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2026.10.17 · Sat

#Meta

#Meta

Models

New models and versions, open weights, and changes in capability and pricing, with their evaluations.

10/16Fri
  1. Artificial Analysis · X79

    Meta releases Muse Spark Open, scoring 39 on Artificial Analysis Intelligence Index

    Meta has released Muse Spark Open, an 816B (42B active) open-weights model that Artificial Analysis reports scores 39 on its Intelligence Index, making it the #1 US open-weights model. Muse Spark Open (xhigh) scores 22 points above Muse Glimmer (high, 17), Meta's 30B dense open-weights model. https://t.co/jf31mQNINe

    Why it matters: The comparison places Muse Spark Open 22 points above Muse Glimmer on the same intelligence index, providing a concrete reference for the reported capability gap between Meta's open-weights models.

  2. Hugging Face Blog87

    Meta releases Muse Spark Open, an open-weight multimodal mixture-of-experts model

    Meta’s Muse Spark Open is an open-weight mixture-of-experts model with approximately 816 billion parameters, around 42 billion active per token, and a context window of up to one million tokens. Trained for agentic coding, it accepts text, images, audio, and video and generates text. Hugging Face provides inference and deployment recipes, reports its own quantization tests, and demonstrates attention-layer LoRA fine-tuning with TRL while keeping the experts frozen.

    Why it matters: The deployment recipes clarify how sparse expert activation reduces per-token computation while retaining substantial memory requirements, helping developers assess hardware needs across checkpoint formats and serving frameworks.

10/13Tue
  1. Latent Space84

    Meta launches Muse Wonder and Muse Wonder Full frontier models

    Meta Superintelligence Labs released Muse Wonder and Muse Wonder Full, its second-generation model family for personal and professional agentic work. Latent Space reports that Wonder is available through the Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Artificial Analysis gives Wonder Full and Wonder Intelligence Index v4.3 scores of 56 and 52, respectively, versus Opus 5.5’s 58; Wonder supports a 1M context window and text, image, video, and audio inputs, with text-only output.

    Why it matters: The benchmark breakdown compares Wonder variants with competing models on agentic performance and token usage, showing how their relative standing changes across tasks rather than a single ranking.

  2. Alexandr Wang · X82

    Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores

    Meta has released Muse Wonder and Muse Wonder Full, according to Artificial Analysis in the post quoted by Alexandr Wang. At max reasoning effort, they score 52 and 56 on the Artificial Analysis Intelligence Index v4.3, compared with Muse Spark 1.3’s 48, following a release gap of 6 weeks. Muse Wonder is available through Meta’s first-party API and Muse Code, while Muse Wonder Full is limited to Muse Code users; both have 1M-token context windows.

    Why it matters: Artificial Analysis’s comparison highlights a tradeoff between Muse Wonder’s improved benchmark performance and its higher cost per task relative to Muse Spark 1.3 despite lower output token usage.

  3. TechCrunch · AI83

    Meta releases frontier models Muse Wonder and Muse Wonder Full

    Meta’s Superintelligence Lab released Muse Wonder and Muse Wonder Full on Monday, larger models described as more capable than Muse Spark. Meta reports benchmark scores comparable to Fable 5.1 and GPT-6 Astra and emphasizes information retention through “active memory.” Wonder costs $4.00 per million input tokens and $20.00 per million output tokens through the Meta Model API; Wonder Full is available only to Muse Code subscribers. Both models will power the Muse agent.

    Why it matters: The split between API access for Wonder and subscriber access for Wonder Full gives developers a concrete basis for comparing integration options within Meta’s new model lineup.

9/29Tue
  1. Latent Space78

    AINews: Opus 5.5 excels at generating explainer videos

    Latent Space's AINews roundup of developments from September 24–25 says community feedback was positive after Opus 5.5 launched that week, especially for generating explainer videos with code.

    Why it matters: The weekly roundup offers a quick look at model and agent-infrastructure developments, including community feedback on Opus 5.5's code-generated videos and how vendors position their new models.

8/10Mon
  1. Hugging Face Blog82

    Meta releases open-source 30B multimodal Muse Glimmer for local agents

    Meta has released Muse Glimmer, a 30B-parameter multimodal model distilled from Muse and licensed under Apache 2.0. It targets local-agent use cases such as coding, document analysis, and personal assistance.

    Why it matters: Meta has open-sourced a 30B multimodal model with reproducible details on its architecture, benchmarks, local deployment, and self-improvement demonstrations.

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