Hunyuan Image 2.1 in ComfyUI | High-Res Text-to-Image Workflow

Next-gen 2.1 model for crisp, sharp, ultra-clear AI visuals fast.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning — you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises — run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout — useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON — the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense — you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations — First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

This workflow helps you create ultra-clear 2K visuals with advanced prompt control. Built for text-to-image generation, it enhances clarity, detail, and composition while remaining highly efficient. You can generate complex scenes, characters, and stylized creations with rich accuracy. Multilingual prompts and a refinement stage ensure sharper outputs. Its design lets you produce polished, professional-grade results without heavy computational cost. Perfect for designers seeking fast, precise, and visually striking creations.

Important nodes:

Key nodes in Comfyui Hunyuan Image 2.1 workflow

DualCLIPLoader (#33)

This node loads the pair of text encoders that Hunyuan Image 2.1 expects. Keep the model type set for Hunyuan, and select Qwen2.5‑VL‑7B and ByT5 Small to combine strong scene understanding with glyph‑aware text handling. If you iterate on style, adjust the positive prompt in tandem with guidance rather than swapping encoders.

CLIPTextEncode (#6 and #7)

These nodes turn your positive and negative prompts into conditioning. Keep the positive prompt concise up top, then add lens, lighting, and style cues. Use the negative prompt to suppress artifacts like extra limbs or noisy text; trim it if you find it overly restrictive for your concept.

EmptyHunyuanImageLatent (#29)

Defines the working resolution and batch. The default 2048×2048 aligns with Hunyuan Image 2.1’s native 2K capability. For other aspect ratios, choose model‑friendly width and height pairs and consider increasing steps slightly if you move far from square.

KSampler (#3)

Drives the denoising process with Hunyuan Image 2.1. Increase steps when you need finer micro‑detail, decrease for quick drafts. Raise guidance for stronger prompt adherence but watch for over‑saturation or rigidity; lower it for more natural variation. Switch seeds to explore compositions without changing your prompt.

UNETLoader (#37)

Loads the Hunyuan Image 2.1 UNet. The included FP8 checkpoint keeps memory usage modest for 2K output. If you have ample VRAM and want maximum headroom for aggressive settings, consider a higher‑precision variant of the same model from the official releases.

VAELoader (#34) and VAEDecode (#8)

These nodes must match the Hunyuan Image 2.1 release to decode correctly. The model’s high‑compression VAE is key to fast 2K generation; pairing the correct VAE avoids color shifts and blocky textures. If you change the base model, always update the VAE accordingly.

Notes

Hunyuan Image 2.1 in ComfyUI | High-Res Text-to-Image Workflow — see RunComfy page for the latest node requirements.