Meta Releases Muse Spark Open With Mac and Cloud Support as Artificial Analysis Publishes Benchmarks
Understand the event
Meta released downloadable weights for Muse Spark Open, a multimodal model for coding and agentic work that Artificial Analysis ranks first among US open-weight models on its Intelligence Index, scoring 39 at the xhigh setting. The model has approximately 816 billion parameters, with 42 billion active per token, and supports up to one million tokens of context. It accepts text, images, audio and video and generates text. Artificial Analysis’s initial AA-AgentPerf testing reports throughput of up to approximately 150 million tokens per second per megawatt of power used on four NVIDIA GB300 or B300 GPUs. Meta says the model can run on two Apple M5 Ultra Mac Studios using MLX; Baoyu reports that this configuration uses 512GB of unified memory per machine. vLLM says its support is verified on NVIDIA and AMD GPUs and TPUs. Ollama Cloud offers access through Pro, Max, Pay-as-you-go and Teams plans. Amazon SageMaker JumpStart offers BF16 and NVFP4 variants in US East (N. Virginia) and US East (Ohio) at launch, charging for endpoints whenever they run, including while idle. The license carries conditions: The Decoder reports that free use requires the label “Built with Muse Spark Open.” Baoyu reports that attribution and usage restrictions apply, and that businesses selling API access to the model or modified versions must notify Meta and sign a separate agreement if their combined revenue with affiliates exceeded $20 million over the preceding 12 months.
Generated by AI from reports · Updated 8 days ago
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11 developments
- 10/24 07:19 (UTC+8) · 1 reportsArtificial Analysis publishes Muse Spark Open benchmark resultsArtificial Analysis · X:Artificial Analysis reports Muse Spark Open throughput results on AA-AgentPerf
- 10/17 22:15 (UTC+8) · 1 reportsReflecting on Meta’s big week, where US open-weight models now stand, and the outlook for meaningful competition to Anthropic & OpenAI. Meta feels like they’reNathan Lambert · X:Reflecting on Meta’s big week, where US open-weight models now stand, and the outlook for meaningful competition to Anthropic & OpenAI. Meta feels like they’re going from strength to strength, but can they close the last bit of the gap to Claude?
- 10/16 08:41 (UTC+8) · 2 reportsArtificial Analysis ranks Muse Spark Open as the top US open-weights modelArtificial Analysis · X:Meta releases Muse Spark Open, scoring 39 on Artificial Analysis Intelligence Index
- 10/16 06:08 (UTC+8) · 1 reportsOllama Rolls Out Muse Spark Open to Additional PlansOllama · X:Ollama expands Muse Spark Open access to Pro and Pay-as-you-go plans
- 10/16 04:42 (UTC+8) · 1 reportsOllama Makes Muse Spark Open Available on Its CloudOllama · X:Muse Spark Open Is Now Available on Ollama
- 10/16 02:13 (UTC+8) · 2 reportsvLLM Adds Day-0 Support for Muse Spark OpenvLLM · X:vLLM adds day-0 support for Meta’s open-weight Muse Spark Open
- 10/16 01:55 (UTC+8) · 1 reportsClément Delangue Demonstrates Serving Muse Spark on Two Mac StudiosClément Delangue · X:Clément Delangue Runs Muse-Spark-Open-816B-A42B-GGUF on Two Mac Studios
- 10/16 01:43 (UTC+8) · 1 reportsAWS Shows How to Deploy Muse Spark Open with SageMaker JumpStartAWS Machine Learning Blog:Meta’s Muse Spark Open now available in Amazon SageMaker JumpStart
- 10/16 01:37 (UTC+8) · 1 reportsNathan Lambert Predicts Strong Adoption for Muse Spark OpenNathan Lambert · X:Nathan Lambert predicts strong muse spark open adoption if reported scores hold up
- 10/16 01:25 (UTC+8) · 1 reportsMeta Releases Muse Spark OpenNathan Lambert · X:Nathan Lambert Says He Needs to Blog After @AIatMeta Announces Muse Spark Open
- 10/15 08:00 (UTC+8) · 11 reportsMeta Releases Muse Spark Open, an Open Weight Multimodal ModelHugging Face Blog:Meta releases Muse Spark Open, an open-weight multimodal mixture-of-experts model
Report timeline
Follow the reports to explore different sides of the event.
- Artificial Analysis reports Muse Spark Open throughput results on AA-AgentPerf
Artificial Analysis reports that results for Meta’s newly released Muse Spark Open, an 816B (42B active) open-weights model, are live on AA-AgentPerf. Its initial testing reaches up to ~150M tokens/s throughput per MW of power used on 4x NVIDIA GB300 or B300 GPUs. The post also reports a score of 39 but leaves the benchmark unidentified, linking to https://t.co/swocvUUvvm.
