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AI CURATED HOT STORY · 10/15/2026

Meta Unveils Muse Spark Open: 816B MoE Model Enables Million-Token Context and Dual Mac Studio Local Inference

9 reports archived9 independent sourcesupdated 10/16/2026, 04:04:53
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Meta has officially open-sourced Muse Spark Open, its most powerful US-based open-weight multimodal model to date. Utilizing a Mixture-of-Experts (MoE) architecture with 816 billion total parameters and 42 billion active parameters, the model supports native text, image, audio, and video inputs. It features a massive 1 million token context window, specifically optimized for long-horizon agentic coding tasks and complex software engineering workflows.

Cross-verified reports indicate that Muse Spark Open performs comparably to top Chinese open-source models like Qwen and GLM in benchmarks. A key breakthrough is its ability to run efficiently on two M5 Ultra Mac Studios via collaboration with Apple and optimization through the MLX framework. This marks a significant advancement in local inference capabilities for high-end consumer hardware, despite requiring substantial memory resources (at least 700GB VRAM or dual 512GB RAM setups).

The release signifies Meta's strong return to the open-source race. The license permits free commercial use and fine-tuning but imposes restrictions on API resellers with annual revenues exceeding $20 million. This strategy balances ecosystem growth with commercial protection while pushing the boundaries of local AI deployment on Apple Silicon.

LATEST/Muse Spark Open is now live on Arena benchmarks and OpenRouter, priced at $1.25 per million input tokens and $4.25 per million output tokens. The community is actively evaluating its performance on dual M5 Ultra Mac Studio clusters and exploring fine-tuning strategies for specific codebases.

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Total 9 reports · Latest first
  2. The DecoderT2·85 pts
    • Muse Spark Open features 816 billion parameters and supports multimodal inputs including text, image, video, and audio.
    • It offers a 1-million-token context window and matches the benchmark performance of leading Chinese models like Qwen and GLM.
    • The model is explicitly optimized for local inference on Apple's M5 Ultra hardware.
  3. Arena.ai (@arena)T1·88 pts
    • Muse Spark Open uses an 816B total / 42B active parameter MoE architecture to balance performance and inference cost.
    • Supports a 1 million token context window, enhancing capabilities for large codebases and long documents.
    • Features native multimodality across text, image, video, and audio, designed specifically for long-horizon agentic workflows.
  4. The Verge AIT2·68 pts
    • Meta launches Muse Spark Open, positioned as the most capable US open-weight model currently available.
    • Apple and Meta engage in rare public collaboration, optimizing model performance on Apple Silicon via the MLX framework.
    • The model supports local inference on a cluster of two M5 Ultra Mac Studios, overcoming desktop compute bottlenecks.
  5. OpenRouter (@OpenRouter)T1·86 pts
    • Positioning: Claimed as the strongest open-weight model from a US lab, optimized for long-horizon tasks and complex software engineering.
    • Architecture: 816B total parameters with 42B active (MoE), balancing performance and inference cost.
    • Capabilities: Supports 1M context window and fully multimodal input including text, image, video, audio, and PDF.
  6. AWS Machine Learning BlogT1·38 pts
    • Muse Spark Open is Meta's open-weight model optimized for agentic coding workflows, focusing on first-attempt accuracy and tool calling.
    • The model supports a 1 million token context window, suitable for large codebases and multi-file refactor tasks.
    • Two variants are available on SageMaker JumpStart: BF16 (`Muse-Spark-Open-816B-A42B`) and NVFP4 quantized, allowing users to balance performance and cost.
  7. 宝玉 (@dotey)T2·88 pts
    • Muse Spark Open is Meta's first open-weight large-scale Muse model, optimized for coding and long-horizon agentic tasks.
    • The 816B total/42B active parameter MoE architecture reduces compute but demands massive memory for full loading.
    • The license permits commercial use, modification, and distillation, but requires separate agreements for API resellers with >$20M annual revenue.
  9. vLLM 官方博客T1·68 pts
    • Muse Spark Open is an 816B parameter sparse MoE model with 42B active parameters and a 1M context window, distilled from Muse Glimmer 30B.
    • vLLM enables Day 0 support with comprehensive parallelism (TP/PP/EP) on Nvidia, AMD, and TPU, plus DSpark speculative decoding for accelerated inference.
    • The model features native multimodal capabilities (image, video, audio) specifically engineered for long-horizon agentic coding workflows.
Meta Unveils Muse Spark Open: 816B MoE Model Enables Million-Token Context and Dual Mac Studio Local Inference | Today for AI