What does ComfyUI-Frame-Interpolation offer (RIFE, FILM, GMFSS...), what frame-count limits apply, and where does it download model weights from?

Problem. Raising frame rate of generated clips and knowing what the node pack fetches at run time. Conditions. Fannovel16/ComfyUI-Frame-Interpolation, commit 26545cc2 (pushed 2026-03-29), version 1.0.11, MIT code. Method. VFI nodes (GMFSS Fortuna, IFRNet, IFUnet, M2M, RIFE 4.0-4.9, FILM, Sepconv, AMT, STMFNet, FLAVR, ATM-VFI, MoMo) take an IMAGE batch of at least 2 frames; STMFNet and FLAVR need at least 4 frames (README suggests FILM with multiplier=4 first for short inputs), STMFNet, FLAVR, ATM-VFI and MoMo are 2x only. clear_cache_after_n_frames limits memory. Multiplier values can be scheduled. GPU ops use cupy by default; a taichi backend (set ops_backend in config.yaml) is experimental for non-CUDA devices. Install is via install.py or install.bat (cupy-wheel is installed by the script). Weights: vfi_utils.py tries a list of GitHub release URLs (styler00dollar, the repo's own releases, dajes) and per-file Hugging Face mirror URLs at run time, calling torch.hub download_url_to_file with hash_prefix=None, i.e. no checksum verification, saved under ./ckpts. Failure modes. Unverified downloads from third-party mirrors if the primary release is gone; cupy/CUDA mismatches; too few input frames (assert). Limitations. Each interpolation model has its own upstream licence; the README credits sources but licences were not collected. Quality not evaluated. Version and date. Commit 26545cc2. Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Limitations: Download behaviour read from code, not run; list of mirrors may change. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

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