TensorScaleAI @TensorScaleAI
Powering the future of generative worlds tensorscale.io Menlo Park Joined August 2026-
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@MiniMax_AI H3 ref-to-video is now live on @TensorScaleAI , with near-real-time inference This brings together Alibaba Cloud PAI’s distilled H3 model with TensorScale’s inference stack, achieving near-real-time speed: 17.7 seconds to generate 15-second 768p video for a real time factor (RTF) of 1.18. We’re continuing to optimize the stack and expect to push RTF below 1, enabling faster-than-real-time generation. Huge credit to MiniMax for the foundational model work, and to the Alibaba PAI team and broader open-source community for pushing the ecosystem forward. We’re excited to build on these efforts and make high-quality video generation faster, cheaper, and easier to serve in production.
LTX 2.5 JUST WENT FASTER THAN REAL TIME LTX (@ltx_io) is already one of the world's most widely used open video models. We just made its latest release, LTX 2.5, fast enough for rapid iteration and affordable enough for production at scale. It’s live on @TensorScaleAI now, generating a 5-sec 1080p video in just 3.12s at $0.04 per second. That's faster than real time, at a fraction of the cost! For creative teams, that means less waiting time, more ideas explored, and lower production costs. For robotics and physical AI teams, that means more data generated at scale, more scenarios tested, and shorter development and deployment cycles. Request early access today and we’ll get you onboarded! (link: lnkd.in/gV4tzeUK)
Today, we’re coming out of stealth with TensorScale (@TensorScaleAI ), and we're already running the fastest video inference in the world. MiniMax (@MiniMax_AI ) H3 — one of the leading open video models — now runs 10x faster and at half the cost on our inference stack. I’m building the company with long-time colleagues Teng Teng (@tt_tsio), Ye Wang (@yewang_ts), and Yun Tang (@_tangyun_). The AI stack was built for language models. We're rebuilding it for video and world models.
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