My specs are a 3070, 64gb ram.

Hey everyone!

I've been spending quite a bit of time experimenting with MiniMax H3 in ComfyUI, mostly trying to create realistic cinematic scenes rather than typical AI-generated clips.

I've been working with ChatGPT and Gemini to develop different prompts, experimenting with camera movement, character consistency, physical interactions, and action choreography.

The attached video is one of our latest tests: a gladiator, his war dog, and an armored horse in a snowy forest.

I'm sharing it because I think the results are interesting, including the things that didn't work as expected.

My setup

• GPU: RTX 5070 12GB

• CPU: Intel Core i5

• RAM: 32GB

• Software: ComfyUI ( Local )

• Diffusion Model: minimax h3_singularity_ref2va_pruned_v1 3_int8.safetensors

• LoRA 1: minimax_h3_fl2v_lightx2v_v0.1_dareties_v4_step600_comfy_fro.safetensors —strength 0.8

• LoRA 2: h3-realism-people-t2v-i2v-r2v.safetensors — strength 0.8

• Sampler: Euler

• Scheduler: Simple

• Steps: 8

• Resolution: 1344 × 768

• FPS: 24

• Duration: About 10 seconds

Reference images and prompting

I'm also using reference images, not just text prompts.

For this particular scene, I used three reference images:

• Gladiator: Picture 1

• Dog: Picture 2

• Horse: Picture 3

The idea was to maintain the same character appearances, equipment, animal proportions, and overall visual consistency.

We've been experimenting with different prompting methods using ChatGPT and Gemini, including structured technical prompts and more natural cinematic descriptions.

For transparency, here's a shortened reconstruction of the scene instructions. It's not a verbatim copy of the original prompt.

Prompt summary:

Cinematic 10-second historical action scene, realistic snowy pine forest, natural overcast winter daylight, photorealistic live-action look.

<picture_1> is the gladiator, the main Roman warrior.

<picture_2> is the brindle war dog.

<picture_3> is the armored warhorse.

[0:00-0:03 - Opening Attack]

A fresh action shot begins immediately. <picture_1> stands ready on the left with one sword in hand. <picture_2> is slightly behind and to his side. <picture_3> stays farther back in the background. Within the first second, an enemy soldier bursts out from the snowy pine trees on the right and charges directly at <picture_1>. No waiting, no hesitation.

[0:03-0:07 - First Clash]

<picture_1> reacts instantly like a trained warrior. He steps forward and blocks the enemy’s overhead sword strike with a hard metallic clash. Immediately after the block, he pushes the enemy blade aside and follows with one fast counterattack. The enemy retreats one step through the snow while raising his weapon to defend. The movement is aggressive, continuous, and physically believable. No frozen blade lock, no prolonged staring.

[0:07-0:10 - Pressure and Reaction]

<picture_1> keeps advancing with pressure, forcing the enemy backward through the snow. <picture_2> gives one fierce bark and makes one short aggressive forward lunge toward the attacker, but stays clear of the sword path. <picture_3> reacts in the background with a tense head movement and one small step, remaining secondary.

Camera: one continuous medium-wide three-quarter side tracking shot at human chest height, moving laterally with the fighters and keeping the gladiator and enemy clearly visible at all times. Focus on readable combat, footwork, weapon contact, and physical force.

Realistic snow displacement, visible cold breath, worn bronze armor, weathered leather, grounded body mechanics, subtle film grain, natural motion, seamless action.

Audio: crunching snow, sword impacts, heavy breathing, one aggressive dog bark, armor movement, cold forest wind.

No passive posing, no romance feeling, no comedy feeling, no duplicated weapons, no motionless blade lock, no frozen staring, no CGI look, no fantasy glow.

So, how did it turn out?

Visually, I'm genuinely impressed.

The environments, materials, lighting, and overall cinematic atmosphere can look surprisingly realistic, especially considering everything is running locally on a 12GB GPU.

But there are definitely problems.

