Upscale nodes

AI upscaling, repair, enhancement, and restoration.

AI Upscale
Bit Depth Convert
Downscale 32-bit
Upscale 32-bit
Upscale By Size
Upscale Face Restore
Upscale Image
Upscale Router
Upscale Tiler
Upscale Video

AI Upscale

RadianceAIUpscale

AI-powered upscaling using neural network models. Supports tiled processing for large images.

Inputs

Input	Type	Default	Range or choices	What it does
`image`	IMAGE			Input image to upscale.
`model_name`	choice	`RealESRGAN_x4plus`	`RealESRGAN_x4plus`, `RealESRGAN_x4plus_anime_6B`, `RealESRGAN_x2plus`, `ESRGAN_4x`, `4x-UltraSharp`, `4x-AnimeSharp`, `SwinIR_4x`, `HAT_4x`, `SUPIR-v0F_fp16`, `SUPIR-v0Q_fp16`	AI upscaling model. RealESRGAN_x4plus is recommended for general use.
`mode`	choice	`Standard`	`Standard`, `Refine (HDR)`, `Normalize (HDR)`	Processing mode. 'Standard' = direct upscale. 'Refine (HDR)' = log-compression for highlights. 'Normalize (HDR)' = scales to safe range.
`tile_size`	int	512	128 to 1024, step 64	Tile size for processing. Smaller = less VRAM, slower.
`tile_overlap`	int	32	0 to 128, step 8	Overlap between tiles to avoid seams.
`auto_download`	boolean	on		Automatically download models if not found.
`unload_model` (optional)	boolean	off		Unload model from VRAM after processing to free memory.
`sdxl_model_name` (optional)	string			SUPIR only: filename of your SDXL base checkpoint (e.g. sd_xl_base_1.0_0.9vae.safetensors). Leave empty to auto-detect from the checkpoints folder. Ignored for all non-SUPIR models.
`supir_prompt` (optional)	string		multi-line text	SUPIR only: text description for SUPIR upscaling. Leave empty for default conditioning. Ignored for all other models.
`vae` (optional)	VAE			Reserved for future SUPIR v2 loader support. Currently unused.
`clip` (optional)	CLIP			Reserved for future SUPIR v2 loader support. Currently unused.

Outputs

Output	Type	What it is
`image`	IMAGE	Upscaled image.
`info`	STRING	Information about the upscaling process.

Bit Depth Convert

RadianceBitDepthConvert

Convert between bit depths with professional dithering to reduce banding.

Inputs

Input	Type	Default	Range or choices	What it does
`image`	IMAGE			Input image in float32 format.
`output_depth`	choice		`32-bit Float`, `16-bit Float`, `16-bit Int`, `10-bit`, `8-bit`	Target bit depth.
`dithering` (optional)	choice	`None`	`None`, `Floyd-Steinberg`, `Ordered`, `Blue Noise`, `Random`	Dithering algorithm. Floyd-Steinberg = error diffusion, Ordered = Bayer, Blue Noise = high-frequency, Random = simple noise.
`dither_strength` (optional)	float	1	0 to 2, step 0.1	Dithering intensity. 1.0 = standard.
`seed` (optional)	int	0	0 to 18446744073709551615	Random seed for reproducible Blue Noise and Random dithering.

Outputs

Output	Type	What it is
`converted_image`	IMAGE	Image quantized to target bit depth.
`bit_depth_info`	STRING	Information about the conversion.

Downscale 32-bit

RadianceDownscale32bit

32-bit downscaling with the exact resampling kernel on GPU or CPU and an adjustable anti-aliasing prefilter.

