Text analysis

ReaderLM (Jina)

Small models that turn raw web page HTML into clean Markdown or JSON. Handy for preparing websites for a knowledge base. Non-commercial license only.

Developer
Jina AI, Germany
First release
Sep 2024
Latest release
Jan 2025
Sizes
0.5B – 1.5B
License
Non-commercial onlyCC-BY-NC 4.0
Russian
Supported
Ready-made builds
GGUF
Running
Available in OllamaAlso runs without a GPU
Industries
Software development, Documents and accounting, Marketing and content
Deploy on your server Hugging Face

What it does

  • Cleaning website pages for a knowledge base
  • Extracting data from pages into JSON
  • Preparing texts for RAG

Where it is used

IT and software developmentMarketing and competitor analysisInternal 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. ReaderLM-v2 (1.5B, 29 языков)
  2. reader-lm 0.5b и 1.5b

How to run it

With Ollama — the fastest wayInstall Ollama on your computer or server and find the model in its library by name. Good enough to try the model on your own tasks in one evening.Find it in the Ollama library
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. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can ReaderLM (Jina) be used in a commercial project?

No. License: CC-BY-NC 4.0. A commercial product needs a different model or a separate agreement with the rights holder.

What hardware does ReaderLM (Jina) 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 ReaderLM (Jina) support Russian?

Yes, Russian is listed on the model card.

Where can I download ReaderLM (Jina) and what does it cost?

The ReaderLM (Jina) 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/jinaai/ReaderLM-v2. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.