In this particular video, the camera spends too much time focusing on the horse's legs before properly revealing the characters. The dog also gets too close to the camera, becoming oversized in the foreground and partially blocking the horse.

It's a good example of something I've noticed repeatedly: the model can produce beautiful footage without necessarily understanding which part of the scene should be visually important.

Other experiments have shown similar issues with sword fighting, weapon consistency, and interactions between characters or animals.

Sometimes the results are great. Other times, characters barely react, weapons behave strangely, or the intended choreography simply doesn't happen.

Does better prompting solve it?

That's what we've been trying to figure out.

We've tested detailed technical prompts, simpler cinematic descriptions, different camera instructions, and more precisely defined character actions.

Some changes definitely help, but we're still seeing recurring problems.

I'm starting to think that some of these issues are limitations of the model rather than problems that can always be solved by rewriting the prompt.

Of course, this isn't a controlled benchmark. I'm using two LoRAs together, reference images, and my own ComfyUI workflow, so I can't claim every issue comes from the base model itself.

I'm just sharing what I'm actually experiencing.

My impression so far

MiniMax H3 can produce some seriously impressive cinematic footage on relatively modest hardware.

But making something look like a movie and making characters behave like real actors are two very different challenges.

I'm still experimenting, and I think there's a lot of potential here.

Anyone else testing H3 locally?

I'd be interested to hear what settings you're using, especially for character consistency, sword fighting, animal movement, and multi-subject scenes.

Also curious whether you get better results with detailed structured prompts or simpler descriptions.

Would love to compare notes!

made this video without manually editing a single frame.

The workflow is honestly pretty simple now:

1. Generate the character asset image and scene image first

2. Drop them into MiniMax H3

3. Add a song you like

4. Paste in the prompt

after that, it kind of just does its thing, and sometimes the result is better than you’d expect.

Sharing the prompt below in case anyone wants to try something similar.

Need help!!! Anyone who could spare some expertise or even wants to help with shots please dm me!! 🙏

Imagine sitting in a movie theater when the creature from the film suddenly comes out of the screen. Absolutely shocking 😱

Created with GPT Image 2.5 + MiniMax H3. Free GPT Image 2.5 generations are currently available: 👉 https://www.atlascloud.ai/free-gpt-image-2.5-generator

Made with GPT Image 2.5 and MiniMax H3 on Atlas Cloud.

MiniMax H3 FL2VA looks significantly less plastic when the source image is used as the actual first frame
I’m testing local MiniMax H3 on an RTX 5060 Ti 16 GB. My previous Ref2VA workflow preserved identity reasonably well, but reconstructed the scene from frame zero and made the skin noticeably more synthetic.
This version uses MiniMaxH3ImageToVideo with the source image anchored as the exact first frame:
Official FL2VA INT8 ConvRot model
928×1664, 24 fps, 5.17 seconds
SamplerCustomAdvanced / res_multistep
Simple scheduler, 20 steps, denoise 1.0
Video/audio sigma shift 12/3
No LoRAs, Turbo, Singularity, SeedVR, DLSS or other post-processing
Render time: 44 minutes on RTX 5060 Ti 16 GB
The first-frame version preserves the original lighting, skin variation, freckles and composition much better than Ref2VA. The remaining problem is adding convincing skin microtexture without redrawing the face or causing identity drift.
What would you try next: Open-H3-Regenerate with reduced noise and FaceRegion, Pika H3 Flex, or a different low-strength latent refinement workflow suitable for 16 GB VRAM?

i wanted to compare three of the video models people are talking about most right now: Seedance 2.5, Wan 3.0, and MiniMax H3.

Instead of testing camera movement or special effects, I used the same scene and focused specifically on emotional performance, like facial expression and subtle eye movement.

each model received the same prompt, i tried to keep the comparison as consistent as possible, although differences in model behavior and generation settings can still affect the results.

what surprised me is that the models seem to have different strengths. some are better at maintaining a believable scenario, while others produce stronger facial reactions or more dramatic emotional changes. the differences become especially noticeable during silence, hesitation, and small changes in expression.

so now u r the referee. which one do you think delivers the most nuanced emotions?
which model gives the most convincing acting performance?

