Model and checkpoint merging tools by lonecatone23. Companion pack to ComfyUI_LC123_nodes and ComfyUI_LC_AV_nodes, kept separate so LC123 stays dependency-light. This pack is where merge, blend, and block-inject nodes live, plus the tools to test what a model actually does (like the same-face test in LC Face Variety Scorer).

Nodes

| Node | Purpose | |---|---| | LC Krea2 Block Merge Advanced | Merge two Krea2 checkpoints with a draggable per-block ratio curve across the 28 uniform MMDiT blocks, plus individual sliders for the 10 named regions. Save/load named presets. | | LC Krea2 Semantic Vector Tuner | Amplify or attenuate regions of a single Krea2 checkpoint's own weights. Not a merge — one model in, one model out. | | LC Checkpoint Save | All-in-one checkpoint saver — model + clip + vae, all required. Adds an enabled toggle and a per-save embed_workflow toggle that core's stock Save Checkpoint node doesn't have. | | LC Diffusion Model Save | Same as LC Checkpoint Save but model-only — no clip/vae sockets at all. | | LC Face Variety Scorer 🧑‍🤝‍🧑 | Same-face test for a model. Scores how different the faces in an image batch are (0.0 - 1.0, lower = more variety), plus a group-shot score and a grid of the faces it found. |

LC Krea2 Block Merge Advanced

Krea2 is a single-stream MMDiT: its 28 main blocks are architecturally uniform, so one continuous curve across them makes sense in a way it wouldn't for a double-stream model like Flux. The 10 named regions (first, tmlp, txtmlp, tproj, and the txtfusion.* group, plus last) are architecturally distinct, so they get their own sliders instead of living on the curve.

💡 The merge itself isn't custom tensor math. It builds the same prefix-to-ratio mapping ComfyUI's own ModelMergeKrea2 node uses and hands it to ComfyUI's own ModelMergeBlocks.merge() (longest-prefix-match, get_key_patches / add_patches). This node is a UI on top of a mechanism ComfyUI core already ships and tests.

Curve drag: click and drag anywhere in the graph. edit_mode is smooth (drag one block, neighbors blend in with a falloff set by smooth_radius) or spike (only the block under the cursor moves). Hover or drag to see a live tooltip with the zone, block number, and value. Zone dividers (low/mid/high) and a labeled 0.5 midline are drawn on the graph.
Presets: pick a name from the preset combo to load it, or type a name into save_name and hit Save preset (writes on the next queue). A preset stores the curve and all 10 named sliders together. Touching any slider or the curve by hand snaps preset back to Custom immediately.
0 = all model1, 1 = all model2 at every block and every named region.

Bundled presets

50_50 is the default on a fresh node.

| Preset | Idea | |---|---| | 50_50 | Flat 0.5 everywhere — every block and every named slider. A neutral, even blend to dial from. Default preset on launch. | | face_favor | Smooth low→high ramp (0.15→0.75). Keeps early blocks and the input/timestep sliders close to model1 to anchor identity/structure, lets late blocks pick up more of model2. | | detail_focus | Low and mid blocks stay flat and close to model1; only the high-zone blocks (and last) ramp hard toward model2 — a surgical late-block detail swap. | | style_favor | The mirror of face_favor: high→low ramp (0.75→0.15). Early structure comes from model2, late refinement/output stays with model1. | | sine_wave | Two full oscillations across the 28 blocks, centered on 0.5. A stress-test / exploratory curve rather than a targeted merge. | | resonance_blocks | Spikes blocks 1, 3, 5, 7, 11, and 15 toward model2 (0.85), everything else stays low (0.3) — the "certain blocks dominate" pattern. 💡 I read "top model" as model2 (the one merged in); flip the spike/baseline values if you meant the opposite. | | even_blend | Plain linear 0→1 ramp across all 28 blocks. The reference/baseline preset. | | core_focus | Gaussian bump centered on the mid zone — pulls model2's "core" understanding into the middle of the network while leaving the edges (and the txtfusion.* sliders moderately) closer to model1. | | heavy_transplant_anchored | Nearly all model2 (0.9) except block 0 and the first/tproj sliders, which stay anchored to model1 to avoid the merge drifting off-structure. |

LC Krea2 Semantic Vector Tuner

Not a merge — this one takes a single checkpoint and turns specific regions up or down. Ported from the Arthemy SDXL Suite's ArthemySDXLModelTuner mechanism: it bakes any patches already on a weight, scales the baked tensor by a target multiplier, and re-patches the difference. Same proven patching approach, re-pointed at Krea2's real prefixes instead of SDXL's UNet layout.

mode: Soft Value dampens the 0-2 sliders so nothing above 1.0 overdrives past roughly 1.13x — safe for exploring. Real Value applies the slider as a literal multiplier.
low_blocks / mid_blocks / high_blocks: scale the same three zones (0-8 / 9-17 / 18-27) as Block Merge Advanced's graph. 💡 Krea2's 28 blocks are architecturally uniform — unlike SDXL's UNet, there's no verified evidence they specialize by depth, so this node doesn't invent named sub-groups the way Arthemy's SDXL tuner does. blocks_override (a 28-value comma list) is there if you want finer control than three zones.
10 named-region sliders: same prefixes, same tooltips as Block Merge Advanced.
base_scale: fallback multiplier for anything that isn't one of the 28 blocks or the 10 named regions.

