sgl-project--sglang/docs_new/cookbook/diffusion/Ideogram/Ideogram4.mdx

---
title: Ideogram 4
metatags:
    description: "Deploy Ideogram 4 with SGLang Diffusion for high-aesthetic text-to-image generation."
---

## 1. Model introduction

[Ideogram 4](https://huggingface.co/ideogram-ai/ideogram-4-nf4) is Ideogram's text-to-image diffusion model. SGLang Diffusion supports the official NF4 checkpoint, the official FP8 checkpoint, and the Comfy-Org NVFP4 transformer checkpoint.

Compared with previous open-source image models, Ideogram 4 provides a significant aesthetic lift, with stronger composition, more polished visual style, and better typography-aware generation.

| Variant | Hugging Face model ID | Notes |
| --- | --- | --- |
| NF4 | `ideogram-ai/ideogram-4-nf4` | Official bitsandbytes NF4 checkpoint. Use this path first for low-memory deployment. |
| FP8 | `ideogram-ai/ideogram-4-fp8` | Official FP8 checkpoint. |
| NVFP4 | `Comfy-Org/Ideogram-4` | Comfy-Org NVFP4 transformer weights. SGLang loads non-transformer components from `ideogram-ai/ideogram-4-fp8`. |

## 2. Prerequisites

- NVIDIA CUDA GPU.
- SGLang installed with diffusion dependencies.
- `bitsandbytes>=0.46.1` for the NF4 checkpoint.
- `HF_TOKEN` with access to the Ideogram 4 gated repositories.

## 3. Serve the model

NF4:

```bash Command
HF_TOKEN=$HF_TOKEN sglang serve \
  --model-path ideogram-ai/ideogram-4-nf4 \
  --num-gpus 1 \
  --performance-mode auto \
  --port 30010
```

FP8:

```bash Command
HF_TOKEN=$HF_TOKEN sglang serve \
  --model-path ideogram-ai/ideogram-4-fp8 \
  --num-gpus 1 \
  --performance-mode auto \
  --port 30010
```

Comfy-Org NVFP4:

```bash Command
HF_TOKEN=$HF_TOKEN sglang serve \
  --model-path Comfy-Org/Ideogram-4 \
  --num-gpus 1 \
  --performance-mode auto \
  --port 30010
```

Use B200 or another Blackwell GPU for NVFP4.

## 4. Generate an image

```python Example
import base64
from openai import OpenAI

client = OpenAI(api_key="EMPTY", base_url="http://localhost:30010/v1")

response = client.images.generate(
    model="ideogram-ai/ideogram-4-nf4",
    prompt="A cinematic poster of a quiet bookstore at dusk with elegant hand-lettered signage",
    size="1024x1024",
    n=1,
    response_format="b64_json",
    extra_body={"preset": "V4_QUALITY_48", "seed": 0},
)

image_bytes = base64.b64decode(response.data[0].b64_json)
with open("ideogram4.png", "wb") as f:
    f.write(image_bytes)
```

Ideogram 4 presets are `V4_DEFAULT_20`, `V4_QUALITY_48`, and `V4_TURBO_12`. The preset controls both `num_inference_steps` and guidance, so do not set those fields directly.