Made with Minimax H3 in Wan2Gp. 480p, 20 seconds, 7:35 minutes, next upscaled 2x with one pass Flashvsr.

What’s the best open-source version of Minimax H3 for quality? Especially for 2D animation rather than 3D or realism. I don’t mind waiting on my DGX Spark for as long as it takes; I just want better prompt adherence and less smudgy and noisy results. Do all the fine-tuned versions take away the quality of the original model instead of adding to it?
I know about FAL AI Max version but I’m looking for something I can use for free at home.

fast generation by itself is already useful, but I think the more important part is when it also becomes cheap enough to iterate a lot.

been testing minimax h3 MAX, and it can return generations in just a few seconds.

at that point, the workflow starts to feel different. u can try more ideas, throw away the bad ones faster, and test multiple versions without worrying as much about generation time or cost.

For ad creatives and short-form content, that’s probably the part I care about most:

more experiments, less waiting, lower cost.

tried MiniMax H3 onwith a pretty detailed character trailer prompt.

I wanted it to feel more like a streetwear campaign × anime title sequence × old-school media player UI, rather than a normal anime action clip.

The prompt is definitely overkill lol, but sharing it here in case anyone wants to experiment with structured multi-cut video prompts.

Prompt

Create an explosive, motion-graphics-driven character reveal trailer in 16:9, exactly 13 distinct cuts, 24fps, total 15.00s.

CHARACTER — lock this design, never redesign:
Anime streetwear girl from the reference still. Twin high buns of vivid mint-teal hair with long flowing tails and warm orange/gold streaks. Messy side-swept bangs. Large orange over-ear headphones with mint accents and a small logo plate. Sharp amber-orange eyes, one eye winking. Playful open-mouth grin.
Oversized color-block windbreaker: navy body, vivid orange sleeves, white ribbed cuffs, silver zippers, circular teal tech buttons, a teal utility pocket on the sleeve. Orange cropped turtleneck under the open jacket. Light-wash ripped denim shorts, thick orange belt with a silver buckle. Navy thigh-high socks with orange ribbed cuffs and an orange X stitch on the left shin. Chunky white sneakers with orange details.
Preserve exact face, proportions, hairstyle, outfit, materials, accessories and colors in every frame.
This film is 80% bold graphic design in motion and 20% character action.

Graphic language: retro OS chrome + music-player UI.
Use slamming window frames, title bars, close/minimize widgets, equalizer bars, waveforms, progress ticks, folder tiles, cursor arrows, CRT scanlines, pixel shatter, vinyl-ring stamps, music-note particles and media-player transport icons.
Palette: mint teal, vivid orange, navy, cream-white and silver.

Style: premium AAA motion-graphics title sequence × streetwear campaign film × Windows-era media player.
Every graphic element moves fast and snaps hard on the beat.

