MiniMax H3 Upscaling Guide · Verified Aug 23, 2026

MiniMax H3 Latent Upscaler: Download, ComfyUI Workflow & 2K Guide

MiniMax H3 latent upscaling is a local workflow for increasing or refining H3 video output inside the generation pipeline. This guide explains what the H3 Latent Upscaler is, where to get the verified model or workflow, how to use it in ComfyUI, what hardware it needs, and why it is not the same as MiniMax's official H3-Regenerate-2K stage.

Direct answer

What Is the MiniMax H3 Latent Upscaler?

The MiniMax H3 Latent Upscaler is a local ecosystem workflow used to increase or refine H3 video output in latent space before final decoding. It is commonly used with node-based H3 workflows such as ComfyUI. The latent upscaler is not the same component as MiniMax's official H3-Regenerate-2K stage: one is a local ecosystem refinement route, while the other belongs to MiniMax's official multi-stage H3 pipeline.

  • Local ecosystem
  • ComfyUI-compatible workflow
  • Not H3-Regenerate-2K
  • Verified Aug 23, 2026

Verified source

MiniMax H3 Latent Upscaler Download

Use the original or currently verified MiniMax H3 Latent Upscaler repository or model source rather than downloading an unexplained mirror. The exact model file, loader and workflow must match the implementation being documented on this page.

Original repository

MiniMax H3 Latent Upscaler

Source
rockerBOO/h3-latent-upscaler
Type
Community / ecosystem implementation
Format
Python ComfyUI custom nodes + JSON example workflows
ComfyUI support
Yes — FL2VA and Ref2VA example graphs
Last verified
Aug 23, 2026
Open Original Source

Which H3 Latent Upscaler File Should You Download?

Which H3 Latent Upscaler File Should You Download?

Download the file specified by the workflow or repository you actually plan to use. MiniMax H3 upscaler implementations can differ in model format, loader requirements and ComfyUI nodes. Do not mix a model from one implementation with installation instructions from another unless the maintainers explicitly document compatibility.

Key H3 distinction

MiniMax H3 Latent Upscaler vs H3-Regenerate-2K

MiniMax H3 Latent Upscaler compared with H3-Regenerate-2K
H3 Latent UpscalerH3-Regenerate-2K
Main roleLocal latent-space upscale / refinementOfficial 2K regeneration stage
H3-Base checkpointSeparate from H3-BaseSeparate stage
Official MiniMax pipeline componentNo / ecosystem implementationYes
Typical environmentComfyUI / local ecosystemMiniMax official H3 pipeline
Local controlHighNot the same local-open path
Main goalIncrease/refine local outputProduce official regenerated 2K result
Same technology?NoNo

MiniMax H3 Latent Upscaler and H3-Regenerate-2K are different technologies. A latent upscaler modifies or reprocesses an H3 workflow in latent space, while H3-Regenerate-2K is the dedicated regeneration stage in MiniMax's official H3-Context-IR → H3-Base → H3-Regenerate-2K architecture. Similar output resolution does not make the two generation paths equivalent.

MiniMax H3 Latent Upscaler — Quick Facts

MiniMax H3 Latent Upscaler quick facts
FactAnswer
Primary purposeLocal resolution / detail refinement
Typical environmentComfyUI
Same as H3-Base?No
Same as H3-Regenerate-2K?No
Can increase output resolution?Yes, depending on implementation
Can guarantee better temporal quality?No
Can repair broken motion?Not reliably
Can repair identity drift?Not reliably
Hardware requirementImplementation-dependent
Official 2K replacementNo

MiniMax H3 Latent Upscaler in ComfyUI

ComfyUI is a natural environment for MiniMax H3 latent upscaling because the upscaler can be inserted directly into an existing H3 node graph. The exact model loader, node names and file paths depend on the upscaler implementation, so use the workflow associated with the verified source rather than combining unrelated instructions.

How to Use the MiniMax H3 Latent Upscaler

  1. Step 1 — Load MiniMax H3

    Start with the H3 model and task family required by the verified workflow.

  2. Step 2 — Create the Base Generation

    Generate the base H3 latent or video result before the upscaling stage.

  3. Step 3 — Route the Correct Latent Representation

    Connect the output expected by the verified latent-upscaler implementation. Do not assume that every decoded video can simply be connected to a latent node.

  4. Step 4 — Load the Verified Upscaler

    Use the exact model, node or loader documented by the implementation source.

  5. Step 5 — Choose the Target Upscale Configuration

    Select only a resolution or scale that your hardware can support.

