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Every AI video comparison you've seen prices a single clip. That's the wrong unit — real work is a 60-120 second piece, and at that length the bill is decided by three things no pricing page shows: how long one generation can run, how often you'll need a retry, and whether audio comes free in the same pass.
Take the viral clip everyone's sharing this week — a Seinfeld/Trump street scene captioned "rendered this locally on my machine," made with MiniMax H3. Priced as one clip, 2 minutes of H3 video looks like $9.60. But H3 caps generations at 15 seconds, so a 2-minute piece is 8 separate generations. At 2 retries per shot, that's about $19. At 4 (typical for anything needing a consistent character across shots), about $38. Regenerate the keepers to 2K and you're at roughly $44 — 4.6x the sticker price, for the identical video.
We built the same math across MiniMax H3, Runway Gen-4.5, Kling 3.0, Google Veo 3.1, and ByteDance's new Seedance 2.5 — full table, with the 2x and 4x retry assumptions shown next to every number, not buried in a footnote. The spread is wide: the same 2-minute video lands under $25 total on some models once retries are counted, and near $190 on another's audio-included tier. Which one wins depends entirely on what you're making, not on which company has the best demo reel.
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One more thing about that "rendered locally" claim: MiniMax's open-weights release excludes the US, EU, UK, and South Korea from local use entirely — not just running the model, but using what it produces. The 12GB-VRAM figure going around is a community trick; MiniMax's own reference setup uses four GPUs. Worth knowing before you plan a workflow around it. Reality check on this whole table: every price is one company's page on one day in August 2026, and none of it measures output quality — a "cheap" take that needs a 5th regenerate isn't actually cheap.
A few days later, a much quieter release may matter more. Generalist AI's GEN-1.5 watches a robot task once — an 8-second clip — and attempts it immediately, no retraining: 59% success rate one-shot, climbing to 83% after just 10 gradient steps on 5 minutes of data. The weights barely move (under 0.15%). It also improvises: shown a brush sweeping blocks into a bowl, then handed a banana instead, it used the banana as a brush. The real story isn't the success rate on 10 small tasks — it's that eight months of broad pretraining made a few seconds of new experience enough to matter at all. Reality check: all numbers are self-reported by Generalist, on 10 deliberately simple tasks, with no independent replication yet.
Both stories are the same shape: AI is getting cheap enough, and quick enough to redirect, that the interesting question stopped being "can it do the demo" and became "what does it actually cost to use this for real."
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— Jerry