Image models ·

Hunyuan-DiT v1.2

Backbone
1.5B
Native output
1024×1024
Default steps
50
License
tencent-hunyuan-community
Released
2024-07

How to run it

Original weights · Hugging Face

Full-precision files from Tencent, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Tencent. The weights themselves download from Hugging Face.

github.com/Tencent-Hunyuan/HunyuanDiT (opens in a new tab)

git clone https://github.com/Tencent-Hunyuan/HunyuanDiT

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

Apps that run Hunyuan-DiT v1.2

Our pick for each kind of computer, assuming the model fits in its memory. Pick your own GPU or device in the Model Finder for an exact answer.

Mac (Apple silicon)

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

Windows PC, NVIDIA GPU

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

Linux, NVIDIA or AMD GPU

ComfyUI

Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Also good:

App Type Opens it as Systems Engine Start
ComfyUI Desktop app Built-in support macOSWindowsLinux PyTorch, GGUF via ComfyUI-GGUF Get ComfyUI
SwarmUI Desktop app Built-in support macOSWindowsLinux ComfyUI Get SwarmUI
SD.Next Desktop app Built-in support macOSWindowsLinux PyTorch Get SD.Next
Stability Matrix Desktop app Built-in support macOSWindowsLinux installs ComfyUI, Forge, InvokeAI, SwarmUI, SD.Next or Fooocus Get Stability Matrix

Which apps can open a model depends on the files published for it: GGUF for llama.cpp-based apps, MLX for Apple’s engine, the original weights for vLLM and SGLang. Compare every app.

Memory needed

Peak GPU memory at the native output size. Offloading moves the text encoder, or the whole pipeline, to system RAM between steps.

Precision Everything on GPU Text encoder offloaded Sequential offload Download
FP16 9.3 GB 5.2 GB 3.1 GB Original weights (opens in a new tab)

Components

Best hardware for Hunyuan-DiT v1.2

The least expensive GPU in our catalog that runs it without offloading is the Intel Arc A380 (launch price $139) at FP16.

Quality Hardware Quant Memory Speed Runs
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 SUPERNVIDIA GeForce RTX 4070 SUPER FP16 9.3 GB / 12.0 GB 11 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Sapphire NITRO+ AMD Radeon RX 9070 XT OCAMD Radeon RX 9070 XT FP16 9.3 GB / 16.0 GB 8.0 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 Ti SUPERNVIDIA GeForce RTX 4070 Ti SUPER FP16 9.3 GB / 16.0 GB 9.6 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4080 SUPERNVIDIA GeForce RTX 4080 SUPER FP16 9.3 GB / 16.0 GB 8.5 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. ASUS TUF Gaming GeForce RTX 5070 Ti 16GB GDDR7 OC EditionNVIDIA GeForce RTX 5070 Ti FP16 9.3 GB / 16.0 GB 9.6 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5080 Founders EditionNVIDIA GeForce RTX 5080 FP16 9.3 GB / 16.0 GB 8.0 s Runs great
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. ASUS Dual GeForce RTX 5060 Ti 16GB GDDR7 OC EditionNVIDIA GeForce RTX 5060 Ti 16GB FP16 9.3 GB / 16.0 GB 15 s Runs well
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. ASUS Dual GeForce RTX 4060 Ti OC Edition 16GB GDDR6NVIDIA GeForce RTX 4060 Ti 16GB FP16 9.3 GB / 16.0 GB 16 s Runs well
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 3060 12GBNVIDIA GeForce RTX 3060 12GB FP16 9.3 GB / 12.0 GB 24 s Runs well
52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Intel Arc B580 Limited EditionIntel Arc B580 FP16 9.3 GB / 12.0 GB 25 s Runs well

Check it on your own hardware

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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