  6. Step 6 — Run the Upscale Stage

    Process the existing H3 output through the latent-upscaling portion of the graph.

  7. Step 7 — Decode the Result

    Convert the refined latent representation into the final video output.

  8. Step 8 — Compare Against the Base

    Check whether detail improved without introducing new flicker, identity drift, halos or temporal instability.

Open MiniMax H3 ComfyUI Guide

Where Does the H3 Latent Upscaler Fit?

Prompt / Reference Inputs
          ↓
     MiniMax H3-Base
          ↓
   Base H3 Generation
          ↓
     Latent Upscaler
          ↓
Higher-Resolution Latent
          ↓
         Decode
          ↓
     Final Video
H3-Context-IR
      ↓
   H3-Base
      ↓
H3-Regenerate-2K

These are different workflows. The first represents a local ecosystem latent-upscaling route. The second represents MiniMax's official H3 architecture.

MiniMax H3 Latent Upscaler Requirements

The H3 Latent Upscaler's memory requirement depends on the implementation, target resolution, number of frames, H3 model format, GPU architecture and offloading strategy. Adding a higher-resolution latent stage can increase memory pressure because larger latent tensors and additional model components must be processed. Do not publish one universal upscaler VRAM minimum without a reproducible benchmark.

MiniMax H3 Latent Upscaler requirements
RequirementGuidance
GPUDepends on base H3 workflow and upscaler
VRAMNo universal verified minimum
System RAMMore important when offloading
StorageDepends on H3 + upscaler model files
ComfyUICommon local environment
NVMe SSDHelpful for heavy offloading
Base H3 workflowRequired before latent refinement
Check MiniMax H3 Hardware

Does the H3 Latent Upscaler Need More VRAM?

Does the H3 Latent Upscaler Need More VRAM?

It can. Adding a latent-upscaling stage can increase MiniMax H3 memory use because higher-resolution tensors and additional model components may need to remain active during the workflow. The exact increase is implementation-specific. Target resolution, frame count, model precision and CPU offloading can change the result, so one upscaler benchmark should not be converted into a universal VRAM requirement.

Can the MiniMax H3 Latent Upscaler Create 2K Video?

A MiniMax H3 latent-upscaler workflow can produce higher-resolution output, including 2K-class dimensions when the implementation supports them, but that should not be described as the same process as MiniMax's official H3-Regenerate-2K stage. Pixel dimensions and generation method are separate questions. A locally upscaled 2K video and an officially regenerated H3 2K video can reach similar dimensions through different pipelines.

  • Resolution ≠ generation method

Does 2K Mean Better MiniMax H3 Quality?

No. Higher resolution does not automatically mean higher generation quality. An H3 latent upscaler can increase spatial detail or output dimensions, but it cannot guarantee better motion, character identity, text rendering, physics or temporal coherence. If the base H3 generation is structurally wrong, upscaling can produce a sharper version of the same mistake.

What Can the MiniMax H3 Latent Upscaler Improve?

Edge Detail

Cleaner object boundaries when the base H3 generation is already stable.

Texture Detail

More apparent detail in hair, fabric, architecture and environmental surfaces.

Perceived Sharpness

Higher-resolution decoding can improve perceived spatial detail.

Large-Screen Output

Higher pixel dimensions can be more suitable for desktop and larger displays.

Editing Headroom

Higher-resolution output can provide more pixels for downstream editing and compression.

What Can't the H3 Latent Upscaler Reliably Fix?

Broken Motion

Incorrect motion remains a generation problem rather than a simple resolution problem.

Identity Drift

Additional detail cannot reliably reconstruct identity information already lost between frames.

Temporal Flicker

Spatial upscaling does not automatically repair inconsistent information across time.

Broken Text

Upscaling distorted text can make the distortion sharper rather than correct it.

Bad Physics

Incorrect object movement is not repaired simply by increasing latent resolution.

Bad Composition

Upscaling does not reframe an incorrectly composed shot.

When Should You Use the MiniMax H3 Latent Upscaler?

  • The base H3 video already has stable motion
  • Character identity is already consistent
  • Composition is correct
  • You need more spatial detail
  • You need a higher-resolution local result
  • Your hardware has additional memory headroom
  • You want to continue editing inside ComfyUI

Use latent upscaling as a refinement stage after the creative structure of the H3 video is already correct.

When Should You Avoid the H3 Latent Upscaler?

  • Severe identity drift
  • Broken subject motion
  • Major temporal flicker
  • Broken anatomy
  • Incorrect camera movement
  • Text that must be precisely readable but is already malformed
  • Very noisy or damaged source video
  • Hardware already close to its memory limit

Regenerate a structurally bad H3 video before upscaling it. A better base generation usually produces a better final result than spending additional compute on a defective source.

