Video Upscaling & Restoration

Overview

"Upscaling video" in ComfyUI splits into three jobs, and the quality win comes from doing them in the right order:

1. Spatial restore + upscale. A temporal-aware model that increases resolution AND cleans compression blocks, blur, and AI-gen mush while keeping frames consistent over time. This is the part a plain image upscaler (ESRGAN, UltimateSDUpscale per-frame) does badly. Per-frame upscalers flicker because each frame is sharpened independently. Use a video model.
2. Frame interpolation (VFI). Synthesize in-between frames to raise fps (e.g. 24→48/60) for smooth motion. Do this after the spatial pass.
3. Encode. Mux frames (plus original audio) back to an MP4.

The two leading temporal restorers in 2026 are SeedVR2 (diffusion-transformer restorer, the proven workhorse) and FlashVSR (newer one-step streaming VSR, faster). Frame interpolation is RIFE (or FILM) via ComfyUI-Frame-Interpolation.

Verification note: every node/pack/model name below was confirmed against the GitHub repos and the ComfyUI registry / Manager as of June 2026. Where a name is approximate or version-dependent it is flagged. Do not substitute a node you can't confirm is installed. Check with install_custom_node (action: "list") / create_workflow (action:"node_info").

---

⭐ Recommended current pipeline (2026)

Downscale → SeedVR2 (temporal restore+upscale) → RIFE (interpolate) → VHS encode. This modernizes the user's classic recipe (below) with the current SeedVR2 node pack and is the path to ship by default. FlashVSR is the faster alternative for the restore stage (see "FlashVSR" section). Swap it in when speed matters more than absolute fidelity.

Node-graph sketch

LoadVideo  ─► GetVideoComponents ─► (IMAGE frames, audio, fps)
                       │
                       ▼
        ImageScaleBy / ImageScale   ◄── DOWNSCALE first (e.g. 0.5×) — clean,
                       │                  small input for the restorer
                       ▼
        SeedVR2 Video Upscaler  ◄── DiT model + VAE + (block swap) + (tiling)
           ├─ "SeedVR2 (Down)Load DiT Model"
           ├─ "SeedVR2 (Down)Load VAE Model"
           └─ ["SeedVR2 Torch Compile Settings"]  (optional speedup)
                       │  (restored, high-res frames)
                       ▼
        RIFE VFI (4.0 - 4.9)   ◄── multiplier 2 (e.g. 24→48 fps)
                       │
                       ▼
        CreateVideo (fps = source × multiplier) ─► SaveVideo
        — or — VHS_VideoCombine (carries audio passthrough)

LoadVideo / GetVideoComponents / CreateVideo / SaveVideo are core ComfyUI video nodes (same ones the official comfy.org SeedVR2 template uses). VHS_LoadVideo / VHS_VideoCombine come from ComfyUI-VideoHelperSuite (installed) and are preferred for the final encode because they pass the original audio through.

Why downscale FIRST (the load-bearing trick)

• The restorer wants a clean low-res input, not a big dirty one. SeedVR2 (and FlashVSR) regenerate detail. Feeding them a small frame forces the model to synthesize sharp detail rather than faithfully magnifying existing compression artifacts and noise. Downscaling first averages away block noise, so the restorer hallucinates clean, coherent texture.
• VRAM and speed headroom. Cost scales with input pixels × frames. Halving each dimension is ~4× fewer pixels per frame, which buys you a larger temporal batch (the thing that kills flicker, see below) and a bigger target multiple.
• It turns "upscale" into "restore-and-upscale." A 720p source downscaled to 360p then SeedVR2'd to 1080p+ looks much better than 720p→1080p straight, because the model rebuilds rather than stretches.
• Rule of thumb: downscale to 0.5× (or to a ~360 to 480p short side) for messy, low-bitrate, or AI-gen footage; skip the downscale for already-clean, high-bitrate sources where you only want more pixels.

---

Quick local path (no downloads) — per-frame ESRGAN + built-in RIFE

When the user wants a fast result on what's already installed (no SeedVR2 / FlashVSR multi-GB download), use the ESRGAN upscale models most setups already have. Check first with list_local_models (common ones: 4x_foolhardy_Remacri, the best for realistic footage/water/skin, and 4x-ClearRealityV1 for clean/sharp).

