AxForge offering · Request
Meta's Llama 3.1 family of 8B, 70B and 405B instruction-tuned models with a 128k-token context and multilingual training, the most deployed open LLM family in production. 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 default open model | Llama 3.1 is what most teams standardise on: mature tooling, broad framework support and years of community fine-tunes and evaluations. |
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| 8B and 70B on one machine | The 8B runs comfortably on a dedicated DGX Spark; the 70B fits the same machine in a quantized build. 405B is a multi-GPU deployment. |
| Licence handled | For an agreed deployment, subject to availability: The Llama 3.1 community licence allows commercial use under its conditions; AxForge deploys under it and tells you exactly what applies to you. |
Specifications
| Model | Llama 3.1 by meta-llama |
|---|---|
| Modalities | Text |
| Sizes | 8.0B, 70.6B, 405.9B |
| Licence | Open, with conditions (llama3.1); AxForge deploys under it and tells you what applies |
| 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) |
Llama 3.1 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.
8B natively and 70B in a quantized build, both with the 128k context; 405B needs a multi-GPU system, which AxForge would scope with you. Any deployment depends on confirmed availability, configuration, licence and price.
Under the Llama 3.1 community licence, yes for almost every business. The licence carries conditions, and AxForge would walk you through them before deployment. Any deployment depends on confirmed availability, configuration, licence and price.
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.