H3 Latent Upscaler vs Traditional Video Upscaler

Latent upscaler compared with a traditional video upscaler
H3 Latent UpscalerTraditional Video Upscaler
Processing stageInside / near generation pipelineAfter video generation
Data spaceLatent representationDecoded pixels
H3 integrationTightIndependent
Requires H3 workflowUsuallyNo
General-purpose videoNo / workflow-specificUsually yes
Temporal repair guaranteedNoNo
Best useLocal H3 workflow refinementGeneral video post-processing

A latent upscaler changes the generation pipeline before final output, while a traditional video upscaler usually processes already decoded frames. Neither approach should be described as a guaranteed temporal-restoration system.

How to Evaluate a MiniMax H3 Upscale

MiniMax H3 upscale evaluation matrix
CheckWhat to CompareImprovement Means
Face detailBase vs upscaleMore detail without identity change
MotionBase vs upscaleNo new jitter
TextureBase vs upscaleMore detail without artificial noise
EdgesBase vs upscaleCleaner boundaries without halos
TextBase vs upscaleNo additional distortion
BackgroundBase vs upscaleAdded detail without flicker
Temporal consistencyEntire clipNo new frame-to-frame instability

An H3 upscale is successful only when added spatial detail does not introduce new temporal or identity artifacts. Resolution alone is not a sufficient quality metric.

MiniMax H3 Latent Upscaler: Myth vs Fact

Myth

The H3 Latent Upscaler is H3-Regenerate-2K.

Fact

They are different technologies and generation stages.

Myth

2K automatically means better H3 quality.

Fact

Higher resolution does not guarantee better motion, identity or temporal consistency.

Myth

Upscaling fixes bad motion.

Fact

Major motion errors should normally be corrected by regenerating the base video.

Myth

Upscaling restores lost facial identity.

Fact

Added detail cannot reliably reconstruct identity that has already drifted between frames.

Myth

Every H3 upscaler uses the same model and nodes.

Fact

Implementations can differ in model files, loaders and ComfyUI nodes.

Myth

GGUF, INT8 and latent upscaling are the same thing.

Fact

Quantization changes model representation, while latent upscaling adds a separate refinement stage.

Continue Your MiniMax H3 Local Workflow

Check Your Hardware

See whether your GPU, RAM and storage are suitable for local H3 workflows.

Install H3 in ComfyUI

Configure the node-based local generation environment.

Download H3 Models

Use verified H3 model sources and formats.

Download H3 Workflows

Choose a graph that matches your H3 task family.

Local H3 Upscaling vs Hosted MiniMax H3

Local upscaling compared with hosted MiniMax H3
Local Latent UpscalerHosted H3
Local GPURequiredNo
Model downloadsRequiredNo local model download
ComfyUI setupUsuallyNot required
Workflow controlHighLower
Memory tuningUser managedHosted
Local graph customizationYesNo local graph required
Best forTechnical local experimentationFast generation

Don't Want to Configure the H3 Latent Upscaler?

You do not need a local latent-upscaler workflow to generate MiniMax H3 video. Local upscaling gives you more control over the ComfyUI pipeline, while hosted H3 removes the need to download large model files, configure upscaling nodes or troubleshoot GPU memory. Choose the local route when you want workflow control; choose hosted H3 when you want the shortest path from prompt to video.

Hosted H3 alternative

Generate MiniMax H3 Online

Generate MiniMax H3 without downloading local model files or configuring a latent-upscaler workflow. The hosted generator runs the supported H3 workflow on remote infrastructure, so your browser does not need to supply the model VRAM.

0/2500
768pRecommended

Recommended for testing prompts and first drafts.

2K output is available on the 2K tier only.

5s
Est. cost: ~30 creditsBalance: — credits

Checking your account…

OutputVideo
History
MiniMax H3 AI video: ocean cliffs at golden hour aerialMiniMax H3 Text to Video sample

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Vintage Binocular Brand Film AI video previewProduct Ads

