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2026.10.17 · Sat

#模型发布

#模型发布

Opinion

Viewpoints, commentary, analysis, interviews, and discussion of trends.

10/14Wed
  1. François Chollet · X78

    Google releases Gemini 4 Argon globally across API and consumer services

    François Chollet congratulates the release, saying Gemini 4 Argon looks like a fantastic model. In the quoted announcement, Sundar Pichai says it is available globally today for developers and enterprises in the paid tier of the Gemini API and the Gemini platform, for Ultra subscribers in Google Antigravity, and for Ultra and Pro subscribers in the Gemini app and Search.

    Why it matters: The quoted announcement maps Gemini 4 Argon access across developer, enterprise, and consumer services, providing context on which paid tiers and subscriptions include the model.

10/7Wed
  1. Josh Woodward · X74

    Nano Banana announces Nano Banana 2.1 with improved image generation and editing

    Nano Banana announced Nano Banana 2.1, claiming improvements over its previous models across the board, including visual design, mask-based editing, subject consistency, and more natural-looking imagery. It is available in @GeminiApp, @GoogleAIStudio, and more. Josh Woodward commented, “Mask-based editing is my favorite from today, much more coming soon!” https://twitter.com/NanoBanana/status/2107521202466046453

    Why it matters: The announcement frames the upgrade around visual design, editing, subject consistency, and natural appearance, providing a concrete comparison with previous models.

10/6Tue
  1. Arthur Mensch · X72

    Mistral announces Mistral Large 4 with 1T parameters and native multimodality

    Mistral AI announced Mistral Large 4, aka Le Chonk, with 1T parameters, 49B active, and native multimodality, available via API today with an open weights release planned for the end of October. It claims the model leads open weights models from the US or Europe on aggregated benchmarks and surpasses closed frontier models on visual grounding. Arthur Mensch adds that it took groundwork, was trained and served on their own compute, and that RL shows no sign of saturation.

    Why it matters: The announced API availability and end of October open weights release give teams distinct timelines for accessing the model through hosted infrastructure or its weights.

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