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H3 Long Video Prompting

H3 Long Video Prompting

Plan MiniMax H3 videos longer than 15 seconds. Splits a concept into chained segments, picks the right generation mode for each (T2VA / I2VA / FL2VA / L2VA / Ref2VA), locks global consistency anchors, and returns one ready-to-submit prompt per segment — plus audio-seam and continuity QC.
#Vidéo#Rédaction#Design
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H3 Long Video Prompting

Turn a shot idea longer than 15 seconds into a segment-by-segment plan that actually renders.

MiniMax H3 generates 15 seconds at a time. A 40-second piece is not a prompt-writing problem — it is an engineering problem: split the action, choose the right input mode per segment, hold consistency, handle the seams. This skill does that work and hands you something you can submit.


The constraint you can't prompt around

02-limit.webp
Spec Value
H3 4–15 s
H3 Max 5–15 s
Duration whole seconds only
Frame rate 24 FPS

There is no prompt trick that gets past 15 seconds. You split. How well you split decides whether the finished piece is watchable — and the usual failure isn't "not knowing how to split", it's ending up with a different face, a different colour temperature and a camera that doesn't match across cuts.


Three steps: split → choose mode → lock anchors

1 · Split

03-plan.webp
  • Each segment ≤ 15 s, whole seconds, cut on a beat of action — not in half by the clock
  • Each segment is an independent request: re-runnable on its own, so a bad segment costs one re-run
  • Number the segments inside the prompt, so the edit can't misalign later

2 · Choose the mode

04-modes.png
Mode Input Composition Use when
T2VA text only free no source media, prompt only
I2VA one first frame locked to it you have an opening still and need it to move
FL2VA first + last frame locked at both ends you need an exact landing, e.g. a specific closing pose
L2VA one last frame locked to it you only know how it ends
Ref2VA image / video / audio reference free, identity locked you must keep a face, a style or a voice

⚠️ The most common mistake: first/last frames and reference media are mutually exclusive. A single request either locks the frame, or locks identity. Writing both into one request produces an invalid request, no matter how good the prose is.

3 · Lock anchors, then write per segment

Consistency does not come from describing the face again in every segment. It comes from one anchor block reused verbatim:

  • Face, features, hair, wardrobe, accessories — written as fixed sentences, never reworded
  • Colour temperature, key-light direction, lens length — fixed, not drifting per segment
  • Aspect ratio, frame rate, banned items (subtitles / watermark / extra people) — stated once in the global settings

The model has never seen this character before, every single time. So the anchors travel with every segment.


Seams: chain the tail frame, or hard cut

05-chain.webp
Situation Use Cost
Continuous action, one conversation Tail-frame chaining — segment 01's last frame becomes segment 02's first frame That segment is frame-driven, so no reference card can ride along
New location, new angle, time jump Hard cut Identity and grade must be carried by the anchors

Get this wrong and you get one of two accidents: a visible flash where the action should have been continuous (you hard-cut it), or a dead-static camera where the angle should have changed (you chained the frame).


What you get

06-output.webp

One Markdown document, in two parts:

  1. Global settings — identity anchors, look, frame, audio, banned items. Written once, reused by every segment.
  2. One complete prompt per segment — written in H3's six-part structure, ready to paste:
subject_definitions:
<Picture 1> is the first frame; it locks the character, wardrobe and location.
summary:
[Shot 1] A slow push-in as she raises a hand toward the window.
retention_analysis:
<Picture 1> fully_preserved — face, hair and wardrobe unchanged.
detailed_description:
[Shot 1] Medium shot opening, pushing to close-up over 6 seconds...
overall_soundscape:
Quiet room tone, fabric movement.
non_diegetic_music:
N/A

A 42-second example

Seg Length Mode Anchor Content
01 15 s I2VA first frame sets composition opening, character enters
02 15 s FL2VA chained from 01's last frame continuous action, camera unchanged
03 12 s FL2VA hard cut to a new angle ending, identity held by anchors

Three independent generations that concatenate into one continuous 42 seconds.


When not to use it

  • Single shot, ≤ 15 s — no splitting needed. Use h3-prompt-writing; this extra step is pure overhead.
  • You just want one prompt, no stitching — same as above.
  • You need precise lip sync — that's digital-human mode's job, not something segment planning can solve.

Hard constraints at a glance

Constraint Value
Segment length H3 4–15 s / H3 Max 5–15 s, whole seconds
Frame rate 24 FPS
First/last frames vs reference media mutually exclusive in one request
Aspect ratio I2VA / FL2VA / L2VA inherit it from the input image; it can't be overridden
Cross-segment consistency carried by the global anchor block, not by luck

FAQ

Q: Can I just write one 30-second prompt?
No. The model caps at 15 seconds. A 30-second prompt gets you a 15-second clip, or a failure.

Q: Why can't I give a last frame and a reference image?
The platform treats those as mutually exclusive branches. If you genuinely need "same identity plus a continuous frame", split instead: chain frames for the continuous segment, use reference media for the segment where the camera changes.

Q: Do I have to rewrite the whole prompt for every segment?
No. Change the subject sentence — what happens in this segment — and carry the anchor block over untouched.

Q: Can segments be generated in parallel?
Reference-driven segments can. Frame-chained segments must be serial, because the next segment's first frame is an artefact of the previous one.

Q: What about audio?
Audio generated per segment will always break at the seams. Either render silent and dub in the edit, or cut on breaths and downbeats — never mid-word.


v2.0 · Compiled from the MiniMax H3 official docs, the H3 API schema published by fal.ai / Atlas Cloud / EmpirioLabs, and the Scenario H3 handbook.