FLUXNATION

The FLUXNATION node is a lie in the best way. It takes a MODEL, prints a status line, and hands the same MODEL back - no math, no parameters, nothing else. And it's the most useful node in the pack, because it's the only one that tells you whether the kernel actually loaded.

Here's the setup. FLUXNATION (the pack) is a fused FP8 CUDA kernel for FLUX.1 that replaces ComfyUI's SingleStreamBlock forward pass with a single torch.ops call, then adds block-sparse "spike" attention and step caching on top. The kernel patches itself into ComfyUI at startup - it's active whether or not any node is in your graph, and the four nodes in the pack are just live control panels for it. This node, also named FLUXNATION, is the pack's namesake and its most minimal member: it's a pure pass-through whose entire job is to print [FLUXNATION] FP8 fused CUDA kernel ACTIVE | SPIKE ON (or SPIKE OFF) to the console when it runs.

Why that matters: the pack's failure mode is silent. The build is genuinely fiddly - Visual Studio 2022, CUDA 12.x, Python 3.10, a hardcoded -arch=sm_89 for RTX 4090-class Ada, and CUTLASS headers the repo references but doesn't ship. If any of that goes sideways, the extension doesn't load, apply_patch() never runs, and ComfyUI just... runs stock. Your workflow still works, the node still passes the model through, and you have no idea you're getting zero speedup. The only signal is a console line at startup: [FLUXNATION] DISABLED - extension not found. Run build_ext.bat. versus the green-light version. Wiring this node in at the head of your graph gives you a second, in-graph signal - if you don't see the ACTIVE print when it executes, the kernel isn't in the pipeline and nothing else you do with this pack matters.

It's also the pack's canary for the spike state. The controller tracks enabled from the FLUX_SPIKE environment variable at launch, and this node echoes the current state, so after you've fiddled with FLUXSPIKEY or ULT7RAFLUX mid-session, a run through this node confirms where the spike flag actually landed. That's the whole value: a status readout you can wire into any workflow without affecting anything.

Install is the pack install, same for every node here. The README's route:

git clone https://github.com/ULT7RA/cuda-kernels.git
# copy FLUXNATION/custom_nodes/FLUXNATION/ -> ComfyUI/custom_nodes/FLUXNATION/
cd FLUXNATION
build_ext.bat

That compiles flux_ext into your Python site-packages. Requirements: Visual Studio 2022 with the C++ workload, CUDA Toolkit 12.x, Python 3.10 - the exact version ComfyUI runs, since that's the interpreter that has to import flux_ext. There's no requirements.txt; the node leans on the torch and Triton already in your ComfyUI environment. On Linux the README's fallback is python setup_ext.py install from the node directory. Launch with FLUX_SPIKE=1 (the run_nvidia_gpu_spike.bat file sets the full recommended set, FLUX_SPIKE=1 FLUX_SPIKE_SWITCH=0.50 FLUX_SPIKE_CAP=0.45 FLUX_SPIKE_TAU=0.05 FLUX_SPIKE_CACHE=1), and the kernel engages at startup. Set FLUX_EXT_DISABLE=1 to force stock ComfyUI for benchmarking - that's the documented A/B switch, and it pairs perfectly with this node's status print as the confirmation on each side.

A couple of caveats before you trust any of it. The pack is new, single-author, and essentially unvalidated - the r/StableDiffusion announcement (April 2026) drew more suspicion than cheers, and the clone history shows a single commit (a Triton hang fix). The claimed numbers are one person's 4090 benchmark (~9.3s vs ~13–14s stock at 20 steps, 1024×1024). None of that makes the kernel fake - the code is real and readable - but it means the status line this node prints is worth more than the usual "all good" message. When ACTIVE, you're running the author's experiment at full speed. When DISABLED, you're running stock ComfyUI, which is honestly a fine place to be.