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Sora was OpenAI’s text-to-video model.
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The 2024 research report describes generating videos up to about one minute and represents video using spacetime patches. OpenAI later discontinued the web/app product on April 26, 2026 and scheduled the API shutdown for September 24, 2026; these are historical system and service facts.
OpenAI’s 2024 Sora report describes a diffusion transformer over spacetime patches in a compressed video representation. It reports clips up to about one minute and image conditioning, and documents limitations such as inconsistent physical interactions. Those statements describe the 2024 report, not all video models or current product availability. OpenAI later states that Sora web/app ended April 26, 2026 and the API was scheduled to end September 24, 2026. The 2024 report also says training jointly used image and video data, and reports generations up to about one minute. Its technical and duration claims describe that 2024 system.
The 2024 report is a research example of text-conditioned video generation, not a currently available service.
The report describes image conditioning that can animate a still image.
The 2024 report discusses variable video durations, resolutions and aspect ratios.
OpenAI’s discontinuation notice documents the later web/app and API retirement dates.
The Sora product discontinuation notice is a dated service-status statement, not a forecast about future video-generation products. Any new availability or capabilities require a later official announcement.
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Sora was OpenAI’s text-to-video model. The 2024 research report describes generating videos up to about one minute and represents video using spacetime patches. OpenAI later discontinued the web/app product on April 26, 2026 and scheduled the API shutdown for September 24, 2026; these are historical system and service facts.
The 2024 report describes Sora generating video from written prompts. It represents video using spacetime patches in a compressed latent representation; the representation does not mean frames are generated independently in a fixed sequence.
Una sola imagen es un cuadro, pero el video requiere docenas o cientos de cuadros que se mantengan coherentes a medida que los objetos y las cámaras se mueven, un problema temporal mucho más difícil.
In the 2024 Sora report, video is represented as spacetime patches that act as transformer tokens. This answer is scoped to that report.
The 2024 Sora report describes diffusion with iterative denoising for video generation; this is a reported model detail, not a universal statement about all current video models.
The 2024 report discusses failures such as inconsistent object interactions and physics. This is a limitation observed in that reported system, not a claim about every current model.
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