Inputs

Input	Type	Default	Range or choices	What it does
`image`	IMAGE			Image or batch to downscale, display-encoded sRGB or linear float (see input_color_space). Values above 1.0 are kept.
`scale_factor`	float	0.5	0.01 to 1, step 0.05	Output size as a fraction of the input (rounded down, minimum 1 px).
`method`	choice		`lanczos`, `lanczos4`, `bicubic`, `mitchell`, `catrom`, `gaussian`, `bilinear`	Resampling kernel, run exactly as named on CUDA and CPU alike: lanczos, lanczos4, bicubic (Catmull-Rom), mitchell, catrom, gaussian, bilinear.
`antialiasing` (optional)	float	0.5	0 to 1, step 0.05	Width of the downscaling prefilter. 0.5 = the kernel's textbook width (stretched by the scale factor), 0 = no prefilter (sharpest, aliases and moires), 1 = twice as wide (softest). pre_blur adds a Gaussian on top.
`pre_blur` (optional)	float	0	0 to 2, step 0.1	Gaussian sigma in input pixels applied before downscaling to suppress aliasing and moire. 0 = off.
`process_in_linear` (optional)	boolean	on		Decode sRGB to linear before resampling and re-encode after, for gamma-correct filtering. Only acts when input_color_space is sRGB; linear/HDR input is never converted.
`use_gpu` (optional)	boolean	on		Run on CUDA when available (MPS is not used). Falls back to the CPU path, which uses the exact resampling kernels.
`input_color_space` (optional)	choice	`sRGB`	`sRGB`, `Linear`, `Auto`	Colour space of the input image. Linear skips the sRGB-linear conversion for HDR or already-linear input. Auto: Linear when any value is outside 0-1, else sRGB.

Outputs

Output	Type
`downscaled_image`	IMAGE
`width`	INT
`height`	INT

Upscale 32-bit

RadianceProUpscale

Professional 32-bit upscaler optimized for Flux with HDR support.

Inputs

Input	Type	Default	Range or choices	What it does
`image`	IMAGE			Image or batch to resize, display-encoded sRGB or linear float (see input_color_space). Alpha is resized separately.
`scale_factor`	float	2	0.1 to 8, step 0.1	Output size as a multiple of the input (rounded down to whole pixels). Below 1.0 downscales.
`preset`	choice		`Custom`, `Flux Default`, `Flux Sharp`, `Flux Smooth`, `Flux HDR`, `Flux Print`, `Flux Cinematic`, `Flux Maximum`	Custom uses the widgets below. Any other preset overrides method, sharpening, detail_enhancement and antialiasing, and the HDR/Cinematic presets force process_in_linear on.
`method` (optional)	choice		`lanczos`, `lanczos4`, `bicubic`, `mitchell`, `catrom`, `hermite`, `gaussian`, `bilinear`, `nearest`	Resampling kernel, run exactly on every path (GPU, CPU and tiled): lanczos (3 lobes), lanczos4, bicubic and catrom (Catmull-Rom), mitchell (B=C=1/3), hermite, gaussian, bilinear, nearest.
`sharpening` (optional)	float	0.3	0 to 2, step 0.05	Unsharp-mask amount applied after resizing. 0 = off, 1 = add the full detail difference once.
`sharpen_radius` (optional)	float	1	0.5 to 5, step 0.1	Gaussian sigma in output pixels for the unsharp mask. Larger sharpens coarser detail.
`detail_enhancement` (optional)	float	0.2	0 to 1, step 0.05	Multi-scale luma detail boost (blur sigmas 1, 2 and 4 px) added equally to RGB after resizing. 0 = off.
`antialiasing` (optional)	float	0.3	0 to 1, step 0.05	Edge-aware softening applied last: blends in a 1 px Gaussian blur in proportion to edge strength. 0 = off; counteracts sharpening on edges.
`input_color_space` (optional)	choice		`sRGB`, `Linear`, `Auto`	Encoding of the input. sRGB allows the linear-light conversion; Linear leaves values untouched. Auto: Linear when any value is outside 0-1 (HDR), else sRGB; the info output says which.
`process_in_linear` (optional)	boolean	on		Decode sRGB to linear before resampling and re-encode after, for gamma-correct filtering. Only acts when input_color_space is sRGB; linear/HDR input is never converted.
`use_tiles` (optional)	boolean	off		Process image in overlapping tiles to handle large images that exceed VRAM.
`tile_size` (optional)	int	512	128 to 2048, step 64	Input tile size in pixels for the tiled CPU path. Used only when tiling is on (or forced above 64 MP) and the image is larger than this.
`tile_overlap` (optional)	int	64	16 to 256, step 16	Overlap in input pixels between tiles, blended to hide seams. Tiled path only.
`output_bit_depth` (optional)	choice		`32-bit Float`, `16-bit Float`, `8-bit`	Precision of the result (always returned as float). 32-bit keeps values above 1.0; 16-bit rounds to half precision; 8-bit clamps to 0-1 and quantises to 256 levels.

Outputs

Output	Type
`upscaled_image`	IMAGE
`width`	INT
`height`	INT
`info`	STRING

Upscale By Size

RadianceUpscaleBySize

Upscale to exact dimensions with aspect ratio control.