Vintage Binocular Brand Film

Product Ads
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“Use Images 1–4 as sequential keyframes, seen through a vintage binocular viewfinder searching for the MINIMAX installation. Open out of focus with subtle handheld shake, then push in quickly and rack focus onto Image 1. Between keyframes, use fast binocular-scan transitions with whip movement, motion blur, optical smearing, and brief exposure flicker. Cut at peak blur, then settle and snap back into focus. Keep the twin circular lens mask absolutely fixed throughout: identical position, scale, feathered black vignette, and edge softness, with no warping or drift. Only the image inside the mask may move. In Image 2, let the fabric move gently in the wind while the MINIMAX lettering follows the folds and remains legible. In Image 3, the subject should feel like a stylish passerby caught by chance, walking, turning, and swinging their arms naturally. In Image 4, the subject adjusts their glasses or lifts their chin slightly with a cool, effortless fashion-campaign attitude. Red typography should resolve with the focus: begin slightly blurred and at low opacity, then fade into clarity over 0.3–0.5 seconds. A subtle vertical slide or slight tracking expansion is allowed. Fade it out before the next transition or let motion blur carry it away. No spins, bounces, or large fly-ins/outs. Visual language: a voyeuristic, Wes Anderson-inspired 35 mm film look with fine grain, soft highlight halation, restrained color, and red typographic accents. Minimal, premium, lightly playful. Do not add people, vehicles, buildings, or logos. Preserve the core composition and the MINIMAX installation exactly. PRODUCTION CONTROL MODE: Reference to Video. Assign Images 1–4 only as sequential visual anchors. TIMELINE: 0–3s search and rack focus; 3–10s two fast scan transitions; 10–15s settle on the final mark. CONTINUITY LOCKS: the twin circular mask, vignette softness and installation lettering never change geometry. CAMERA: handheld micro-shake inside the mask only; cut at peak motion blur. AUDIO: wind, cloth movement and two short optical whooshes; restrained low pulse, no dominant score. END FRAME: hold the final mark sharp for one second. AVOID: mask drift, melted text, cross-dissolves and extra subjects.”

View full prompt

Use Images 1–4 as sequential keyframes, seen through a vintage binocular viewfinder searching for the MINIMAX installation. Open out of focus with subtle handheld shake, then push in quickly and rack focus onto Image 1. Between keyframes, use fast binocular-scan transitions with whip movement, motion blur, optical smearing, and brief exposure flicker. Cut at peak blur, then settle and snap back into focus. Keep the twin circular lens mask absolutely fixed throughout: identical position, scale, feathered black vignette, and edge softness, with no warping or drift. Only the image inside the mask may move. In Image 2, let the fabric move gently in the wind while the MINIMAX lettering follows the folds and remains legible. In Image 3, the subject should feel like a stylish passerby caught by chance, walking, turning, and swinging their arms naturally. In Image 4, the subject adjusts their glasses or lifts their chin slightly with a cool, effortless fashion-campaign attitude. Red typography should resolve with the focus: begin slightly blurred and at low opacity, then fade into clarity over 0.3–0.5 seconds. A subtle vertical slide or slight tracking expansion is allowed. Fade it out before the next transition or let motion blur carry it away. No spins, bounces, or large fly-ins/outs. Visual language: a voyeuristic, Wes Anderson-inspired 35 mm film look with fine grain, soft highlight halation, restrained color, and red typographic accents. Minimal, premium, lightly playful. Do not add people, vehicles, buildings, or logos. Preserve the core composition and the MINIMAX installation exactly. PRODUCTION CONTROL MODE: Reference to Video. Assign Images 1–4 only as sequential visual anchors. TIMELINE: 0–3s search and rack focus; 3–10s two fast scan transitions; 10–15s settle on the final mark. CONTINUITY LOCKS: the twin circular mask, vignette softness and installation lettering never change geometry. CAMERA: handheld micro-shake inside the mask only; cut at peak motion blur. AUDIO: wind, cloth movement and two short optical whooshes; restrained low pulse, no dominant score. END FRAME: hold the final mark sharp for one second. AVOID: mask drift, melted text, cross-dissolves and extra subjects.

Epic Space Opera Teaser AI video previewCinematic

Epic Space Opera Teaser

Cinematic
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“Epic theatrical space-opera teaser Keep the pace fast and the scale enormous without letting the edit drag. Use sharp hard cuts, a shaking command deck, white-hot flashes, split-second black frames, and a violent jump-to-warp impact. Title cards should use wide-tracked cinematic typography—not pure white—with restrained material texture, subtle illumination, and a faint edge glow. Animate the titles by emerging from deep-space shadow, catching a sweep of starlight, opening their letter spacing, leaving a slight afterimage, and flashing briefly against black. PRODUCTION CONTROL MODE: First & Last Frame. SHOT BUDGET: maximum four shots. TIMELINE: 0–3s command-deck disturbance; 3–7s gateway reveal; 7–11s jump-to-warp impact; 11–15s title on black. CAMERA: one primary movement per shot. TEXT LOCK: exact title copy, centered, wide-tracked, fully readable for at least 24 frames. AUDIO: sub-bass rise, one metallic impact at the warp cut, then a short vacuum drop. AVOID: extra title cards, soft dissolves, pure-white typography and constant camera shake.”