- Nathan Lambert Highlights Recent Open Models and Regulatory Actions
The latest open models and some analysis of recent regulatory action from MOFCOM on model exports / DHS on DeepSeek. Great to see a bunch of strong US open weight models from Reflection, Meta, and Nvidia in this one! https://t.co/CBmAc9GJ45
- Reflecting on Meta’s big week, where US open-weight models now stand, and the outlook for meaningful competition to Anthropic & OpenAI. Meta feels like they’re going from strength to strength, but can they close the last bit of the gap to Claude?
Reflecting on Meta’s big week, where US open-weight models now stand, and the outlook for meaningful competition to Anthropic & OpenAI. Meta feels like they’re going from strength to strength, but can they close the last bit of the gap to Claude?
- NVIDIA AI · XPicksMeta releases Muse Spark Open, an 816B open-weights model
NVIDIA AI congratulates @alexandr_wang and the @Muse team on their open-weights model release. https://t.co/7JH7PXOnAz In the quoted post, @ArtificialAnlys reports that Meta's Muse Spark Open has 816B parameters (42B active) and scores 39 on the Artificial Analysis Intelligence Index, ranking it the #1 US open-weights model. Muse Spark Open (xhigh) scores 22 points above Meta's 30B dense Muse Glimmer (high, 17). https://t.co/jf31mQNINe
- Six projects from the last few weeks that caught our attention: A wildfire analysis prototype that maps the fire’s spread over time and tracks hot spots, made with Opus 5.5.
Six projects from the last few weeks that caught our attention: A wildfire analysis prototype that maps the fire’s spread over time and tracks hot spots, made with Opus 5.5.
- Meta releases Muse Spark Open with day-one vLLM support
Great work from the Meta team! vLLM powered RL inference during Muse Spark Open’s training, and now supports its open release from day one. https://t.co/pkhr0rQ9vq https://t.co/VjcbSXPQaY
- 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
- Ollama · XPicksOllama expands Muse Spark Open access to Pro and Pay-as-you-go plans
Muse Spark Open is now rolled out to Pro, Max, Pay-as-you-go, and Teams plans on Ollama. https://t.co/OmAFXzZyjm
- Muse Spark Open Is Now Available on Ollama
Muse Spark Open is now on Ollama. @Meta's open-weight model for coding and tool use, with a 1M-token context window. Run it on Ollama’s cloud: ollama run muse-spark-open:cloud Use with Claude Code: ollama launch claude muse-spark-open:cloud Now available to Max and Teams
- TechCrunch · AIPicksMeta launches Muse Spark Open, an open-weight AI model designed for Macs
Meta has launched Muse Spark Open, a natively multimodal open-weight model with 816 billion parameters and a 1 million token context window, built for complex coding tasks and agentic workflows. It is designed to run locally on Macs, though Engadget reports it requires at least 1 terabyte of RAM. Meta claims superior performance over other popular open-weight models in its evaluations and is making the model available now through multiple API platforms.
- The DecoderPicksMeta releases Muse Spark Open for coding and agentic tasks
Meta has released Muse Spark Open, an open-weight model with 816 billion parameters (42 billion active), up to one million tokens of context, and text, image, video, and audio support. Meta reports leads over Qwen 3.8, GLM 5.3, and Kimi K3 in several benchmark categories, while trailing some competitors in coding. Weights are on Hugging Face; use requires the label "Built with Muse Spark Open," and API providers earning more than $20 million annually need a separate agreement with Meta.
- NVIDIA AI · XPicksMeta releases Muse Spark Open for coding and agentic work
Meta announced Muse Spark Open, describing it as the most capable US open-weight model to date, built for coding, agentic work, and multi-step reasoning. NVIDIA AI says the 816B model was trained on NVIDIA GB300 NVL72 and has a 1M-token context window for working across large codebases. Meta also produced NVFP4 checkpoints optimized for Blackwell Ultra. https://t.co/yAtoxNeYJm https://t.co/HJUKdC1n3D
- The Verge · AIPicksMeta and Apple team up to run Muse Spark Open on Macs
Meta announced Muse Spark Open today, releasing its weights and saying it can run on two Apple M5 Ultra Mac Studios using the latest MLX framework. Meta says the natively multimodal model has 816 billion total parameters and excels at long-horizon tasks, complex software engineering, and multi-step reasoning. Meta and Apple collaborated over several months, and Apple published a technical post covering MLX, Muse Spark Open, and two other open models.
