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    Artificial Analysis says GPT Image 2.5 Flare leads in 5 of its 9 text-to-image capabilities

    Artificial Analysis's preliminary speed tests put Flare (max) at a median generation time of 52.7 seconds, down 63% from GPT Image 2 (high)'s 142.9 seconds.

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    1 Source, 19d ago, first seen 19d ago

    TLDR

    Artificial Analysis reports that GPT Image 2.5 Flare leads in five of the nine capabilities measured in its text-to-image arena. Its largest leads over the next-best models are in Knowledge, Material and Physics—covering real-world facts, surface properties and physical behavior. It also narrowly leads Complex Compositions and Text Rendering. In preliminary speed tests, the group says Flare (max) reduced median generation time by 63% versus GPT Image 2 (high), from 142.9 to 52.7 seconds. Those tests used 1024 × 1024 PNG outputs, with timing covering both inference and image transfer across several runs.

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    1 Source, first seen 19d ago

    Combined views

    430

    1 Source, first seen 19d ago

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    1 Source

    @ArtificialAnlysGPT Image 2.5 Flare leads in 5 of the 9 Text to Image capabilities we measure, with the largest leads in Knowledge, Material, and Physics. Our Text to Image arena scores models on two axes: nine capabilities, which are the skills that go into making an image, and ten use cases, which measure how those capabilities combine in real workloads. Flare's largest leads over the next-best model are in Knowledge and Physics, both over GPT Image 2 (high), and Material, over Microsoft's MAI-Image-2.6. Flare also narrowly leads Complex Compositions and Text Rendering. ➤ Knowledge covers real landmarks, species, and domain facts across science and common sense. ➤ Material covers surface properties, transparency, subsurface scattering, and texture realism. ➤ Physics covers gravity, support, collision, and thermal and state change.

    1 Source

    @ArtificialAnlysGPT Image 2.5 Flare leads in 5 of the 9 Text to Image capabilities we measure, with the largest leads in Knowledge, Material, and Physics. Our Text to Image arena scores models on two axes: nine capabilities, which are the skills that go into making an image, and ten use cases, which measure how those capabilities combine in real workloads. Flare's largest leads over the next-best model are in Knowledge and Physics, both over GPT Image 2 (high), and Material, over Microsoft's MAI-Image-2.6. Flare also narrowly leads Complex Compositions and Text Rendering. ➤ Knowledge covers real landmarks, species, and domain facts across science and common sense. ➤ Material covers surface properties, transparency, subsurface scattering, and texture realism. ➤ Physics covers gravity, support, collision, and thermal and state change.