View full prompt

Epic theatrical space-opera teaser Keep the pace fast and the scale enormous without letting the edit drag. Use sharp hard cuts, a shaking command deck, white-hot flashes, split-second black frames, and a violent jump-to-warp impact. Title cards should use wide-tracked cinematic typography—not pure white—with restrained material texture, subtle illumination, and a faint edge glow. Animate the titles by emerging from deep-space shadow, catching a sweep of starlight, opening their letter spacing, leaving a slight afterimage, and flashing briefly against black. PRODUCTION CONTROL MODE: First & Last Frame. SHOT BUDGET: maximum four shots. TIMELINE: 0–3s command-deck disturbance; 3–7s gateway reveal; 7–11s jump-to-warp impact; 11–15s title on black. CAMERA: one primary movement per shot. TEXT LOCK: exact title copy, centered, wide-tracked, fully readable for at least 24 frames. AUDIO: sub-bass rise, one metallic impact at the warp cut, then a short vacuum drop. AVOID: extra title cards, soft dissolves, pure-white typography and constant camera shake.

Desert Fashion Campaign AI video previewFashion

Desert Fashion Campaign

Fashion
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“Create a premium 16:9 landscape fashion film. Use Image 1 for the overall mood, location, and film texture; Image 2 for the talent; Image 3 for the bag; and Image 4 for the closing brand mark. This is a fashion campaign for the clothing and bag. The tone is elevated, cool, and restrained, but the edit should still feel lively and fashion-forward—not like a conventional narrative film or an e-commerce ad. Keep the story simple: beside a vintage car on a desert highway, a woman walks to the rear of the car, opens the trunk, takes out a black bag, shares a quiet beat with the man standing nearby, then leaves carrying the bag. Integrate the clothing and bag naturally into the performance so they feel like part of the characters’ identity. PRODUCTION CONTROL MODE: Reference to Video. Image 1 controls desert location and film texture; Image 2 the woman; Image 3 the black bag; Image 4 the closing mark. ACTION ORDER: approach trunk → open trunk → lift bag by its handle → brief eye contact → walk away. CAMERA: three restrained editorial setups, never more than one move per setup. PRODUCT LOCK: preserve bag silhouette, material, hardware and color. AUDIO: desert wind, trunk latch, footsteps on gravel; minimal music. END FRAME: clean brand mark after the walk-away. AVOID: extra products, wardrobe swaps and e-commerce turntable shots.”

View full prompt

Create a premium 16:9 landscape fashion film. Use Image 1 for the overall mood, location, and film texture; Image 2 for the talent; Image 3 for the bag; and Image 4 for the closing brand mark. This is a fashion campaign for the clothing and bag. The tone is elevated, cool, and restrained, but the edit should still feel lively and fashion-forward—not like a conventional narrative film or an e-commerce ad. Keep the story simple: beside a vintage car on a desert highway, a woman walks to the rear of the car, opens the trunk, takes out a black bag, shares a quiet beat with the man standing nearby, then leaves carrying the bag. Integrate the clothing and bag naturally into the performance so they feel like part of the characters’ identity. PRODUCTION CONTROL MODE: Reference to Video. Image 1 controls desert location and film texture; Image 2 the woman; Image 3 the black bag; Image 4 the closing mark. ACTION ORDER: approach trunk → open trunk → lift bag by its handle → brief eye contact → walk away. CAMERA: three restrained editorial setups, never more than one move per setup. PRODUCT LOCK: preserve bag silhouette, material, hardware and color. AUDIO: desert wind, trunk latch, footsteps on gravel; minimal music. END FRAME: clean brand mark after the walk-away. AVOID: extra products, wardrobe swaps and e-commerce turntable shots.

