[diffusion] model: support Ideogram4 NVFP4 (#27379)

docs_new/cookbook/diffusion/Ideogram/Ideogram4.mdx

@@ -0,0 +1,82 @@
+---
+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.

docs_new/cookbook/diffusion/intro.mdx

@@ -23,6 +23,12 @@ Offline models generate each image or video request as a bounded denoising job.
     href="/cookbook/diffusion/FLUX/FLUX"
     img="/cards/logos/flux.png"
   />
+  <Card
+    title="Ideogram 4"
+    mode="card"
+    href="/cookbook/diffusion/Ideogram/Ideogram4"
+    img="/cards/logos/ideogram.png"
+  />
   <Card
     title="Wan"
     mode="card"

docs_new/docs.json

@@ -1114,6 +1114,13 @@
                       "cookbook/diffusion/FLUX/FLUX"
                     ]
                   },
+                  {
+                    "group": "Ideogram",
+                    "tag": "NEW",
+                    "pages": [
+                      "cookbook/diffusion/Ideogram/Ideogram4"
+                    ]
+                  },
                   {
                     "group": "Wan",
                     "pages": [