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Tuesday

  1. ZhidongxiSelected

    Meta releases frontier model series Muse Wonder, focused on personal and professional agent tasks

    Meta releases its first frontier model series Muse Wonder, including two models, Muse Wonder and Muse Wonder Full, focused on personal and professional agent tasks and introducing proactive memory and proactive focus capabilities. On DeepSWE 1.1 and SWE-Marathon tests, Muse Wonder Full scores higher than Claude Fable 5.1, GPT-6 Astra and Claude Opus 5.5; at the highest reasoning effort on the Artificial Analysis leaderboard, the two models' Intelligence Index scores are 52 and 56 respectively. Muse Wonder is priced at 4 USD per million input tokens and 20 USD per million output tokens; Muse Wonder Full is now available on the API platform and open to Muse Code subscribers.

    Meta releases its first frontier model series Muse Wonder, including two models, Muse Wonder and Muse Wonder Full, focused on personal and professional agent tasks and introducing proactive memory and proactive focus capabilities. On DeepSWE 1.1 and SWE-Marathon tests, Muse Wonder Full scores higher than Claude Fable 5.1, GPT-6 Astra and Claude Opus 5.5; at the highest reasoning effort on the Artificial Analysis leaderboard, the two models' Intelligence Index scores are 52 and 56 respectively. M

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    #hot-signal#Model releases#Agents#Multimodal
  11. Latent SpaceSelected

    Meta MSL releases Muse Wonder and Muse Wonder Full models

    Meta Superintelligence Labs releases its second-generation model family Muse Wonder and Muse Wonder Full; the former is positioned as a fast frontier model, the latter as the full version, and Meta says they target personal and professional agent work. On Artificial Analysis's Intelligence Index v4.3, Wonder Full scores 56 and Wonder scores 52, higher than Muse Spark 1.3's 48, while Opus 5.5 leads with 58. Specifications are 1M context, input supports text, images, video and audio, output is text only, and pricing is 4 USD per million tokens for input, 0.20 USD for cached input, and 20 USD for output.

    Meta Superintelligence Labs releases its second-generation model family Muse Wonder and Muse Wonder Full; the former is positioned as a fast frontier model, the latter as the full version, and Meta says they target personal and professional agent work. On Artificial Analysis's Intelligence Index v4.3, Wonder Full scores 56 and Wonder scores 52, higher than Muse Spark 1.3's 48, while Opus 5.5 leads with 58. Specifications are 1M context, input supports text, images, video and audio, output is tex

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    #newsletter#Model releases#Agents#English text is being prepared.
  13. Huxiu

    Meta releases Muse Wonder and Muse Wonder Full, surpassing Claude on long-horizon coding tests…

    Meta Superintelligence Labs launched its new-generation flagship models Muse Wonder and Muse Wonder Full on October 13. The Full version scored 56 on the Artificial Analysis Composite Intelligence Index, 2 points behind Claude Opus 5.5's 58. On the DeepSWE 1.1 long-horizon software engineering test, Wonder Full scored 79.0, surpassing Opus 5.5's 74.2 and GPT-6 Astra's 74.1, but it still trails Opus on Terminal-Bench 4.0 and ProgramBench. Artificial Analysis estimates its average task cost at $4.52, up 183% from the previous generation Muse Spark 1.3; a developer comparison on the same prompt shows its 3D game generation is noticeably worse than Opus, and Meta's model card has acknowledged 3D tasks as a known limitation.

    Meta Superintelligence Labs launched its new-generation flagship models Muse Wonder and Muse Wonder Full on October 13. The Full version scored 56 on the Artificial Analysis Composite Intelligence Index, 2 points behind Claude Opus 5.5's 58. On the DeepSWE 1.1 long-horizon software engineering test, Wonder Full scored 79.0, surpassing Opus 5.5's 74.2 and GPT-6 Astra's 74.1, but it still trails Opus on Terminal-Bench 4.0 and ProgramBench. Artificial Analysis estimates its average task cost at $4.

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    #hot-signal#Model releases#Agents#English text is being prepared.

Wednesday

  3. The New StackSelected

    Google releases flagship model Gemini 4 Argon, with a shared 1 million token budget for input and output

    Google has opened the new flagship model Gemini 4 Argon to developers in the paid tier of the Gemini API, Google AI Studio, and tools such as the Gemini App, with the call name gemini-4-argon. The model uses a shared budget of 1 million tokens combined for input and output, different from the 1 million output cap stated at its September 30 release; long prompts will eat into reply space. Pricing before November 30 is $2 per million input tokens and $10 for output, rising to $4 and $20 afterward, with cached input discounted 95% during the promotional period. Google says it ranks first on the Vals Index, scores 87% on ERQA, and has already been made available to coding agents in Antigravity.

    Google has opened the new flagship model Gemini 4 Argon to developers in the paid tier of the Gemini API, Google AI Studio, and tools such as the Gemini App, with the call name gemini-4-argon. The model uses a shared budget of 1 million tokens combined for input and output, different from the 1 million output cap stated at its September 30 release; long prompts will eat into reply space. Pricing before November 30 is $2 per million input tokens and $10 for output, rising to $4 and $20 afterward,

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    #hot-signal#Model releases#Google#Agents