# CogView4

CogView4 is THUDM's 6B-parameter diffusion-transformer text-to-image model. It uses a **GLM** language
model as its text encoder and a 16-channel VAE. InvokeAI supports the base **CogView4-6B** checkpoint.
CogView4 support is basic: plain generation and Canvas image editing work, but the adapters and
controls that other families offer are not available.

## License

CogView4-6B is released under **Apache 2.0**, which allows commercial use. The download is not gated.

This is a summary, not legal advice. Read the full license on the model's HuggingFace page before using a model commercially.

## Hardware

The Diffusers download is about **31 GB**, including the GLM text encoder and VAE. See
[System Requirements](/start-here/system-requirements/) for general guidance, and the
[Low VRAM guide](/configuration/optimization/low-vram-mode/) if you run out of memory.

## Installing

Install **CogView4** from the Model Manager's starter models. Its source is `THUDM/CogView4-6B`. This
family has no starter bundle.

CogView4 installs in **Diffusers** format only, as a single folder that contains the transformer, GLM
text encoder, tokenizer and VAE. No other models are needed, and the components cannot be replaced
individually. Single-file and GGUF CogView4 models are not recognized.

## Generation settings

When you select CogView4, InvokeAI applies the defaults from the model's reference example:

| Setting    | Default     |
| ---------- | ----------- |
| Steps      | 50          |
| CFG Scale  | 3.5         |
| Resolution | 1024 × 1024 |

- **CFG Scale** applies true classifier-free guidance.
- **Width and height** must be multiples of **32**.
- **Negative prompts** are supported and always used.
- **No scheduler choice.** CogView4 uses its own flow-matching sampler, so the Scheduler control is
  hidden.
- **Prompt weighting** (Compel syntax) does not apply to CogView4. See
  [Prompt Syntax](/users-guide/image-generation/advanced-prompt-syntax/#attention-weighting). The GLM encoder reads up to **1024
  tokens**, so long, descriptive prompts are fine.

## Canvas

On the Canvas, CogView4 supports text-to-image, image-to-image, inpainting and outpainting. LoRAs,
ControlNet, reference images, regional guidance and PiD decoding are **not** available for CogView4.

## Workflow editor

The CogView4 nodes are **Main Model - CogView4**, **Prompt - CogView4**, **Denoise - CogView4**,
**Image to Latents - CogView4** and **Latents to Image - CogView4**. Each prompt needs its own **Prompt -
CogView4** node. Connect them to the denoise node's positive and negative conditioning inputs. Both are
required.