❯ MiniMax H3, Post-Trained by a Third Party, Surpasses Stock Version to Top Image-to-Video Leaderboard

RANKINGSOn the image-to-video leaderboard from independent evaluator Artificial Analysis, MiniMax H3 Max, post-trained by inference platform fal, tops the chart at 1204 points, pushing the 1184-point original MiniMax H3 down to third. On the audio-inclusive text-to-video leaderboard, it ranks third at 1234 — also ahead of the original. Open-source weights fine-tuned by a third party overtaking the original maker is a first on video-model leaderboards.

EARNINGSMiniMax listed in Hong Kong this January and posted interim results on August 27: first-half total revenue of $116.6 million, up 283% year on year — one half-year alone already exceeding the full-year 2025 total of $79 million. Gross margin rose from 12.1% to 17.9%; adjusted net loss widened to $293 million, roughly double the $138.7 million a year earlier. The structural shift is the more telling detail: open-platform and enterprise services revenue jumped 703% to $73.9 million, lifting its share from 30.3% to 63.4% — the growth engine has moved from the consumer side to the API side.

WEEKLY SHAKEUPH3 launched on July 31, featuring unified full-modal generation — natively outputting 4-to-15-second 2K video plus synchronized stereo audio — and is officially priced at $0.13 per second of 2K. ByteDance’s Seedance 2.0, which topped both leaderboards two months ago, has now dropped out of the top five. Alibaba’s Wan 3.0 has taken the top spot in text-to-video, while Kling 3.0 and Veo 3.1 have both slipped to the middle of the pack. The open-source calculus of video-model vendors is due for a rethink: releasing weights buys ecosystem and leaderboard exposure — the cost is seeing your own flagship fine-tuned into something better by an outsider.

▪ SIGNALA maker outranked by its own open-sourced weights shows that this cycle’s gap lies in post-training craft, not the base model.