offering · Request
The sentence-transformers workhorse: a 23M-parameter embedding model producing 384-dimensional vectors, the most downloaded embedding model in the world, under Apache-2.0. Validated on AxForge hardware with a dedicated DGX Spark deployment option for your traffic only, subject to confirmed availability, configuration and licence, as an OpenAI-compatible endpoint on hardware only you use, operated by AxForge in the EU.
Currently request-only. Add your request to the public forum; this is not a booking or a promised launch.
Why AxForge
| The most used embedding model | Hundreds of millions of downloads: the default in tutorials, vector databases and RAG starters everywhere. |
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| Tiny and fast | 23M parameters and 384 dimensions: thousands of embeddings per second on a single machine, cheap to store and search. |
| Apache-2.0 | Permissive: commercial use, no licence conversation. |
Specifications
| Model | all-MiniLM-L6-v2 by sentence-transformers |
|---|---|
| Modalities | Text → vector (embeddings) |
| Sizes | 23M |
| Context window | 512 tokens |
| Licence | Open weights (apache-2.0); 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 | €1.19/hour on demand · €0.95/hour by the week · €0.91/hour by the month · €0.85/hour by the year |
| Managed service | Quoted per deployment |
| Region | Málaga, Spain (eu-es-1) |
all-MiniLM-L6-v2 catalogue reference: specifications and requirements. List prices in EUR.
How it works
| 1 | Add a public request describing your workload, context needs and preferred rental term. A request does not reserve hardware or promise a deployment. |
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| 2 | If AxForge can offer a deployment, agree the configuration, hardware rental, licence and managed-service price in writing before anything is billed. |
| 3 | Only after availability and terms are confirmed would AxForge provision the agreed dedicated system and model build. |
| 4 | After provisioning, point your OpenAI SDK at your own endpoint with the model name you receive. |
| 5 | After provisioning, adjust the term (hour, week, month or year) as your workload settles. |
Request model or sign in to start.
FAQ
This page describes the managed deployment option. Availability, the model build, hardware, licence and price must be agreed before a deployment can be offered. A public request does not provision or reserve a machine. Check the console for the current serverless offering list.
English text, short passages and high volume where speed and cost matter more than the last few points of retrieval quality; for multilingual or long inputs look at BGE-M3 or Qwen3 Embedding.
Yes, a dedicated DGX Spark runs a small embedding model next to an LLM behind one OpenAI-compatible endpoint.
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.
For a deployment agreed after availability is confirmed: Hardware by the hour, week, month or year; the managed service is quoted per deployment. Both are confirmed in writing before anything is billed.