Inputs

Input	Type	Default	Range or choices	What it does
`image`	IMAGE			Image or batch to resize, display-encoded sRGB or linear float (see input_color_space). Alpha is resized separately.
`width`	int	2048	64 to 16384, step 8	Target output width in pixels.
`height`	int	2048	64 to 16384, step 8	Target output height in pixels.
`method`	choice		`lanczos`, `lanczos4`, `bicubic`, `mitchell`, `catrom`, `hermite`, `gaussian`, `bilinear`, `nearest`	Resampling kernel, run exactly as named: lanczos (3 lobes), lanczos4, bicubic and catrom (Catmull-Rom), mitchell (B=C=1/3), hermite, gaussian, bilinear, nearest.
`maintain_aspect` (optional)	boolean	on		Keep the source aspect ratio using aspect_mode to fit the width x height box. Off resizes to exactly width x height.
`aspect_mode` (optional)	choice		`fit`, `fill`, `stretch`	With maintain_aspect on. fit: largest size inside the box. fill: smallest size covering the box (not cropped, so one side exceeds it). stretch: exactly width x height.
`sharpening` (optional)	float	0.2	0 to 2, step 0.05	Unsharp-mask amount (1 px sigma) applied after resizing. 0 = off.
`process_in_linear` (optional)	boolean	on		Decode sRGB to linear before resampling and re-encode after, for gamma-correct filtering. Only acts when input_color_space is sRGB; linear/HDR input is never converted.
`input_color_space` (optional)	choice	`sRGB`	`sRGB`, `Linear`, `Auto`	Colour space of the input. Linear skips the sRGB-to-linear conversion for HDR/linear input. Auto: Linear when any value is outside 0-1, else sRGB.

Outputs

Output	Type
`upscaled_image`	IMAGE
`final_width`	INT
`final_height`	INT

Upscale Face Restore

RadianceUpscaleFaceRestore

Restore and enhance facial detail using a face restoration model.

Inputs

Input	Type	Default	Range or choices	What it does
`images`	IMAGE			Upscaled image batch (B,H,W,C) float32.
`face_model`	choice	`auto (CodeFormer → GFPGAN → skip)`	`auto (CodeFormer → GFPGAN → skip)`, `codeformer`, `gfpgan_v1.4`, `skip (detection only)`	Face restoration model. Auto tries CodeFormer first, falls back to GFPGAN, skips if neither is available.
`fidelity_weight`	float	0.75	0 to 1, step 0.05	CodeFormer fidelity: 0 = maximum enhancement (creative), 1 = faithful to input (precise). 0.5–0.8 is recommended for most upscaled content.
`blend_radius`	int	20	0 to 80, step 4	Gaussian feather radius in pixels at face crop edge. Higher = softer transition. 0 = hard paste.
`face_pad_frac`	float	0.25	0 to 0.6, step 0.05	Extra padding around each detected face bbox (fraction of face width/height). 0.25 = 25%.
`min_face_px`	int	64	16 to 256, step 16	Smallest face (in pixels) to process. Smaller faces are skipped.
`colour_correct`	boolean	on		Apply histogram-match colour correction after restoration to cancel diffusion colour drift.
`colour_strength`	float	0.8	0 to 1, step 0.05	Strength of histogram-match correction. 1.0 = full match to input colours.
`original_images` (optional)	IMAGE			Original (pre-upscale) images for colour reference. Used by histogram-match correction. Leave disconnected to use the restored images as self-reference.

Outputs

Output	Type
`restored`	IMAGE
`face_mask`	IMAGE
`pass_info`	STRING

Upscale Image

RadianceUpscaleImage

Upscale a still image using a selected super-resolution model.

