Fact-checking and judges

ArmoRM (RLHFlow)

An answer scorer that returns a breakdown across several attributes rather than a single overall score. The scorer itself makes mistakes and does not replace manual review on important tasks.

The last open version came out in May 2024. The family has not been updated for a long time: the model still works, but do not expect fixes or new sizes.

Developer
RLHFlow, USA
First release
May 2024
Latest release
May 2024
Sizes
8B
License
Commercial use with conditionsLlama 3 Community License — base model restrictions apply
Russian
Not stated
Running
On your own serverNeeds a GPU
Industries
Software development, Science and research, Customer support
Deploy on your server Hugging Face GitHub

What it does

  • Choosing the best of several candidate answers
  • Preparing data for model fine-tuning
  • Scoring assistant answers across several attributes

Where it is used

IT and software developmentResearch and scienceCustomer support

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. ArmoRM-Llama3-8B-v0.1

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can ArmoRM (RLHFlow) be used in a commercial project?

With conditions. License: Llama 3 Community License — base model restrictions apply. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does ArmoRM (RLHFlow) need?

At minimum: One GPU with 16–80 GB — mid-size versions. Without a GPU the model is not practical. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does ArmoRM (RLHFlow) support Russian?

The model card does not list languages, so Russian support cannot be promised — it has to be tested on your own examples.

Where can I download ArmoRM (RLHFlow) and what does it cost?

The ArmoRM (RLHFlow) weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

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Details

Source: huggingface.co/RLHFlow/ArmoRM-Llama3-8B-v0.1. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.