# ComfyUI-HiCache
**Training-free Hunyuan3D shape-generation acceleration for ComfyUI** — skip DiT
forwards during flow-matching sampling and forecast the velocity instead, using
the [`hicache-pp`](https://pypi.org/project/hicache-pp/) library
([HiCache](https://arxiv.org/abs/2508.16984) Hermite-polynomial and HiCache++
DMD/Prony-exponential forecasters).
> **Status: GPU-validated end-to-end inside ComfyUI** (2026-06-11, RTX 5090,
> real ComfyUI + kijai/ComfyUI-Hunyuan3DWrapper + Hunyuan3D-2mini fp16):
> the patch engages on schedule, sampling runs 2.7x faster at the recommended
> `hermite interval=3`, the accelerated mesh stays well above the
> different-seed noise floor in F-score against the unaccelerated mesh, and
> repeated runs in one session reset state correctly. Measured details in
> *Validated on* below.
## Runtime path
Scheduled Hunyuan3D model evaluations anchor the velocity history. Forecasted steps reuse that history, while incompatible schedules and failed forecasts return to the full model and report the fallback.
## What it does
One node, `HiCache Accelerate (Hunyuan3D)`, wired between
[kijai/ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)'s
`Hy3DModelLoader` and its mesh sampler (`Hy3DGenerateMesh` /
`Hy3DGenerateMeshMultiView`):
```
Hy3DModelLoader ──pipeline──▶ HiCache Accelerate ──pipeline──▶ Hy3DGenerateMesh
```
The node patches `pipeline.model` (the shape DiT). On *compute* steps the DiT
runs normally and its output is cached as a forecast anchor; on *skipped* steps
the DiT is **not called at all** — the flow-matching velocity is forecast from
the cached anchors. With `interval = N`, roughly `(N-1)/N` of the DiT forwards
are skipped. The patch needs nothing from ComfyUI internals and works on any
pipeline object whose denoise loop calls
`self.model(latent_model_input, timestep, cond, ...)` once per step — which
covers the wrapper's vendored `hy3dgen` (Hunyuan3D 2.0) and `hy3dshape`
(Hunyuan3D 2.1) pipelines, including the mini/turbo checkpoints
([wrapper issue #97](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper/issues/97)
— the patch is checkpoint-agnostic; only the loop shape matters).
### Methods
| method | basis | when to use |
|---|---|---|
| `hermite` *(default)* | HiCache, dual-scaled physicist's Hermite polynomial ([arXiv:2508.16984](https://arxiv.org/abs/2508.16984)) | interval 3; the best-measured setting inside ComfyUI and on both upstream checkpoints |
| `dmd` | HiCache++, Dynamic Mode Decomposition / Prony exponential basis | larger intervals (4 to 5) on the big 2.1 DiT; on mini it measured below the seed-noise floor inside ComfyUI (see *Validated on*) |
| `auto` | holdout-selected per compute step: serves DMD only when it demonstrably beats the polynomial on the cached window | when unsure |
### Inputs
| input | default | meaning |
|---|---|---|
| `pipeline` | — | `HY3DMODEL` from `Hy3DModelLoader` |
| `method` | `hermite` | forecast basis (above) |
| `interval` | 3 | compute 1 step, forecast `interval-1`. `1` disables caching |
| `warmup_steps` | 2 | always compute the first N steps (floored at 1 — the first step has nothing to forecast from) |
| `enable` | true | off = unpatch, restore the original DiT |
| `max_order` | 1 | Hermite / finite-difference order |
| `sigma` | 0.5 | Hermite contraction factor in (0,1) |
| `dmd_history` | 5 | DMD snapshot window length |
Re-running the node with new parameters re-patches cleanly; `enable=false` (or
`interval=1`) restores the original model. State resets automatically at each
new sampling run.
## First-result acceptance checklist
Use a fixed small input and record the exact ComfyUI, wrapper, checkpoint, node
commit, method, interval, seed, and torch/CUDA versions. Before treating a run
as accelerated, verify all of the following:
* **Baseline:** run once with `enable=false` (or `interval=1`) and save the
output plus the unaccelerated DiT-forward count.
