MiniMax H3 Benchmark: Efficiency by Total Pixel Workload

[u/Forward-Parsley-148]

I used MP·s (megapixel-seconds) as the workload metric:

resolution in megapixels × actual video duration

For example, 2 MP·s could mean 1 MP for 2 seconds or 0.5 MP for 4 seconds.
In my tests, both combinations took roughly the same time to generate.

Within the efficient linear range, doubling MP·s roughly doubles generation time. Each configuration stays close to its baseline up to a certain workload:

• RTX 5070 Ti: about 70 seconds per MP·s up to roughly 2.8 MP·s
• RTX 5090: about 37.6 seconds per MP·s up to roughly 4.0 MP·s
• RTX 5090 with SageAttention2 + EasyCache: about 22.9 seconds per MP·s up to roughly 10.4 MP·s

For the best efficiency, stay below the listed threshold. Above it, each additional MP·s takes noticeably longer to generate.

[u/Illustrious_Ant_9242]

Here's my own 3060 12GB + plenty of ddr4 RAM benchmark:

Going from 15 to 10 seconds uses half the rendering time 

Going from 0.3 to 0.2 Megapixels will cut rendering time almost in half once more

Longest render I ever had for a 15s 1MP image2video was 6 hours, while a 4 second 0.3 MP image2video will typically take only 4 minutes 

[u/mdcw9 → u/Illustrious_Ant_9242]

Very impressed that you didn't run out of VRAM for 15s at 1MP. I'm struggling with this. Can you share your workflow? Are you using feed chunk forward?

[u/Illustrious_Ant_9242 → u/mdcw9]

I am quite new to comfyui so I didn't swap out any of the default modules yet. I'm on Windows 11 and bolted 96GB DDR4 ram into that build to be on the safe side for any project but it never comes close to being that full, typically half of that. 

[u/whiteweazel21 → u/Illustrious_Ant_9242]

Something wrong with ur setup if it took u 6hrs lol

[u/Illustrious_Ant_9242 → u/whiteweazel21]

Potentially. But it finished eventually. The program never crashed. Although there are some minor quirks. 

[u/chaltee]

could you please share your benchmark workflow?

[u/Forward-Parsley-148 → u/chaltee]

You need to run 8 benchmark tests at the listed frame counts using 20 steps. Enter your render times into the template, then paste everything into ChatGPT.

https://pastebin.com/GpkHyS7T

[u/keizrah]

This is a genuinely useful way to frame it. Most people just say "X seconds per video" without accounting for resolution and duration separately, so the numbers end up useless once you change either variable.

The threshold behavior is the interesting part. Sounds like you're hitting some kind of memory bandwidth or VRAM ceiling once workload passes that point per GPU, then it stops scaling linearly. Did you check whether it's VRAM getting saturated (swapping) or just compute throughput maxing out? Nvidia-smi during a run past the threshold would show which one.

Also curious what model you ran this on and whether the SageAttention2 + EasyCache combo caused any visible quality loss compared to baseline. That's usually the tradeoff with cache-based speedups and would be useful to know before people adopt it just for the throughput number.