Meta released open weights for its Muse Spark AI model, shifting it from a proprietary system to Muse Spark Open designed for coding and long-running agent work. The model has 816 billion parameters, with 42 billion active per token, and it supports a context window of up to 1 million tokens. The release adds a license with limited commercial terms and changes usage by enabling free downloads/adaptation for developers (with restrictions on hosted resale, and on military/critical-infrastructure uses), while keeping Meta’s top systems closed.
Meta launched Muse Spark Open, an open-weight AI model designed to run on Macs, and paired it with Muse Code for coding and other agentic workflows. The model uses 816 billion parameters and a 1 million token context window. Running it locally requires at least 1 terabyte of RAM, and Meta is making the model available now through multiple API platforms for desktop-focused coding and tasks.
Accenture CTO Marc Warner and three other AI executives said few large organizations have truly rebuilt core operations around AI, with many using AI mainly in peripheral tasks. They estimated the share of enterprises or government processes “close to zero” that have been reinvented with AI at the core. They argue returns are limited until companies redesign core workflows and governance, and they urge teams to focus less on blame for failures except in critical incidents.
Meta released the Muse Spark Open weights as an open-weight multimodal model for coding and AI agents. It has 816 billion parameters with a 1 million-token context window. The release comes with a custom license that allows free use and fine-tuning but adds conditions like advance notification above $20 million revenue and a requirement to display “Built with Muse Spark Open.”
Meta’s Muse Spark Open is now available in Amazon SageMaker JumpStart as an open-weight, coding-optimized model deployable to SageMaker endpoints in customers’ own AWS accounts. The model supports a 1 million-token context window and is offered in BF16 (Muse-Spark-Open-816B-A42B) and an NVFP4 4-bit quantized variant. Deployments shift to Amazon-managed infrastructure on a customer-controlled endpoint (including VPC/KMS/network isolation options) with instance sizing differing by variant (ml.p5e.48xlarge for NVFP4 vs ml.p6-b300.48xlarge for BF16).
Nvidia launched customizable Nemotron 3.5 Super LV and agent-focused Nemotron 3.5 Bolt LLMs for always-on AI agents, with an additional smaller Bolt E4B planned later this month. Super VL is an open 120-billion-parameter model trained on about 26 trillion tokens. Organizations can download the open weights to run and post-train models behind their own firewalls, while Bolt models enable local and edge deployment within 24 GB or as little as 4 GB.
Meta launched Muse Spark Open, an 816B open-weight AI model with 42B active parameters, and made it available via multiple model APIs and major model hubs under the Muse Model License. The model uses a 1 million token window. The license adds limits tied to developers’ revenue and requires UI attribution (“Built with Muse Spark Open”), while Meta’s benchmarks claim it performs at or above several top Chinese open-weight models but trails them on specific coding tests like Terminal-Bench 2.1.
Mistral CEO Arthur Mensch argued in a LinkedIn essay that Europe should not rely on U.S./China frontier models while instead building its own AI models. He said Europe pays more than €260 billion a year to American cloud and software providers. He calls for Europe to increase compute and investment, including Mistral’s plan to raise capacity sixfold over the coming year.
Meta’s open-weights coding and agent-focused foundation model, listed for launch, is available to download or run locally. It has 816B total parameters with a 1M token context window. The update gives developers options to get the weights via Hugging Face or run it on two M5 Ultra Mac Studios using MLX.
Meta’s Muse Spark Open open-weight agentic coding model launched on Together AI and is available using serverless and dedicated infrastructure. It includes a 1M-token context window, and Together AI lists pricing at $1.25 per 1M input tokens and $4.25 per 1M output tokens. Developers can now run Muse Spark Open via the Together API on day 0, with support for long-running code-understanding workflows.
Meta released Muse Spark Open, a large open-weight multimodal mixture-of-experts model that can take text plus images, audio, and video and run agentic coding tasks. The model is built with about 816 billion total parameters and a 1,000,000-token context window. Developers can now run, fine-tune, and deploy the model via released checkpoint formats and tooling, with modality-specific encoders and inference support updated accordingly.
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