Inputs

Input	Type	Default	Range or choices	What it does
`operation`	choice	`Upscale`	`Upscale`, `Route`	Upscale: run super-resolution. Route: pass images through and output the recommended tier, content class and stats (no upscale).
`images`	IMAGE			Input image batch.
`scale` (optional)	choice	`4×`	`2×`, `4×`, `8× (tile cascade)`	Output scale. 8× runs the 4× model twice, the second pass area-downsampled by half.
`hdr_mode` (optional)	choice	`auto`	`auto`, `preserve`, `clamp`	Scene-linear / HDR handling. auto: preserve range when input exceeds 1.0, else clamp. preserve: Reinhard tonemap before SR and re-expand after (keeps highlights >1.0). clamp: legacy [0,1] (LDR).
`color_encoding` (optional)	choice	`passthrough`	`passthrough`, `linear<->sRGB`, `linear<->LogC3`	Encode scene-linear -> display (sRGB/LogC3) before SR and decode after, so the LDR-trained network sees the domain it expects. passthrough: feed pixels unchanged.
`mode` (optional)	choice	`precise`	`precise`, `creative`, `balanced`	precise: Real-ESRGAN fidelity-first. creative: diffusion detail hallucination (requires VRAM). balanced: GAN upscale + light sharpening.
`tile_size` (optional)	int	512	128 to 1024, step 64	Tile size in input pixels. Reduce if OOM.
`overlap` (optional)	int	128	32 to 256, step 32	Overlap between tiles in input pixels, blended to hide seams.
`sharpness_boost` (optional)	float	0	0 to 1, step 0.05	Unsharp mask strength applied after upscale.
`denoise_pre` (optional)	float	0	0 to 1, step 0.05	Gaussian pre-denoise strength.
`upscale_model` (optional)	UPSCALE_MODEL			Optional ComfyUI UPSCALE_MODEL; its native scale should match scale. When connected it replaces the built-in tiers (model_tier and creative mode are ignored).
`model_tier` (optional)	choice	`auto`	`auto`, `tier1_fast (Real-ESRGAN — GAN, ms/frame)`, `tier2_quality (HAT-L — transformer SOTA PSNR)`, `tier2_quality (SwinIR-L — transformer quality)`, `tier3_creative (SD x4 — diffusion hallucination)`, `tier3_creative (SeedVR2 — one-step video diffusion)`	Model tier. 'auto' selects based on content analysis.
`diffusion_steps` (optional)	int	20	1 to 50, step 1	Inference steps for Tier 3 diffusion (creative mode or a tier3 model_tier). More steps are slower; SeedVR2 is one-step.
`diffusion_noise_level` (optional)	int	20	0 to 350, step 10	SD x4 upscaler only: noise added to the low-res input. Higher lets the model invent more detail and drift further from the source.
`guidance_scale` (optional)	float	7.5	1 to 20, step 0.5	SD x4 upscaler only: classifier-free guidance toward enhancement_prompt. Higher follows the prompt more strongly.
`enhancement_prompt` (optional)	string			Text prompt for creative mode diffusion steering.
`prefer_speed` (optional)	boolean	off		Always recommend Tier 1 fast regardless of content.
`sample_frame` (optional)	int	0	0 to 9999	Index of frame to analyse (for Route operation).

Outputs

Output	Type
`image_a`	IMAGE
`image_b`	IMAGE
`info`	STRING
`data1`	STRING
`data2`	STRING

Upscale Router

RadianceUpscaleRouter

Measure noise, sharpness and saturation on one frame and recommend a model_tier for Upscale Image or Video. Heuristic statistics only; images pass through unchanged.

Inputs

Input	Type	Default	Range or choices	What it does
`images`	IMAGE			Image or frame batch to analyse; returned unchanged on the images output.
`prefer_speed`	boolean	off		Always recommend Tier 1 fast regardless of content.
`sample_frame`	int	0	0 to 9999	Index of frame to analyse (for video batches).

Outputs

Output	Type
`recommended_tier`	STRING
`content_class`	STRING
`stats_json`	STRING
`images`	IMAGE

Upscale Tiler

RadianceUpscaleTiler

Tile large images into overlapping patches for memory-safe upscaling.

