Steve Jang@stevejang · 2026/08/26赛道影响post-trained by @fal research = 50x speedup _and_ highest ELO 👀 https://t.co/o5zzfRXj3B
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Steve Jang@stevejang · 2026/08/26观点输出@grx_xce 🚀🚀🚀
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Steve Jang@stevejang · 2026/08/26观点输出RT @burkaygur: What a debut for fal Research. Congrats team.
Next task: accelerate all video models. DMs open. Be fast or be irrelevant.
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Steve Jang@stevejang · 2026/08/26观点输出https://t.co/VNaTvJUgLr
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Steve Jang@stevejang · 2026/08/26观点输出👀
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Steve Jang@stevejang · 2026/08/26赛道影响this is a turning point in AI video and the open-weights question.
the new @fal research group worked some wonders on the minimax h3 model. i had posted about a few days ago - essentially, reducing the RTF well below 1, and generating and rendering video faster than you can watch it.
today they are shipping their new H3 Max model for everyone to try. It’s a heavily post-trained version of the Minimax H3 open-weights model. it’s beating all other video models in its category on speed and cost, at highest of quality, according to @DesignArena & @ArtificialAnlys.
another intriguing part of this is how an open-weights model can be *significantly* optimized by throwing data and compute at the model, plus deep human expertise like the @fal research team.
in LLMs, we have examples of this like @perplexity’s PPLX-27B model which is a heavy post-train of Qwen’s open weight model. inference and training services like @FireworksAI_HQ and @parasail_io similar work on LLMs for enterprises and startups, respectively.
tapping into “value-added” deep inference and harness builders in the ecosystem allows these models to further improve in strong and surprising ways. unfortunately, there are not many frontier video models that are open-weights currently. so, kudos to @MiniMax_AI for being one of the first.
i think it’s inevitable that, like the LLM labs, the gen media model labs will have open-weights versions for developers and inference providers to improve and vary the performance as users would demand…at least those labs that want the very best version of their own models available to consumer and enterprise customers.
Steve Jang@stevejang · 2026/08/26观点输出RT @pandemona: The web is searchable. Podcasts should be too.
Introducing Radar by @particlepro_.
Radar lets you search and spot trends…
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Steve Jang@stevejang · 2026/08/26观点输出RT @AravSrinivas: Big thanks to @nvidia for working together with us and supporting this research on DGX Spark as well as enabling an open…
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Steve Jang@stevejang · 2026/08/26观点输出@loganthorneloe never left
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Steve Jang@stevejang · 2026/08/26观点输出@katiewav that is so cool to hear, katie. nam june was / is / will always be an inspiration.
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