• Upscale: ImageUpscaleWithModel with a 4× ESRGAN model, then ImageScale back down to a clean 2× (a 4×→2× supersample). That downscale-after step is the single biggest quality lever here. It averages out per-frame noise.
• Interpolate: the built-in FrameInterpolate with RIFE v4.26 (see the Frame-interpolation section; no custom node on 0.26+).

Tradeoff: flicker. ESRGAN upscalers are per-frame (no temporal awareness), so they can shimmer or flicker on video, most visible on water and fine detail. The 4×→2× supersample mitigates it; if it still shimmers, that's the signal to switch the upscale stage to a temporal model (SeedVR2 / FlashVSR below), which is the real fix. So: per-frame ESRGAN = quick and local; SeedVR2 = flicker-free and best. Order is unchanged: upscale the real frames first, then interpolate.

This is the right default for a "do it now, locally" request; reach for the temporal restorers below when quality (or zero flicker) matters more than turnaround.

---

SeedVR2 (recommended restore stage)

Pack: ComfyUI-SeedVR2_VideoUpscaler (author numz), GitHub numz/ComfyUI-SeedVR2_VideoUpscaler, installable via ComfyUI-Manager / registry by that name. Install with panel_install_node or apply_manifest.

Node classes (4):

Node	Role
SeedVR2 (Down)Load DiT Model	loads the diffusion-transformer restorer (auto-downloads on first use)
SeedVR2 (Down)Load VAE Model	loads ema_vae_fp16.safetensors
SeedVR2 Torch Compile Settings	optional — torch.compile for speed
SeedVR2 Video Upscaler	the main node: takes frames + DiT + VAE → restored frames

Models (auto-download to models/SEEDVR2/; 3B = lighter, 7B = best quality):

File	Tier
seedvr2_ema_3b_fp16.safetensors	3B full precision
seedvr2_ema_3b_fp8_e4m3fn.safetensors	3B fp8 (mid VRAM)
seedvr2_ema_3b-Q4_K_M.gguf / -Q8_0.gguf	3B GGUF (low VRAM)
seedvr2_ema_7b_fp16.safetensors	7B full quality
seedvr2_ema_7b_fp8_e4m3fn_mixed_block35_fp16.safetensors	7B fp8
seedvr2_ema_7b-Q4_K_M.gguf (+ _sharp variants)	7B GGUF
ema_vae_fp16.safetensors	shared VAE

Key params on "SeedVR2 Video Upscaler":

Param	Meaning / recommended
resolution	target SHORT edge in pixels (not a ratio). Default 1080. Set the short side of your output (e.g. 1080 for 1080p-class).
batch_size	frames processed together. Must be 4n+1 (1, 5, 9, 13, 17, 21…). Higher = less temporal flicker but more VRAM. 5 is the default; push to 13–45 if VRAM allows for smoother results.
seed	default 42; fixed for reproducibility
blocks_to_swap	0–32 (3B) / 0–36 (7B). >0 offloads transformer blocks to CPU to cut VRAM (slower). Use max (32/36) on 8 GB.
VAE tiling	enable + set encode/decode tile size to fit the VAE step in low VRAM

3B vs 7B: start with 3B fp8. It's the speed/quality sweet spot for most footage. Move to 7B only when you need maximum reconstruction on faces/text and have the VRAM (or use the 7B GGUF + block swap).

---

FlashVSR (newer SOTA — faster restore stage)

Pack: ComfyUI-FlashVSR (author 1038lab), GitHub 1038lab/ComfyUI-FlashVSR, built on FlashVSR V1.1 (one-step diffusion + locality-constrained sparse attention + tiny conditional decoder). Manager name ComfyUI-FlashVSR. Models auto-download from HF 1038lab/FlashVSR to models/FlashVSR/ on first run.

Note: several community forks exist (smthemex/ComfyUI_FlashVSR, lihaoyun6/ComfyUI-FlashVSR_Ultra_Fast, naxci1/ComfyUI-FlashVSR_Stable). The 1038lab pack is the cleanest two-node implementation; pick a fork only if you need its specific VRAM tricks.