LC Checkpoint Save / LC Diffusion Model Save

A checkpoint means an all-in-one file, so these are two separate nodes rather than one node with optional sockets. Both reuse ComfyUI core's own comfy.sd.save_checkpoint() and the same modelspec-metadata detection core's stock "Save Checkpoint" node uses, so the files they write are the same format. Both share these two things core's node doesn't give you:

enabled: off skips the save entirely, no file written. A save node has no outputs, so ComfyUI's native bypass has nothing to pass through — this is a real toggle you can convert to an input and wire from a switch elsewhere in the graph.
embed_workflow: per-save control over whether the prompt/workflow JSON goes into the file's metadata, independent of the --disable-metadata launch flag core's node is stuck reading. 💡 Turn this off before sharing a model if you don't want your exact node graph attached to the file.

LC Checkpoint Save: model, clip, and vae are all required. filename_prefix defaults to checkpoints/LC_ModelBuilder.

LC Diffusion Model Save: only model — no clip/vae sockets at all. filename_prefix defaults to diffusion_models/LC_ModelBuilder. 💡 The file still carries the same model.diffusion_model. prefix a full checkpoint's UNet half uses, not a bare-key export — that's not a loading problem (Load Diffusion Model auto-strips known prefixes) but the file will be a little larger than a from-source diffusion_models/ release.

LC Face Variety Scorer 🧑‍🤝‍🧑

Catches "same face" in a model. Feed it a batch of generations (same prompt, different seeds works best, 8 or more images) and it finds the main face in each one, compares every face against every other face with a face recognition model, and averages it.

score: 0.0 - 1.0, lower = more variety. It only looks at the face, not hair, clothes or lighting.

| Score | What it looks like | |---|---| | 0.0 - 0.2 | Clearly different people | | 0.2 - 0.35 | Different people who share a few features | | 0.35 - 0.5 | Could be sisters, or the same person in a different photo | | 0.5 - 1.0 | Same person |

same_pct: the percent of face pairs above same_threshold (0.35), i.e. "could be the same person."
crowd_score: same scale, but compares the faces inside each image. For group shots, lower = the crowd is different people, not clones.
faces: a grid of the faces it used, so you can see what it measured.
report: all of the above as text, ready for a Show Text / Preview Any node.
💡 Pair it with LC Image Batch From Folder (LC123) to score a whole folder of test images. The example workflow is in workflows/.

Face models (auto-download): the first run downloads InsightFace's buffalo_l pack (~280 MB) into ComfyUI/models/insightface/models/buffalo_l/. If you already have it there (IPAdapter FaceID, ReActor, etc. use the same folder), nothing is downloaded. The download is checksum-verified, so a cut-off download never leaves broken files behind.

No insightface, no opencv: the models run straight through onnxruntime. The insightface Python package (the one that needs a C++ compiler and fights with numpy/protobuf) is not needed, and neither is opencv.

install.py (run by ComfyUI-Manager) checks for a working onnxruntime. Already have one (any flavor)? It changes nothing. None at all? It installs the plain CPU onnxruntime. It never uninstalls or upgrades anything, and it saves a pip freeze backup to install_backups/ before any change. If your onnxruntime is installed but broken, it prints the exact repair commands instead of guessing.
device: cpu is the default and works on every install (NVIDIA, AMD, Intel, Mac). A normal test batch takes seconds. auto tries CUDA first and quietly falls back to CPU.

⚠️ The buffalo_l model files are released by InsightFace for non-commercial research use only. Check their license before using this commercially.

Credits

InsightFace by Jia Guo, Jiankang Deng and contributors: github.com/deepinsight/insightface. The face detection decode and alignment in lc_face_variety.py follow InsightFace's own reference code (MIT).
ArcFace: Deng et al., ArcFace: Additive Angular Margin Loss for Deep Face Recognition, CVPR 2019.
SCRFD: Guo et al., Sample and Computation Redistribution for Efficient Face Detection, 2021.

Install

Clone into ComfyUI/custom_nodes/:

git clone https://github.com/lonecatone23/ComfyUI_LC_ModelBuilder_nodes

Check the folder structure. __init__.py should sit directly in ComfyUI/custom_nodes/ComfyUI_LC_ModelBuilder_nodes/, not nested one level deeper.
Restart ComfyUI.
💡 No requirements.txt. The merge and save nodes only use what ships with ComfyUI core. LC Face Variety Scorer needs onnxruntime, and install.py handles that for you (ComfyUI-Manager runs it on install and update). Installing by hand with git clone? Run python install.py once with ComfyUI's own python.
💡 The LC Face Variety Test workflow in workflows/ also uses LC Image Batch From Folder from ComfyUI_LC123_nodes (v1.40.0 or newer).
💡 Hard-refresh your browser (Ctrl+Shift+R) after updating, so the new JS chrome actually loads.

"True Nothing is. Permitted Everything is"- Yoda Auditore, Assassin's Wars