Cyber-Grunge Fashion Film AI video previewCinematic

Cyber-Grunge Fashion Film

Cinematic
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“Use Image 1 as the reference for texture and mood, and Image 2 for the subject’s appearance. Generate a 15-second, 16:9 fashion short. Preserve the subject’s identity: long platinum-blonde hair, narrow black vintage sunglasses, a glossy black patent-leather trench coat, a cool, self-assured expression, and orange firelight reflected across the coat. Style: fast-cut fashion film on analog stock, set against a nighttime blaze with black smoke and orange-red flames. Layer in VHS glitches, CCTV signal interruptions, 1990s film grain, scanlines, chromatic aberration, light leaks, flash-to-white transitions, and subtle frame jitter. PRODUCTION CONTROL MODE: Reference to Video. Image 1 controls texture and fire-lit mood; Image 2 controls identity, hair, sunglasses and coat. TIMELINE: 0–4s close-up identity lock; 4–10s two fashion poses with hard cuts; 10–15s walking hero shot. EFFECT RULE: glitches may affect signal and background, not facial geometry or garment construction. CAMERA: handheld 35mm language with two deliberate flash cuts. AUDIO: fire crackle, low industrial beat and one tape-stop accent. AVOID: face replacement, coat color changes, continuous glitch overlays and unreadable silhouettes.”

View full prompt

Use Image 1 as the reference for texture and mood, and Image 2 for the subject’s appearance. Generate a 15-second, 16:9 fashion short. Preserve the subject’s identity: long platinum-blonde hair, narrow black vintage sunglasses, a glossy black patent-leather trench coat, a cool, self-assured expression, and orange firelight reflected across the coat. Style: fast-cut fashion film on analog stock, set against a nighttime blaze with black smoke and orange-red flames. Layer in VHS glitches, CCTV signal interruptions, 1990s film grain, scanlines, chromatic aberration, light leaks, flash-to-white transitions, and subtle frame jitter. PRODUCTION CONTROL MODE: Reference to Video. Image 1 controls texture and fire-lit mood; Image 2 controls identity, hair, sunglasses and coat. TIMELINE: 0–4s close-up identity lock; 4–10s two fashion poses with hard cuts; 10–15s walking hero shot. EFFECT RULE: glitches may affect signal and background, not facial geometry or garment construction. CAMERA: handheld 35mm language with two deliberate flash cuts. AUDIO: fire crackle, low industrial beat and one tape-stop accent. AVOID: face replacement, coat color changes, continuous glitch overlays and unreadable silhouettes.

Retro Anime Crime Title Sequence AI video previewCinematic

Retro Anime Crime Title Sequence

Cinematic
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“Create a 15-second, 16:9 opening-title sequence for a stylish crime mystery. Draw from retro Japanese animation titles, hard-edged silhouettes, comic-book collage, asymmetric split screens, bold geometric color fields, English credit typography, sparse katakana accents, and a noir-jazz sensibility. Aim for 60% suspense and 40% jazz: mysterious, cool, agile, and urban—never horror, heavy drama, or a cheerful jazz music video. Build the sequence as motion-graphics collage: linework appears over black, split-screen boundaries snap into place, then color blocks and frames assemble piece by piece. Character silhouettes, prop close-ups, and English credits slide, pop, and reveal through masks on the beat. Keep it designed and graphic, not like conventional narrative animation. Credits must be clean and legible. Animate thin frames drawing on, names sliding in, letters appearing one at a time, or color blocks revealing type, then hold briefly. Do not introduce Chinese text, garbled characters, or misspellings. Each role and each name appears once only; do not assign multiple roles to the same name. Vary the transitions: circular vinyl-record wipes, vertical car-door cuts, long character shadows wiping frame, red-line slices, oversized letter masks, split-screen reconfigurations, hard color-block cuts, and tiled frames snapping into place. Keep every transition crisp, rhythmic, suspenseful, and collage-driven. No soft dissolves or fluid morphs. BGM: an original 15-second title cue, 60% suspense and 40% jazz. Use a low drone, tense string pizzicato, cool synth pulses, low kick, sparse brushwork, fragments of walking bass, short baritone-sax phrases, and clipped brass accents. Build suspense with low frequencies and hi-hat in the first 2 seconds; bring in the low beat at 3 seconds, jazz-bass movement at 6 seconds, and a short sax/brass riff at 10 seconds. Freeze the final 2 seconds on a tense chord and drum hit. Keep it mysterious and criminally cool, never upbeat, and do not imitate an existing melody. PRODUCTION CONTROL MODE: Reference to Video. Images 1–5 define graphic language, character silhouettes, palette and credit layout; do not combine identities across references. SHOT PLAN: black-and-white linework → geometric split-screen assembly → prop close-ups → final ensemble title. TYPOGRAPHY LOCK: exact English credit strings supplied in the prompt, one credit per card, minimum one-second hold. MOTION: masks, slides and snap cuts on beat; no fluid morphing. AUDIO: brushed drums, upright bass and clipped brass accents. AVOID: narrative lip sync, 3D rendering, horror imagery and decorative fake text.”

