Fact-checking and judgesText analysis

HHEM (Vectara)

A small model that checks whether an AI answer is grounded in the source text or made up. Runs on a CPU and works well as a filter in RAG systems.

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

Developer
Vectara, USA
First release
Oct 2023
Latest release
Jul 2024
Sizes
110M
License
Commercial use allowedApache 2.0 (the open version is HHEM-2.1-Open; the newer HHEM-2.3 is paid only)
Russian
Not supported
Running
On your own serverAlso runs without a GPU
Industries
Customer support, Documents and accounting, Legal
Deploy on your server Hugging Face GitHub

What it does

  • Checking knowledge base chatbot answers for fabrications
  • Quality control of document summaries
  • Comparing language models by their tendency to make errors

Where it is used

Support teams with an AI botLegal and document managementInternal knowledge bases

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
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. HHEM-2.1-Open (без лимита 512 токенов)
  2. HHEM-1.0

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 HHEM (Vectara) be used in a commercial project?

Yes. License: Apache 2.0 (the open version is HHEM-2.1-Open; the newer HHEM-2.3 is paid only). It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does HHEM (Vectara) need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does HHEM (Vectara) support Russian?

No. The model card lists its languages and Russian is not among them.

Where can I download HHEM (Vectara) and what does it cost?

The HHEM (Vectara) 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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DetailsModeration and safetyGranite GuardianIBM · USACommercial use allowed

IBM judge models: they catch harm, profanity and jailbreak attempts, and in RAG and agents check whether an answer is grounded in the documents. You can state your own rule in words.

Details

Source: huggingface.co/vectara/hallucination_evaluation_model. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.