On October 20, 2026, Meta released the technical report for Muse Glimmer, a 30B open-weight model aimed at agent tasks on consumer-grade hardware, running at 4-bit precision on a single consumer GPU. The reporter adds that the model leads open-source models of the same scale in tool calling and multi-step planning, surpassing Qwen3.6-27B and Gemma4-31B on some metrics; after 4-bit quantization it is about 17GB, targeting devices with 24GB of VRAM, and uses DFlash speculative decoding to reach about 233 tokens/s on an RTX 5090, roughly 3.1 times faster than ordinary decoding. There are currently no subsequent developments.
On October 20, 2026, Meta released the technical report for Muse Glimmer, a 30B open-weight model aimed at agent tasks on consumer-grade hardware, running at 4-bit precision on a single consumer GPU. The reporter adds that the model leads open-source models of the same scale in tool calling and multi-step planning, surpassing Qwen3.6-27B and Gemma4-31B on some metrics; after 4-bit quantization it is about 17GB, targeting devices with 24GB of VRAM, and uses DFlash speculative decoding to reach ab
Meta's engineering team has published technical details of the Prometheus supercluster. Located in New Albany, Ohio, the cluster currently consists of hundreds of thousands of GPUs and operates as a single machine, with plans to scale to approximately 1 million GPUs. Meta confirmed that the first phase has already used the cluster to train the Muse family of foundation models (including Muse Wonder), with Muse Wonder achieving pretraining goodput of over 85% and reinforcement learning goodput of over 90%. Meta also disclosed two platforms: Catalina, based on NVIDIA GB200 NVL72, and Clemente, based on GB300 NVL72, as well as the upcoming Vera Rubin NVL72 platform.
Meta's engineering team has published technical details of the Prometheus supercluster. Located in New Albany, Ohio, the cluster currently consists of hundreds of thousands of GPUs and operates as a single machine, with plans to scale to approximately 1 million GPUs. Meta confirmed that the first phase has already used the cluster to train the Muse family of foundation models (including Muse Wonder), with Muse Wonder achieving pretraining goodput of over 85% and reinforcement learning goodput of
On October 20, 2026, watchdog groups Sleeping Giants Brasil and CTRL+Z submitted new evidence to Brazil's Superior Electoral Court, alleging that tools on Meta's Instagram and WhatsApp still favor Senator Flávio Bolsonaro and associate President Lula with derogatory content, even though the court has ordered Meta to ensure both candidates receive equal conditions. The evidence concerns GIF search, hashtag ranking, and answers from the Meta AI built into WhatsApp; the organizations are demanding that Meta make corrections within 24 hours and disclose the rules for ranking and AI-generated answers. Judge Bellizze had previously set a daily fine of 500,000 reais (about $99,000) and warned that it could rise to 1 million reais (about $198,000) if noncompliance continues. Meta denies intentionally favoring any candidate and has attributed earlier problems to technical glitches.
On October 20, 2026, watchdog groups Sleeping Giants Brasil and CTRL+Z submitted new evidence to Brazil's Superior Electoral Court, alleging that tools on Meta's Instagram and WhatsApp still favor Senator Flávio Bolsonaro and associate President Lula with derogatory content, even though the court has ordered Meta to ensure both candidates receive equal conditions. The evidence concerns GIF search, hashtag ranking, and answers from the Meta AI built into WhatsApp; the organizations are demanding
On October 20, 2026, watchdog groups Sleeping Giants Brasil and CTRL+Z submitted new evidence to Brazil's Superior Electoral Court, alleging that tools on Meta's Instagram and WhatsApp still favor Senator Flávio Bolsonaro and associate President Lula with derogatory content, even though the court has ordered Meta to ensure both candidates receive equal conditions. The evidence concerns GIF search, hashtag ranking, and answers from the Meta AI built into WhatsApp; the organizations are demanding that Meta make corrections within 24 hours and disclose the rules for ranking and AI-generated answers. Judge Bellizze had previously set a daily fine of 500,000 reais (about $99,000) and warned that it could rise to 1 million reais (about $198,000) if noncompliance continues. Meta denies intentionally favoring any candidate and has attributed earlier problems to technical glitches.
On October 20, 2026, Meta released the technical report for Muse Glimmer, a 30B open-weight model aimed at agent tasks on consumer-grade hardware, running at 4-bit precision on a single consumer GPU. The reporter adds that the model leads open-source models of the same scale in tool calling and multi-step planning, surpassing Qwen3.6-27B and Gemma4-31B on some metrics; after 4-bit quantization it is about 17GB, targeting devices with 24GB of VRAM, and uses DFlash speculative decoding to reach about 233 tokens/s on an RTX 5090, roughly 3.1 times faster than ordinary decoding. There are currently no subsequent developments.
Meta updated its commercial terms, removing language that had been interpreted as allowing it to scrape website content to train AI. Neiman Lab and Cornell University law professor James Grimmelmann previously argued that the clause was intended to let Meta use scraped content for free to train AI, and could bypass blocking instructions in robots.txt. Meta Vice President of Communications Andy Stone and spokesperson Daniel Roberts had responded that Meta's use of web crawlers had not changed, and this terms update directly removed the disputed language. Other reports said that when Meta updated its business services terms, it had stated it had the right to use content from business account domains, web pages or URLs to train AI models, and deleted that language after controversy; Meta said the update was merely a consolidation of existing advertising terms, not an expansion of crawler behavior, and that the revised terms limit crawlers and data collection to advertising and business products only, while site owners can still control crawler permissions via robots.txt.
Meta updated its commercial terms, removing language that had been interpreted as allowing it to scrape website content to train AI. Neiman Lab and Cornell University law professor James Grimmelmann previously argued that the clause was intended to let Meta use scraped content for free to train AI, and could bypass blocking instructions in robots.txt. Meta Vice President of Communications Andy Stone and spokesperson Daniel Roberts had responded that Meta's use of web crawlers had not changed, and this terms update directly removed the disputed language. Other reports said that when Meta updated its business services terms, it had stated it had the right to use content from business account domains, web pages or URLs to train AI models, and deleted that language after controversy; Meta said the update was merely a consolidation of existing advertising terms, not an expansion of crawler behavior, and that the revised terms limit crawlers and data collection to advertising and business products only, while site owners can still control crawler permissions via robots.txt.
Meta updated its commercial terms, removing language that had been interpreted as allowing it to scrape website content to train AI. Neiman Lab and Cornell University law professor James Grimmelmann previously argued that the clause was intended to let Meta use scraped content for free to train AI, and could bypass blocking instructions in robots.txt. Meta Vice President of Communications Andy Stone and spokesperson Daniel Roberts had responded that Meta's use of web crawlers had not changed, an
Meta's engineering team has published technical details of the Prometheus supercluster. Located in New Albany, Ohio, the cluster currently consists of hundreds of thousands of GPUs and operates as a single machine, with plans to scale to approximately 1 million GPUs. Meta confirmed that the first phase has already used the cluster to train the Muse family of foundation models (including Muse Wonder), with Muse Wonder achieving pretraining goodput of over 85% and reinforcement learning goodput of over 90%. Meta also disclosed two platforms: Catalina, based on NVIDIA GB200 NVL72, and Clemente, based on GB300 NVL72, as well as the upcoming Vera Rubin NVL72 platform.