u/VQSGecko

Rocm performance and reliability has been greatly improved on Comfyui if using up to date Comfyui, Rocm, and Pytorch.

System

• CPU: AMD 7840HS
• GPU: RX 7900 XT (OCuLink) (20GB VRAM)
• RAM: 64 GB DDR5
• OS: Ubuntu 26.04
• ComfyUI 0.33.1 + comfy-kitchen 0.2.31 + comfy-aimdo 0.4.13
• pytorch version: 2.12.0+rocm7.14.0
• Python version: 3.13.15
• Resolution tested: 0.4 MP
• Steps: 20
• Video lengths: 5 s (cold) and 8 s

Models used

• Diffusion Model: minimax_h3_fl2va_pruned_int8_convrot.safetensors
• CLIP / Text Encoder: qwen3vl_32b_minimax_h3_int4_convrot.safetensors
• Video VAE: minimax_h3_video_vae_int8_convrot.safetensors
• Audio VAE: minimax_h3_audio_vae_fp32.safetensors

High-level findings (5 s / 8 s step times)

Configuration	5 s (s/it)	8 s (s/it)	Approx. speedup vs baseline
pytorch attention	27.8	56.9	1.00× (baseline)
TheRock + pytorch attention	17.0	35.7	~1.6×
Standard / TheRock + CK or Flash Attn	16.2–16.3	29.6–29.9	~1.7× / ~1.9×
Above + Dynamic VRAM	16.2–16.3	29.6–29.9	Same step time, better wall-clock
Spectrum nodes + CK/Flash + DynVRAM	8.9	16.3–16.5	~3.1–3.5×

Key takeaways

• CK attention and Flash Attention are essentially tied on this hardware once you are on recent comfy-kitchen.
• Dynamic VRAM does not change step time much but meaningfully reduces total prompt time (especially cold runs). It also reduces system ram usage and helps with hard drive swap file usage.
• Dynamic VRAM is not on by default it requires --enable-dynamic-vram (you don't need a flag currently to turn it off)
• CK Attention is not on by default it requires --use-ck-attention
• The only exports I use HIP_VISIBLE_DEVICES=0 and CUDA_VISIBLE_DEVICES=0 since I have 2 GPUS. I found that other exports cause issues on runs and are no longer needed. Only add them if having issues on a fresh installation of Comfyui and Rocm.

Flags tested

• --use-ck-attention
• --enable-dynamic-vram