Meta Superintelligence Labs has released Muse Spark 1.3, an agentic coding model designed for long-horizon workflows rather than single-turn generation. The update is now available in Muse Code and the Meta Model API, featuring a 1M-token context window while keeping weights closed.
Meta has released Muse Spark 1.3 with improved coding and agentic performance, while Google launched Gemini 3.8 Flash offering enhanced reasoning capabilities at the same introductory pricing as its predecessor.
This update covers several developments in the AI landscape, including Meta opening its Muse platform to third-party developers, releasing a new version of its segmentation model, and a security incident involving Google's Gemini.
Meta has released Muse for Mac, the first version of its personal AI agent capable of completing tasks directly on a user's computer. This macOS application extends the agent launched earlier in September for iOS, Android, web, and WhatsApp by adding a desktop layer that interacts with native apps.
Meta has introduced Muse, a personal AI agent built on the Muse Spark 1.3 model, designed with security features to protect against prompt-injection attacks. The system runs each agent in an isolated virtual machine divided into a sealed runtime cell and external service zones to separate untrusted data from user credentials.
Meta has introduced Muse, a proactive personal AI agent that executes tasks such as booking travel and negotiating bills rather than just answering questions. The service is rolling out now in the US on iOS, Android, and muse.ai, featuring a free tier and paid plans.
A research team from FAIR at Meta, the University of Oxford, and University College London has introduced AI Research Preference Models (RPMs) to help AI agents rank unexecuted machine learning experiment candidates. This approach addresses the bottleneck where idea generation is cheap but verification via GPU training is expensive.
Meta Superintelligence has released Muse Spark 1.3, a new frontier model that reportedly matches the performance of OpenAI's GPT-5.6-Sol and Anthropic's Opus. The release positions Muse Spark as the third-best model in the world and confirms Meta's status as a leading frontier lab.
Meta Superintelligence Labs has released Muse Voice Transcribe, a single autoregressive model that performs streaming automatic speech recognition (ASR), speaker diarization for 20+ speakers, and endpointing in one pass. The model is available as a hosted API on the Meta Model API under the name muse-voice-transcribe-1.0.
Meta is developing a new artificial intelligence model named Watermelon, which is intended to be as powerful as Anthropic’s cutting-edge models. The project was delayed until at least October after Meta paused and later resumed the pretraining stage in July.
Meta has introduced MetaRoCE, a clean-sheet RDMA transport protocol designed specifically for AI workloads on commodity Ethernet. Unlike standard RoCE, which relies on lossless networks and Priority Flow Control (PFC), MetaRoCE treats the fabric as lossy and moves ordering, path selection, and recovery logic into the Network Interface Card (NIC).
Meta has released MobileMoE, a collection of on-device Mixture-of-Experts (MoE) language models designed to optimize the quality-efficiency trade-off for mobile devices. The family includes three model scales with sub-billion active parameters and weight footprints under 3 GB in INT4 format.