* **Accelerated:** run the same input and seed with the node enabled; confirm
`pipeline.model.branch_id` is `stacked_pre_cfg`, the `run_id` changes on a
retry, and `pipeline.model.telemetry` reports the actual decision and method
counters. DMD/auto history below their method-specific floors is rejected;
short or non-uniform windows remain visible as Hermite fallback counts.
* **Lifecycle:** repeat the run, including a one-step `t=0` retry, and confirm
the run starts with a fresh full decision rather than a stale forecast.
* **Comparison:** compare baseline and accelerated outputs and retain the raw
per-run counts. GPU timing/quality and a clean-host workflow import are
separate gates; this CPU package check does not establish a speed or quality
claim.
The node never mutates the pipeline it receives: it returns a shallow copy
whose `model` attribute is the patch (weights stay shared, so this costs no
VRAM). This matters because ComfyUI caches node outputs keyed on node inputs;
an in-place patch lets a cached output alias a pipeline that a later run
re-patched with different settings. That failure was actually observed during
GPU validation (a cached `hermite interval=3` output silently ran
`dmd interval=5`) and is covered by a regression test.
## Measured inside ComfyUI (this node, end-to-end)
Setup: ComfyUI 0.24.0, kijai/ComfyUI-Hunyuan3DWrapper master, Hunyuan3D-2mini
fp16 single-file checkpoint, RTX 5090, torch 2.12 cu128. Workflow: LoadImage
(518x518 RGBA crop) -> InvertMask -> Hy3DModelLoader -> HiCacheAccelerate ->
Hy3DGenerateMesh (30 steps, cfg 5.5) -> Hy3DVAEDecode (octree 384) ->
Hy3DExportMesh. Quality metric: F-score@0.05 of the accelerated mesh against
the unaccelerated mesh from the same seed (50k surface samples each, shared
canonical frame, no alignment needed); as a floor, two unaccelerated runs
that differ only in seed score 0.751 on the same metric.
| config | DiT steps run | sampling | sampling speedup | F1@0.05 vs baseline |
|---|---|---:|---:|---:|
| baseline (`enable=false`) | 30/30 | 1.87 s (16.1 it/s) | 1.00x | 1.000 |
| `hermite interval=3` | 11/30 | 0.70 s (43.1 it/s) | **2.68x** | **0.825** |
| `dmd interval=5` | 7/30 | 1.10 s (27.2 it/s) | 1.69x | 0.719 |
Reading: `hermite i3` is comfortably above the 0.751 different-seed floor
(the accelerated mesh is closer to its baseline than a fresh seed is), at a
2.7x sampling speedup. `dmd i5` lands at the floor on mini inside ComfyUI;
its forecast also costs more per skipped step (an SVD), which eats into the
speedup on a DiT this small. Hence the node defaults are `hermite` / `3`.
On mini the end-to-end win is modest in absolute terms (about 1.2 s of a
roughly 9 s run) because VAE decode and marching cubes dominate; the larger
the shape DiT and the higher the step count, the larger the end-to-end share
the node saves.
## Measured numbers (from the adapter repos, outside ComfyUI)
The same forecasters, wired into the upstream Hunyuan3D pipelines (outside
ComfyUI), measured on Toys4K image-to-3D with geometry-preserving A/B
(F-score@0.05 vs. the uncached baseline, solo re-timed speedups). Full tables
and methodology:
[hicache-plus-plus results](https://github.com/Archerkattri/hicache-plus-plus/blob/master/results/RESULTS.md).
**Hunyuan3D-2.1** (baseline F-score 0.911):
| interval | Hermite (HiCache) | DMD (HiCache++) | speedup |
|---:|---:|---:|---:|
| i3 | **0.876** | 0.852 | 1.72× |
| i4 | 0.776 | **0.827** | 1.80× |
| i5 | 0.735 | **0.860** | 1.79× |
**Hunyuan3D-2-mini** (baseline F-score 0.794, 1.89 s/gen): DMD i5 is **exactly
lossless** (0.794) at 1.69 s; HiCache i3 0.792 at 1.58 s.
