HunyuanImage 3.0
Frontierby Tencent
Massive MoE-based text-to-image model from Tencent. 84B total parameters with ~14B active (Mixture of Experts). Autoregressive + diffusion hybrid architecture. Excellent quality and Chinese/English text rendering. One of the largest open image generation models.
VRAM requirements, GPU fit, and setup notes for HunyuanImage 3.0, including 8GB/12GB fit guidance where relevant. Recommended runtimes: ComfyUI and Diffusers support. Best download size: ~157.0 GB at BF16.
- 84B total params (MoE) — only ~14B active per image
- Autoregressive + diffusion hybrid architecture
- Excellent Chinese and English text rendering
- One of the largest open image models
Your hardware
Detecting...
Image Quality Benchmarks
Measured quality metrics for HunyuanImage 3.0 outputs.
How often humans prefer this model's output (0-100%)
Visual quality and composition rating (5-9 scale)
VRAM Requirements by Resolution and Precision
Compare which GPUs can run HunyuanImage 3.0 at different precisions. FP8 uses less memory than FP16 when available, and the grade shows how comfortably each GPU handles the workload.
FP16 (full precision)
| Resolution | VRAM Required | RTX 4090 24GB | RTX 3060 12GB | RTX 4060 8GB | MacBook Pro M4 Pro 24GB |
|---|---|---|---|---|---|
| 512×512 | 177.3 GB | F | F | F | F |
| 768×768 | 177.4 GB | F | F | F | F |
| 1024×1024 | 177.7 GB | F | F | F | F |
Optimization Tips
Turbo / LCM distillation
Use distilled scheduler at 4-8 steps for faster iteration
Run with Python
from diffusers import HunyuanDiTPipeline
import torch
pipe = HunyuanDiTPipeline.from_pretrained(
"tencent/HunyuanImage-3.0",
torch_dtype=torch.float16
)
pipe.to("cuda")
image = pipe(
prompt="your prompt here",
num_inference_steps=30,
guidance_scale=6.0,
height=1024,
width=1024,
).images[0]
image.save("output.png")Get started
Setup instructions for running HunyuanImage 3.0 locally
1. Download the model
Get the checkpoint from HuggingFace
2. Place in:
ComfyUI/models/checkpoints/3. Launch ComfyUI
python main.pyMemory Breakdown
VRAM allocation at 1024×1024 on RTX 4090 24GB (24 GB)
Estimated Generation Time
Time per image at 1024×1024, 28 steps, FP16.
Sample Outputs
Available Formats, Downloads & Setup
Download HunyuanImage 3.0 in the precision that matches your GPU. Lower precision usually means less VRAM pressure, while higher precision keeps more quality.
| フォーマット | 精度 | サイズ | プロバイダー | |
|---|---|---|---|---|
| safetensors | BF16 | 157.0 GB | official | ダウンロード |
LoRA Ecosystem
LimitedNew model with very few LoRAs available yet.
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Frequently asked questions
FAQ — HunyuanImage 3.0 VRAM, Runtimes & Fit
How much VRAM does HunyuanImage 3.0 need?
HunyuanImage 3.0 (84B parameters) requires approximately 177.7 GB of VRAM at FP16 precision for standard 1024×1024 image generation. If you want a lighter setup, lower precisions like FP8 can reduce memory use when available.
Can I run HunyuanImage 3.0 on an 8GB GPU?
HunyuanImage 3.0 usually needs more than 8GB for comfortable local use. Check the VRAM table above for the exact resolution and precision trade-off.
Does HunyuanImage 3.0 work in ComfyUI and Diffusers?
HunyuanImage 3.0 is marked for ComfyUI and Diffusers support in our catalog, so those are the runtimes we recommend first for local setup. If your workflow uses another front end, check the model's available formats and workflow notes above before downloading.
Can I run HunyuanImage 3.0 on RTX 4090?
HunyuanImage 3.0 is too large for the RTX 4090's 24 GB VRAM at FP16. Consider using FP8 precision or a GPU with more VRAM.
Does HunyuanImage 3.0 support ControlNet?
There are currently no known ControlNet adapters for HunyuanImage 3.0. Check Hugging Face and Civitai for community-contributed adapters.
Does HunyuanImage 3.0 have LoRA support?
New model with very few LoRAs available yet. The LoRA ecosystem for HunyuanImage 3.0 is rated as "minimal". Each LoRA adds roughly 0.5 GB of extra VRAM.
How fast is HunyuanImage 3.0?
On a reference GPU (RTX 4090 24GB), HunyuanImage 3.0 generates a 1024×1024 image in approximately ~11.9s at FP16 with 28 inference steps. Faster GPUs with higher memory bandwidth will produce images more quickly.
About HunyuanImage 3.0
See also