- vLLM · XPicksvLLM adds day-0 support for Meta’s open-weight Muse Spark Open
Day-0 support for Meta’s open-weight Muse Spark Open is live on vLLM, verified on NVIDIA and AMD GPUs as well as TPUs! 816B parameters, 42B active per token, a 1M-token context with image, video and audio inputs, built for long-horizon agentic coding. We’re excited to have worked https://t.co/MleWIPrBMD
- Clément Delangue Runs Muse-Spark-Open-816B-A42B-GGUF on Two Mac Studios
llama serve -hf ggml-org/Muse-Spark-Open-816B-A42B-GGUF:Q2_K (on two Mac studios). Well done @finkd & @johnternus!
- Meta’s Muse Spark Open now available in Amazon SageMaker JumpStart
Meta’s coding-optimized open-weight model Muse Spark Open is now available in Amazon SageMaker JumpStart in BF16 and NVFP4 variants, with a 1 million-token context window and 816B total parameters, including 42B active per token. AWS provides deployment instructions using SageMaker Studio or the SageMaker Python SDK, plus inference and cleanup examples. At launch, availability covers US East (N. Virginia) and US East (Ohio).
- 宝玉 · XPicksMeta releases Muse Spark Open with downloadable weights and conditional commercial use
Baoyu reports that Meta released Muse Spark Open on October 15, an open-weight model with 816B total parameters, 42B active parameters, and a 1M token context window. It accepts text, images, video, and audio and outputs text; the Muse Model License permits free commercial use subject to attribution, usage restrictions, and a separate agreement for qualifying API businesses. The model card lists minimum memory requirements of 700GB for NVFP4 and 2TB for BF16, while Meta describes optimization for two Mac Studio machines with 512GB unified memory each.
- Nathan Lambert predicts strong muse spark open adoption if reported scores hold up
Nathan Lambert predicts adoption of muse spark open will surge if its performance roughly matches its reported scores, calling it the first US open-weight model with near-frontier agentic capabilities. He compares the shift with GLM 5.2 and Kimi K3 in China. In the quoted announcement, @alexandr_wang describes muse spark open as having 816B total params, 42B active, 1M-token context, and native multimodality, built for coding and agentic work. https://t.co/9elY7xigU5
- Meta announces Muse Spark Open weights release today
Clément Delangue reacts with “Meta is back!” and links to https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B. In the quoted post, @finkd says Muse Spark Open weights are releasing today and that it runs great on new Mac Studios thanks to work with @johnternus and Apple. https://twitter.com/finkd/status/2110778025629347999
- Nathan Lambert Says He Needs to Blog After @AIatMeta Announces Muse Spark Open
@AIatMeta says it is releasing Muse Spark Open, which it calls “the most capable US open-weight model to date.” The quoted post says the model is built for coding and agentic work and lists 816B total and 42B active parameters, plus a 1M token [context window](https://t.co/yAtoxNeYJm). Nathan Lambert reacts: “Okay now I really gotta blog 🎉” https://t.co/uKl5X18Xpw
- Ollama · XPicksMeta releases Muse Spark Open, with Ollama availability coming shortly
Meta announced Muse Spark Open, calling it the most capable US open-weight model to date and describing it as built for coding and agentic work. Meta lists 816B total / 42B active parameters, a 1M token context window, and native text, image, video, and audio support. Ollama welcomed the release and said the model will be available on Ollama shortly. https://twitter.com/AIatMeta/status/2110779754274292212
- Alexandr Wang Opens Muse Spark and Asks Why 2026 Won’t Be Like 1984
muse spark open. why 2026 won't be like 1984 https://t.co/jYnOSfZf9u
- AI at Meta · XPicksMeta releases Muse Spark Open for coding and agentic work
Today Meta is releasing Muse Spark Open, which it calls the most capable US open-weight model to date. Built for coding and agentic work, Meta says it excels at long-horizon tasks, complex software engineering, and multi-step reasoning. Key model specs include 816B total / 42B active parameters, a 1M token context window, and native multimodality across text, image, video, and audio.
- Alexandr Wang Says Muse Spark Is the Most Capable US Open-Weight Model to Date
1/ Muse Spark open is the most capable US open-weight model to date. 816B total params, 42B active. 1M-token context. Natively multimodal. Built for coding and agentic work like long-horizon tasks, hard software engineering, and multi-step reasoning. America! 🇺🇲 https://t.co/NjtOB7aY9D
- Alexandr Wang Says Muse Spark Open Weights Are Out Today
Muse Spark Open — weights out today! Best US open-source model, and runs on the new Mac Studio 🍎 https://t.co/C8PU0RvlUA
- Hugging Face BlogPicksMeta 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.
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