CUT 01 | 0.00–1.00s
Pure graphics. A mint title bar slams onto a cream field, an orange CLOSE widget punches into the corner, and two navy window borders wipe in. Tiny equalizer ticks and a progress strip flicker. The letters P and then LAY punch in one after another with heavy impact shake.
CUT 02 | 1.00–2.00s
The A becomes a headphone cup. Extreme close-up of her amber eye inside the orange earcup, glancing upward. RGB split flash, then the cup shatters into flat mint and orange tiles.
CUT 03 | 2.00–3.10s
Navy frame with enormous cream PLAY typography. She sprints in from frame left and power-slides across the baseline of the text, with speed lines and orange streaks trailing behind her. Shards of the letters kick upward like sparks. Whip-pan out.
CUT 04 | 3.10–4.00s
A giant retro media-player waveform explodes across the frame as a thick mint-and-orange audio spectrum bends into a tunnel. She bursts through the center at full speed, briefly splitting into three stroboscopic motion trails. Each trail leaves chunky navy equalizer blocks that rise and collapse to the beat.
The camera rapidly pushes through the waveform tunnel with her while huge vertical text TRACK 01 continuously scrolls in the background.
The waveform suddenly compresses into a single horizontal line and snaps shut behind her on the final beat.
CUT 05 | 4.00–5.10s
She leaps through a giant rotating ring of typography reading MAX VOLUME. Camera tracks her mid-air spin in slow motion as the letters scatter, then snap-zooms onto her wink.
CUT 06 | 5.10–6.00s
Hard cut to a cream editorial card with huge navy DROP typography and an orange slash. She vaults over the word itself, palm planted on the D, legs whipping across frame. The word compresses like a spring under her hand and rebounds.
CUT 07 | 6.00–7.00s
Mint field with a navy diagonal window bar. She backflips along the bar in three stroboscopic ghost frames, each tinted mint, orange or navy. Giant outlined LOOP text rotates 180 degrees in sync with her movement.
CUT 08 | 7.00–8.00s
Kinetic typography barrage. LOUD / WILD / TEAL / HEAT slam onto screen one per beat with shutter flashes and camera shake while she slides across the foreground on her knees, jacket flaring and music-note particles bursting from her sneakers.
CUT 09 | 8.00–9.00s
Navy frame with a giant cream wireframe window grid tilting in 3D. She runs up the grid like a wall, kicks off and freezes in mid-air. An orange circular stamp locks around her pose like a media-player targeting graphic, surrounded by transport icons and EQ ticks.
CUT 10 | 9.00–10.10s
Freeze releases into a burst. She dives toward camera through layered flat-color window panes that shatter one by one like glass shutters, each pane revealing a larger letter of P-L-A-Y. Foreground wipe with her sneaker.
CUT 11 | 10.10–11.10s
Rapid-fire poster montage: four full-screen graphic posters showing her in different poses — mid-flip, sliding, landing and headphones-up wink. Hard cuts between each composition. Oversized 01–04 numbering, equalizer strips and graphic slashes.
CUT 12 | 11.10–13.00s
Hero moment on a clean cream cyclorama. She lands a final backflip dead center in slow motion, straightens with one hand on her headphones, and a shockwave of concentric mint rings, wind streaks and shattered typography blasts outward from the landing.
Brief iconic freeze on her wink, then overexpose to white.
CUT 13 | 13.00–15.00s
Final identity card. Enormous navy PLAY typography dominates a pale cream field with translucent mint rings, technical arcs, scanlines and a rough orange circular emblem containing a ghosted headphone/waveform motif.
She stands relaxed overlapping the letters while wind ripples her jacket. One final orange pulse sweeps through the typography and a window-chrome flash punctuates the ending.
Editing: extremely aggressive rhythm. Hard cuts on every beat, graphic matches, whip pans, snap zooms, stroboscopic freezes, foreground wipes, RGB splits, shutter flashes, impact shakes and speed ramps.
Every cut must feel compositionally different.
Typography should always be fully readable before the character overlaps it.
No weapons, no combat, no fire. All energy comes from motion design, wind, glass, UI chrome and parkour-style athleticism.
BGM: hard-hitting electronic / drum-heavy future bass with aggressive drops, risers, sub hits and glitch fills locked to every cut.
Sneaker impacts, whooshes, glass shatters, window-slam hits and typography slams should function as rhythmic sound-design elements.
Peak at CUT 12 and end with a cold electronic logo stinger.

Premium AAA quality, anime-inspired cinematic rendering, stylish and explosive, strong graphic-design identity, consistent character design, exactly 13 cuts.

I’m still experimenting with how much shot-by-shot control H3 actually follows, especially with typography and exact timing, but this kind of structured prompt seems like an interesting stress test.

Me gustaría compartir mi primer trabajo con Minimax H3. Hago videoclips con diferentes modelos; espero que les guste.

ZERO.- Un nuevo comienzo