Source adapter repos (measured, runnable):
[hunyuan2-plus-plus](https://github.com/Archerkattri/hunyuan2-plus-plus) (2.0 + mini),
[hunyuan2.1-plus-plus](https://github.com/Archerkattri/hunyuan2.1-plus-plus) (2.1).
These numbers come from first-class pipeline wiring (the forecast caches the
CFG-combined velocity); the ComfyUI node is a model-level patch that caches
the pre-CFG stacked output instead. For Hermite the two are mathematically
identical. For DMD they are not, and the inside-ComfyUI measurement above
confirms the difference is real on mini: prefer `hermite` in this node unless
you re-A/B `dmd` on your own checkpoint.
## Install
**Via ComfyUI-Manager:** search for `ComfyUI-HiCache` (once indexed), or
*Install via Git URL* → `https://github.com/Archerkattri/ComfyUI-HiCache`.
**Manual:**
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/Archerkattri/ComfyUI-HiCache
pip install -r ComfyUI-HiCache/requirements.txt # just: hicache-pp
```
Requires [ComfyUI-Hunyuan3DWrapper](https://github.com/kijai/ComfyUI-Hunyuan3DWrapper)
to provide the `HY3DMODEL` pipeline the node accelerates.
## Validated on
What has actually been verified, and how:
* **CPU node-pack integration smoke**: `pytest -q tests/test_nodes.py` imports the
package as ComfyUI does, checks its node mappings and input schema, and verifies
patch/unpatch behavior without requiring a ComfyUI installation. Forecast and
budget unit tests are not included in this review branch.
* **End-to-end GPU validation inside ComfyUI** (2026-06-11, RTX 5090, ComfyUI
0.24.0, wrapper master, Hunyuan3D-2mini fp16):
* headless ComfyUI boots with the pack installed, zero import errors, and
`HiCacheAccelerate` appears in `/object_info`;
* the full image-to-mesh workflow executes through the ComfyUI API with the
node wired in, and the patch demonstrably engages: with 30 sampling steps
the run-boundary log reports `11 computed + 19 skipped` for
`hermite interval=3` and `7 computed + 23 skipped` for `dmd interval=5`,
exactly the library schedule, with the sampling rates and meshes in the
table above;
* repeated runs in one server session (the same patched pipeline served
from ComfyUI's node-output cache across prompts) each reset the forecast
state at the run boundary and produce fresh, seed-dependent meshes;
* two bugs were found during this validation and fixed: (1) ComfyUI cache
aliasing, fixed by copy-on-patch (see *Inputs*);
(2) back-to-back single-step runs both start at t=0, which the old
strictly-decreasing run-boundary check missed, so the second run could be
served a stale anchor; the boundary check is now non-increasing.
* **Adapter-repo GPU measurements**: the identical forecasters and schedule,
measured in the upstream (non-ComfyUI) Hunyuan3D pipelines (tables above).
**Not yet measured:** the full-size Hunyuan3D 2.0/2.1 checkpoints inside
ComfyUI (the mechanism is identical and checkpoint-agnostic, and the adapter
repos measured those checkpoints upstream, but the in-Comfy numbers above are
mini-only), and the multiview sampler path (`Hy3DGenerateMeshMultiView`).
### One honest design note
The adapter repos wire the forecast into the pipeline loop and cache the
*CFG-combined* velocity; a model-level patch (the only non-invasive option for
a ComfyUI node) caches the *pre-CFG stacked* DiT output instead. For the
Hermite forecaster the two are mathematically identical (forecast and CFG
combine are both linear); for DMD the fit runs on the stacked trajectory
rather than the combined one. The inside-ComfyUI A/B above shows this matters
in practice: DMD's upstream "lossless at interval 5 on mini" result does NOT
transfer to the model-level patch, so this README does not claim it. Hermite
numbers transfer exactly, and that is what the defaults use.
## License
MIT. Not affiliated with Tencent (Hunyuan3D) or kijai (ComfyUI-Hunyuan3DWrapper).
## Current release status
The current adapter includes the shared HiCache++ budget/identity/manifest
bridge, timing and fallback accounting. Its CPU contract suite passes 45 tests.
ComfyUI execution with the real CUDA model workflow was not run in this
environment, so no image-quality or speedup claim is made.