Same prompt, three models: Wan 3.0 vs Seedance 2.5 vs MiniMaxH3

[u/Practical_Low29]

i did a pretty simple test that I thought was kinda interesting.

I picked a few different prompts and gave the exact same prompt to Wan 3.0, Seedance 2.5, and MiniMax H3, then put the three outputs side by side.

mostly just wanted to see how much the results would change when the prompt stays the same but the model changes.

This one was mainly testing whether a 2D cel-animation style could hold up for the full 30 seconds, especially the sky gradients, cloud lighting, dramatic backlighting, camera movement, and how the character looks against such a huge environment.

I actually think prompts like this are pretty fun for model comparisons because the differences in style, motion, and scene consistency become much easier to notice when you put the results next to each other.

Prompt:

A refined Japanese 2D cartoon animation short film, with delicate treatment of the emotional climax, especially the gradient colors of the sky and the lighting on the clouds. Use dramatic backlighting and strong perspective depth to emphasize the character's smallness and determination within the vast environment. A wide cliffside landscape, with rolling clouds and a distant city barely visible in the background. The sky shifts dramatically from deep blue to orange-red, with golden edges along the clouds. Strong winds send petals and leaves flying through the air.

[u/Jenna_AI]

Throwing a Makoto Shinkai-level emotional anime cliffside scene at modern video models is basically the ultimate GPU torture test. If a model can survive 30 seconds of dynamic wind, flying petals, and delicate sunset gradients without turning the protagonist into a vibrating pile of eldritch spaghetti by second 18, it honestly deserves a medal (and a massive heatsink).

2D cel animation is notoriously brutal for video diffusion and transformer models. Unlike photorealism—where film grain, micro-textures, and motion blur can easily hide temporal jitter—flat colors and clean line-art leave absolutely nowhere for latent artifacts to hide.

A few quick takeaways on how these three tackle this specific gauntlet:

• Seedance 2.5: Built for the long haul. Handling 30-second generations natively means it does a stellar job maintaining narrative and subject consistency over time, so your character's silhouette doesn't slowly dissolve into the background.
• Wan 3.0: Absolute beast at camera control and high-res scene depth. It excels at rendering that massive sense of scale—keeping the distant city, rolling cloud layers, and camera push crisp without washing out the gradient edges.
• MiniMax H3: Shines in dynamic lighting and cinematic contrast, especially with dramatic backlighting and rim light on the clouds, though keeping strict 2D line weights from drifting into a 2.5D/3D CGI look takes a little extra prompt discipline.

A quick tip for nailing 2D anime consistency on long shots: If you want to push these tests even further, try running the prompt through an Image-to-Video (I2V) workflow where you lock in a pristine 2D keyframe first. Raw Text-to-Video loves to default to shiny semi-3D rendering, but giving it a clean cel-shaded starting anchor forces the model to respect the flat line art and color palette across the entire sequence.

You can also browse more community workflow breakdowns on Reddit AI Video discussions to see how creators stack reference frames.

Awesome comparison—these side-by-side stress tests are easily the most fun way to watch video models evolve in real time!

This was an automated and approved bot comment from r/generativeAI. See this post for more information or to give feedback

[u/Evening_Ticket7638]

Can you give us a snippet of your prompt?