Run LoRA on RunComfy - billed per request. The inference uses the same base model and the full AI Toolkit pipeline definition from your training run, so what you saw during training is what you get in inference.
Choose a base model, and start running your lora
MiniMax-H3
LoRA 실행
Krea 2 Edit
LoRA 실행
Krea 2 Edit Turbo
LoRA 실행
Krea 2 Turbo
LoRA 실행
Krea 2
LoRA 실행
LTX-2.3
LoRA 실행
Z-Image Base
LoRA 실행
FLUX.2 Klein 9B
LoRA 실행
LTX-2
LoRA 실행
Qwen Image 2512
LoRA 실행
Z-Image de-Turbo
LoRA 실행
Z-Image Turbo
LoRA 실행
FLUX.2
LoRA 실행
Wan 2.2 14B I2V
LoRA 실행
Wan 2.2 14B T2V
LoRA 실행
Qwen Image
LoRA 실행
SDXL
LoRA 실행
FLEX 1
LoRA 실행
FLUX.1
LoRA 실행
MiniMax-H3-Image
LoRA 실행
PrunaAI P-H3-Image
LoRA 실행
Fibo 2.0 Dev
LoRA 실행
FastH3 Omni
LoRA 실행
MOSS-Image SFT [Edit Training]
LoRA 실행
MOSS-Image SFT
LoRA 실행
MOSS-Image Base
LoRA 실행
MOSS-Image Base [Edit Training]
LoRA 실행
FLUX.3 Image Klein (base)
LoRA 실행
Qwen-Image-2.1 Turbo (w/ Training Adapter)
LoRA 실행
Iris-3B (pixel space)
LoRA 실행
FastH3 8-Step V2
LoRA 실행
Ming-Image 0.1 Design (w/ Training Adapter)
LoRA 실행
Qwen-Image-2.1
LoRA 실행
YuE2
LoRA 실행
MiniMax-H3 Ref2V
LoRA 실행
LTX-2.5
LoRA 실행
Mage-Flow
LoRA 실행
Mage-Flow Edit
LoRA 실행
Anima
LoRA 실행
Boogu Image
LoRA 실행
Boogu Image Edit
LoRA 실행
PRXPixel (pixel space)
LoRA 실행
Ideogram4
LoRA 실행
Z-Image L2P (pixel space)
LoRA 실행
HiDream-O1
LoRA 실행
ERNIE-Image
LoRA 실행
Nucleus-Image
LoRA 실행
ACE-Step 1.5
LoRA 실행
ACE-Step 1.5 XL
LoRA 실행
Zeta Chroma
LoRA 실행
FLUX.2-klein-base-4B
LoRA 실행
Qwen-Image-Edit-2511
LoRA 실행
Qwen-Image-Edit-2509
LoRA 실행
Qwen-Image-Edit
LoRA 실행
Wan 2.2 TI2V (5B)
LoRA 실행
HiDream E1
LoRA 실행
Wan 2.1 I2V (14B-480P)
LoRA 실행
Wan 2.1 I2V (14B-720P)
LoRA 실행
FLUX.1-Kontext-dev
LoRA 실행
OmniGen2
LoRA 실행
SD 1.5
LoRA 실행
Flex.2
LoRA 실행
Chroma
LoRA 실행
Wan 2.1 (1.3B)
LoRA 실행
Wan 2.1 (14B)
LoRA 실행
HiDream
LoRA 실행
Lumina2
LoRA 실행