View full prompt

Create a 15-second, 16:9 opening-title sequence for a stylish crime mystery. Draw from retro Japanese animation titles, hard-edged silhouettes, comic-book collage, asymmetric split screens, bold geometric color fields, English credit typography, sparse katakana accents, and a noir-jazz sensibility. Aim for 60% suspense and 40% jazz: mysterious, cool, agile, and urban—never horror, heavy drama, or a cheerful jazz music video. Build the sequence as motion-graphics collage: linework appears over black, split-screen boundaries snap into place, then color blocks and frames assemble piece by piece. Character silhouettes, prop close-ups, and English credits slide, pop, and reveal through masks on the beat. Keep it designed and graphic, not like conventional narrative animation. Credits must be clean and legible. Animate thin frames drawing on, names sliding in, letters appearing one at a time, or color blocks revealing type, then hold briefly. Do not introduce Chinese text, garbled characters, or misspellings. Each role and each name appears once only; do not assign multiple roles to the same name. Vary the transitions: circular vinyl-record wipes, vertical car-door cuts, long character shadows wiping frame, red-line slices, oversized letter masks, split-screen reconfigurations, hard color-block cuts, and tiled frames snapping into place. Keep every transition crisp, rhythmic, suspenseful, and collage-driven. No soft dissolves or fluid morphs. BGM: an original 15-second title cue, 60% suspense and 40% jazz. Use a low drone, tense string pizzicato, cool synth pulses, low kick, sparse brushwork, fragments of walking bass, short baritone-sax phrases, and clipped brass accents. Build suspense with low frequencies and hi-hat in the first 2 seconds; bring in the low beat at 3 seconds, jazz-bass movement at 6 seconds, and a short sax/brass riff at 10 seconds. Freeze the final 2 seconds on a tense chord and drum hit. Keep it mysterious and criminally cool, never upbeat, and do not imitate an existing melody. PRODUCTION CONTROL MODE: Reference to Video. Images 1–5 define graphic language, character silhouettes, palette and credit layout; do not combine identities across references. SHOT PLAN: black-and-white linework → geometric split-screen assembly → prop close-ups → final ensemble title. TYPOGRAPHY LOCK: exact English credit strings supplied in the prompt, one credit per card, minimum one-second hold. MOTION: masks, slides and snap cuts on beat; no fluid morphing. AUDIO: brushed drums, upright bass and clipped brass accents. AVOID: narrative lip sync, 3D rendering, horror imagery and decorative fake text.

Hand-Drawn Kitchen Creature AI video previewCinematic

Hand-Drawn Kitchen Creature

Cinematic
Model
MiniMax H3
Duration
5 seconds
Resolution
768p
Aspect ratio
16:9

“15 seconds, 16:9 landscape. Blend live-action footage of a small kitchen at dusk with hand-drawn luminous animation. The last sunset light lingers at the window. The lived-in kitchen contains an old wooden table, a half-washed mug, a lightly fogged glass bottle, and a hanging dish towel. Shoot as if someone is filming one-handed on a phone: subtle hand tremor, hesitant close-focus pulls, backlit exposure breathing, and slightly coarse noise in the shadows. It should feel like an astonishing event captured in a rush at home, not a carefully dressed commercial. Do not show giant eyes, split mouths, fangs, threatening behavior, lunges, sudden black frames, or jump scares. Use only room tone, cloth friction, a soft mug clink, faucet drips, the camera operator’s footsteps and quiet breathing, plus gentle electronic tones and tiny vocalizations from the drawn creatures. PRODUCTION CONTROL MODE: Text to Video. TIMELINE: 0–4s hesitant kitchen discovery; 4–9s luminous creature crosses the table; 9–13s it reacts to a mug clink; 13–15s operator steadies the phone. CAMERA: one-handed phone, delayed autofocus and exposure breathing. SOUND: room tone, faucet drip, cloth friction, mug clink, footsteps and breathing; only tiny electronic creature tones, no score. CONTINUITY: kitchen layout and sunset direction remain stable. AVOID: giant eyes, fangs, lunges, jump cuts to black and studio lighting.”