Node classes: FlashVSR ⚡ (preset: Fast / Balanced / High Quality) and FlashVSR Advanced ⚡ (model_version = Tiny / Tiny Long / Full, enable_tiling, speed_optimization, quality_boost, sageattention). Supports 2x and 4x (4x recommended). Needs ≥21 input frames. Variants: Full (best, heavy VRAM), Tiny (fast), Tiny Long (low VRAM). SageAttention adds ~20 to 30% speed.

When to prefer FlashVSR over SeedVR2: real-time, long clips, or speed-critical jobs, or when SeedVR2 is too slow on your hardware. Prefer SeedVR2 when you want the strongest restoration of badly-degraded footage and can spend the time.

---

Frame interpolation (VFI)

Built-in (ComfyUI 0.26+) — PREFER this, no custom node needed

Current ComfyUI ships a core frame interpolator, nodes FrameInterpolationModelLoader + FrameInterpolate (RIFE/FILM), so on 0.26+ you do NOT install a custom node. It auto-detects checkpoints dropped in models/frame_interpolation/ (that folder is empty by default, which is why the model dropdown looks blank). Core-compatible weights live at HF Comfy-Org/frame_interpolation (under a frame_interpolation/ subpath):

File	~Size	Use
rife_v4.26.safetensors	22 MB	RIFE, newest/most accurate — default for smooth small-motion fps-doubling
film_net_fp16.safetensors	66 MB	FILM — large-motion gaps

Drop a file into models/frame_interpolation/ and restart so the dropdown populates (ComfyUI caches model lists). download_model may not target that folder; pull it directly into models/frame_interpolation/. Check what's there with list_local_models / the core node's dropdown before installing anything.

Custom node (more methods / pre-0.26 ComfyUI)

Pack: ComfyUI-Frame-Interpolation (author Fannovel16), GitHub Fannovel16/ComfyUI-Frame-Interpolation. Manager-installable by that name. Reach for it only when you need methods the core node lacks (GMFSS, STMFNet, FLAVR, IFRNet…) or you're on a ComfyUI older than 0.26.

Primary node: RIFE VFI (4.0 - 4.9)

Param	Meaning / recommended
ckpt_name	RIFE weights rife40…rife49. rife47 / rife49 are the recommended ones.
multiplier	integer fps multiple. multiplier = target_fps / source_fps (24→48 = 2; 24→96 = 4). Use 2 for the standard "double the smoothness" pass.
clear_cache_after_n_frames	lower it (e.g. 10) if you OOM on long clips
fast_mode	no effect from RIFE 4.5+ (contextnet removed) — leave default
ensemble	slightly higher quality, slower

After interpolation, set the encode node's fps to source_fps × multiplier so playback speed is unchanged (only smoother).

Alternatives in the same pack: FILM VFI (Google FILM, strong on large motion, heavier), plus GMFSS Fortuna VFI, STMFNet VFI/FLAVR VFI (these last two need ≥4 input frames), IFRNet, M2M, AMT, etc. There is no "GIMM-VFI" node in this pack. If a workflow asks for GIMM-VFI it's a separate custom node; verify it's installed before citing it. Default to RIFE; reach for FILM when RIFE smears fast motion.

About "RIFE 56"

The user's "RIFE 56" is shorthand, not a RIFE model version. RIFE in this pack tops out at 4.9 (rife49). It almost certainly means RIFE targeting ~56 fps (i.e. a multiplier chosen so the output lands near 56 fps, e.g. 24 fps × 2 ≈ 48, or a ~2.3× target), or a RIFE-resample node that takes a target fps directly. Map it to RIFE VFI (4.0 - 4.9), ckpt rife47/rife49, multiplier = round(56 / source_fps) (multiplier 2 from 24/25/30 fps). Confirm the intended output fps with the user rather than chasing a non-existent "RIFE 56" model.

---

2x vs 4x

• 2x is the safest default; it pairs with the downscale-first trick (downscale 0.5×, then 2x back recovers original size but restored). Lower VRAM, fewer artifacts.
• 4x is for small sources or when you need a big jump; FlashVSR's recommended factor. Costs ~4× the pixels, so expect VAE tiling / block swap.
• With SeedVR2 you don't pick a literal "2x/4x"; you set the target short-edge resolution and the effective factor falls out of input vs target size.

