TextComputer-use agents

LLaDA

Diffusion language models: text is written in blocks and then refined rather than word by word, which speeds up generation. LLaDA2.2 can edit what it has written and targets agents. LLaDA-Image is a separate product.

Developer
Renmin University of China (GSAI) and Ant Group (inclusionAI), China
First release
Feb 2025
Latest release
Sep 2026
Sizes
8B – 100B (MoE)
License
Commercial use allowedLLaDA 8B and 1.5: MIT; LLaDA-MoE and LLaDA2.x: Apache 2.0
Russian
Not stated
Ready-made builds
GGUF
Running
On your own serverNeeds a GPU
Industries
Software development, Science and research
Deploy on your server Hugging Face GitHub

What it does

  • Fast generation of code and text
  • Agent scenarios with long context
  • Research into alternatives to standard LLMs

Where it is used

DevelopmentResearch groups

Hardware requirements

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

Versions

  1. LLaDA2.2-mini
  2. LLaDA2.2-flash
  3. LLaDA2.1 mini и flash
  4. LLaDA2.0 mini (16B) и flash (100B)
  5. LLaDA-MoE 7B-A1B
  6. LLaDA 1.5
  7. LLaDA 8B

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. 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 LLaDA be used in a commercial project?

Yes. License: LLaDA 8B and 1.5: MIT; LLaDA-MoE and LLaDA2.x: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does LLaDA 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 LLaDA 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 LLaDA and what does it cost?

The LLaDA 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.

Similar models

TextLing / RingAnt Group (inclusionAI) · ChinaCommercial use allowed

An Ant Group family: Ling for standard models, Ring for reasoning ones. There are trillion-parameter flagships and the efficient Ling-3.0-tiny, which needs only 1.3 billion active parameters.

DetailsTextQwenAlibaba · ChinaCommercial use with conditions

A family of language models with strong Russian language support, from small versions for a laptop to a flagship on par with commercial APIs.

DetailsTextSeed-OSSByteDance · ChinaCommercial use allowed

An open ByteDance 36B model with up to 512K tokens of context and an adjustable thinking budget. Fits on a single powerful GPU.

Details

Source: huggingface.co/inclusionAI/LLaDA2.2-mini. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.