View full prompt

15 seconds, 16:9 landscape. Blend live-action footage of a small kitchen at dusk with hand-drawn luminous animation. The last sunset light lingers at the window. The lived-in kitchen contains an old wooden table, a half-washed mug, a lightly fogged glass bottle, and a hanging dish towel. Shoot as if someone is filming one-handed on a phone: subtle hand tremor, hesitant close-focus pulls, backlit exposure breathing, and slightly coarse noise in the shadows. It should feel like an astonishing event captured in a rush at home, not a carefully dressed commercial. Do not show giant eyes, split mouths, fangs, threatening behavior, lunges, sudden black frames, or jump scares. Use only room tone, cloth friction, a soft mug clink, faucet drips, the camera operator’s footsteps and quiet breathing, plus gentle electronic tones and tiny vocalizations from the drawn creatures. PRODUCTION CONTROL MODE: Text to Video. TIMELINE: 0–4s hesitant kitchen discovery; 4–9s luminous creature crosses the table; 9–13s it reacts to a mug clink; 13–15s operator steadies the phone. CAMERA: one-handed phone, delayed autofocus and exposure breathing. SOUND: room tone, faucet drip, cloth friction, mug clink, footsteps and breathing; only tiny electronic creature tones, no score. CONTINUITY: kitchen layout and sunset direction remain stable. AVOID: giant eyes, fangs, lunges, jump cuts to black and studio lighting.

MiniMax H3 Latent Upscaler FAQ

1. What is the MiniMax H3 Latent Upscaler?

The MiniMax H3 Latent Upscaler is a local ecosystem workflow used to increase or refine H3 output in latent space before final decoding. It is distinct from MiniMax's official H3-Regenerate-2K stage and should not be presented as the same technology.

2. Where can I download the MiniMax H3 Latent Upscaler?

Use the original or currently verified repository or model source associated with the H3 latent-upscaler workflow you intend to run. Avoid unexplained mirrors, because model format, loaders and ComfyUI nodes can differ between implementations.

3. Is the MiniMax H3 Latent Upscaler official?

The commonly discussed local H3 latent-upscaler workflow belongs to the broader H3 ecosystem rather than the original H3-Base checkpoint release. Identify the exact implementation instead of labeling every H3 upscaler as an official MiniMax component.

4. Is it the same as H3-Regenerate-2K?

No. H3-Regenerate-2K is the dedicated regeneration stage in MiniMax's official H3 pipeline. A latent upscaler is a separate local refinement workflow.

5. Can the H3 Latent Upscaler create 2K video?

A supported latent-upscaler workflow can produce higher-resolution output, including 2K-class dimensions depending on the implementation, but this is not the same generation method as MiniMax's official H3-Regenerate-2K workflow.

6. Does the H3 Latent Upscaler need more VRAM?

It can. Higher-resolution latent tensors and additional model components may increase memory use. The exact requirement depends on implementation, resolution, frame count, model precision and offloading.

7. Do I need ComfyUI?

ComfyUI is a common environment for local H3 latent-upscaler workflows because the upscaler can be inserted into an existing H3 graph. The exact nodes depend on the implementation.

8. Can the upscaler fix bad motion?

Not reliably. Major motion problems should normally be fixed by regenerating the base H3 video rather than enlarging the defective output.

9. Can it fix faces?

It can improve apparent facial detail when identity is already stable, but it cannot reliably repair identity drift already present across frames.

10. Should I upscale every H3 video?

No. Upscale after confirming that motion, identity, composition and temporal consistency are already acceptable.

11. Should I regenerate or upscale a bad video?

Regenerate first when the base H3 video contains major structural errors. Upscaling usually preserves or enlarges existing problems rather than solving them.

12. Is a latent upscaler better than a traditional video upscaler?

Neither is universally better. A latent upscaler works inside or near the generation pipeline, while a traditional upscaler processes already decoded video. They solve different workflow problems.

MiniMax H3 Upscaling Glossary

Latent Space
An internal compressed representation processed by a generative model before final pixels are decoded.
Latent Upscaling
Increasing or refining the latent representation before final video decoding.
H3-Base
The core MiniMax H3 generation stage.
H3-Regenerate-2K
MiniMax's official regeneration stage in the complete H3 pipeline.
ComfyUI
A node-based interface commonly used for local generative-media workflows.
Temporal Consistency
Stability of visual information across consecutive video frames.
Identity Drift
Unwanted changes in a subject or character's identity between frames.
Spatial Detail
Fine visual information within individual frames.
Video Upscaler
A post-processing system that increases the resolution of already decoded video.

Sources & Verification

Changelog

Page changelog
DateChange
Aug 23, 2026Initial production guide; verified community source, official regeneration distinction and ComfyUI workflow references.

Related Guides

Choose Your MiniMax H3 Upscaling Route

Build the Local Workflow

Use ComfyUI when you want direct control over H3 latent upscaling, model files and local workflow configuration.

Open ComfyUI Guide

Skip the Upscaler Setup

Generate hosted MiniMax H3 video without configuring local model files, upscaling nodes or GPU memory.

Generate MiniMax H3 Online