---

VRAM tiers

VRAM	SeedVR2	FlashVSR	Interp / encode
8 GB or less	3B GGUF Q4_K_M + blocks_to_swap = max + VAE tiling; small batch (1–5)	Tiny Long + enable_tiling	RIFE multiplier 2; low clear_cache_after_n_frames; encode in chunks
12–16 GB	3B/7B fp8 + some block swap or VAE tiling; batch 5–13	Tiny or Full + tiling	RIFE 2–4×; ensemble off
24 GB+	7B fp16 (or 3B fp16), no offload; batch 13–45 for max temporal stability	Full at 4x	RIFE 2–4× + ensemble; FILM if needed

General: downscale first to buy a bigger batch; always clear_vram before switching model families; reduce frame/batch counts first when you OOM.

---

Gotchas

• Temporal flicker is the #1 video-upscale failure. Cause: per-frame (non-temporal) upscaling or too-small a SeedVR2 batch_size. Fix: use a temporal model (SeedVR2/FlashVSR), raise batch_size (next 4n+1 up), and don't downscale so hard the model has nothing to lock onto frame-to-frame.
• Frame-count constraints: SeedVR2 batch_size must be 4n+1; FlashVSR needs ≥21 frames; STMFNet/FLAVR interp need ≥4 frames. A clip shorter than the batch/min will error or degrade.
• Color shift / brightness drift after restore is common with diffusion restorers. Mitigate: don't over-downscale; if it persists, do a color-match pass against the source (e.g. an essentials/ImageBlend-style match) before encode, and check pixel format (yuv420p) at encode.
• Audio passthrough: core SaveVideo/CreateVideo drop audio. Use VHS_VideoCombine (VideoHelperSuite) and feed it the audio from GetVideoComponents / VHS_LoadVideo to keep the original track.
• fps after interpolation: set the encoder fps to source_fps × multiplier, not the source fps, or the video plays in slow motion.
• ffmpeg is required for muxing (same as the LTX skill): if CreateVideo / SaveVideo / VHS_VideoCombine error with "ffmpeg could not be found", run <comfy-venv>/python -m pip install imageio-ffmpeg and reboot.
• Models auto-download on first run for SeedVR2 and FlashVSR. The first generation stalls while it pulls multi-GB weights; that's expected.
• Order matters: restore/upscale BEFORE interpolation. Interpolating first then upscaling doubles the restorer's workload and can lock in interpolation smear.

---

Classic baseline (the user's proven recipe)

The user's older, battle-tested pipeline, still solid, is:

DOWNSCALE the video first → SeedVR2 → RIFE ("RIFE 56").

That is exactly the structure the recommended 2026 pipeline above preserves: downscale-first to give the restorer clean input and VRAM headroom, SeedVR2 for the temporal restore/upscale, RIFE for the fps bump. The only modernizations:

• Use the current ComfyUI-SeedVR2_VideoUpscaler node pack (4-node: DiT loader + VAE loader + [torch compile] + upscaler) with the 3B fp8 model as the default and batch_size raised for temporal stability.
• Read "RIFE 56" as RIFE targeting ~56 fps (a multiplier, typically 2 from 24/25/30 fps), using rife47/rife49, not a literal model version.
• Consider FlashVSR as a faster drop-in for the SeedVR2 stage when speed matters more than maximum fidelity.

---

Packs

No dedicated video-upscale installer pack ships yet. To build one (see the installer-packs skill), the manifest's custom_nodes[] should pull numz/ComfyUI-SeedVR2_VideoUpscaler, Fannovel16/ComfyUI-Frame-Interpolation, and Kosinkadink/ComfyUI-VideoHelperSuite (already installed), optionally 1038lab/ComfyUI-FlashVSR. SeedVR2 and FlashVSR weights auto-download on first run, so models[] can be left light; record that in pack.yaml. Install nodes ad-hoc with panel_install_node or apply a manifest with apply_manifest. Offer to contribute a finished pack upstream (github.com/artokun/comfyui-mcp).

Sources

• Official: none found.
• Empirical: sampler values, wiring, and prompt notes from working graphs in packs/ and observed renders; not a vendor prompting guide.