Inputs

Input	Type	Default	Range or choices	What it does
`operation`	choice	`Tile`	`Tile`, `ColourFix`	Tile: tiled upscale of images (output clamped to 0-1). ColourFix: histogram-match source to reference to remove upscaler colour drift.
`images` (optional)	IMAGE			Input image batch (B,H,W,C) float32.
`scale` (optional)	choice	`4×`	`2×`, `4×`, `8× (tile cascade)`	Upscale factor. 8× uses two cascaded 4× passes.
`tile_size` (optional)	int	512	128 to 2048, step 64	Tile side in input pixels. Smaller = less VRAM.
`overlap` (optional)	int	128	32 to 512, step 32	Tile overlap in input pixels. ≥20% of tile_size recommended.
`blend_mode` (optional)	choice	`laplacian_pyramid`	`laplacian_pyramid`, `gaussian_feather`, `linear`	laplacian_pyramid: best quality. gaussian_feather: fast. linear: simple.
`upscale_model` (optional)	UPSCALE_MODEL			Any ComfyUI UPSCALE_MODEL; its native scale should match scale. Leave empty to use the built-in model chosen by model_tier.
`model_tier` (optional)	choice	`tier1_fast (Real-ESRGAN — GAN, ms/frame)`	`auto`, `tier1_fast (Real-ESRGAN — GAN, ms/frame)`, `tier2_quality (HAT-L — transformer SOTA PSNR)`, `tier2_quality (SwinIR-L — transformer quality)`, `tier3_creative (SD x4 — diffusion hallucination)`, `tier3_creative (SeedVR2 — one-step video diffusion)`	Built-in model tier when no upscale_model is connected.
`source` (optional)	IMAGE			Upscaled image with colour drift (ColourFix mode).
`reference` (optional)	IMAGE			Original pre-upscale image — colour reference (ColourFix mode).
`cf_strength` (optional)	float	1	0 to 1, step 0.05	ColourFix strength: 0 = off, 1 = full CDF match.
`n_bins` (optional)	int	512	64 to 2048, step 64	Histogram resolution (ColourFix mode).

Outputs

Output	Type
`image_a`	IMAGE
`image_b`	IMAGE
`info`	STRING

Upscale Video

RadianceUpscaleVideo

Upscale a video sequence using a selected super-resolution model.

Inputs

Input	Type	Default	Range or choices	What it does
`frames`	IMAGE			Video frame batch (B,H,W,C) float32. B = frame count.
`scale`	choice	`4×`	`2×`, `4×`, `8× (tile cascade)`	Output scale. 8× runs the 4× model twice, the second pass area-downsampled by half.
`tile_size`	int	512	128 to 1024, step 64	Spatial tile size in input pixels. Reduce if OOM.
`overlap_spatial`	int	128	32 to 256, step 32	Spatial tile overlap in input pixels.
`window_size`	int	16	4 to 64, step 4	Frames per processing batch (VRAM). Tier 1/2 models are single-image: each frame is still upscaled on its own.
`overlap_temporal`	int	4	1 to 16, step 1	Frames shared between adjacent windows. Minimum 1 for seam-free stitching.
`flow_compensation`	boolean	on		At window seams each overlap frame is upscaled twice; Lucas-Kanade flow aligns the two results before they are blended. It does not compensate camera motion between frames.
`sharpness_boost`	float	0	0 to 1, step 0.05	Unsharp-mask strength (sigma 1.5 px) applied after upscaling. 0 = off.
`upscale_model` (optional)	UPSCALE_MODEL			Optional ComfyUI UPSCALE_MODEL; its native scale should match scale. When connected it replaces model_tier.
`model_tier` (optional)	choice	`tier1_fast (Real-ESRGAN — GAN, ms/frame)`	`auto`, `tier1_fast (Real-ESRGAN — GAN, ms/frame)`, `tier2_quality (HAT-L — transformer SOTA PSNR)`, `tier2_quality (SwinIR-L — transformer quality)`, `tier3_creative (SD x4 — diffusion hallucination)`, `tier3_creative (SeedVR2 — one-step video diffusion)`	Select 'SeedVR2' for best temporal consistency on video. Requires seedvr2 or diffusers package.
`enhancement_prompt` (optional)	string			Text prompt for Tier 3 diffusion steering (e.g. 'cinematic film grain, detailed textures').
`diffusion_steps` (optional)	int	1	1 to 50, step 1	Diffusion inference steps. SeedVR2 uses 1 (one-step); SD x4 upscaler recommended 15-25.
`hdr_mode` (optional)	choice	`auto`	`auto`, `preserve`, `clamp`	Scene-linear / HDR handling. auto: preserve range when input exceeds 1.0, else clamp. preserve: Reinhard tonemap before SR and re-expand after. clamp: legacy [0,1] (LDR).
`color_encoding` (optional)	choice	`passthrough`	`passthrough`, `linear<->sRGB`, `linear<->LogC3`	Encode scene-linear -> display (sRGB/LogC3) before SR and decode after. passthrough: feed pixels unchanged.

Outputs

Output	Type
`upscaled`	IMAGE
`confidence_map`	IMAGE
`pass_info`	STRING