Muse Spark Open

Headlines · 6

1. 4h
   AI safety worries mount as the industry keeps racing ahead

   This week's enterprise AI roundup reports that after a run of "rogue agent" incidents, more government officials are calling for regulation, several states are suing OpenAI, about 400 scientists urged global AI oversight, and Microsoft's president said AI is less regulated than a carton of milk. On the money side, Anthropic told investors revenue grew 45% sequentially to $16.8B in Q3, a slowdown that could pull its planned IPO valuation from $2T toward $1.5T, while CoreWeave's debt load weighed on neocloud and supplier shares. On models and products, Meta released the 816B-parameter open-weight Muse Spark Open for coding and agent work plus Muse Wonder for personal and professional agents, Nvidia expanded its Nemotron family, and Grok Voice 3.0, Gemini 4 Argon and Microsoft's Maia 300 also arrived, alongside news that Character.AI filed for bankruptcy.

   SiliconANGLE AI · 🔥 9
2. 10h
   Apple and Meta team up to run Muse Spark Open locally on Mac Studio

   According to an analysis published on Huxiu, Meta's open-weight model Muse Spark Open will be able to run locally on clusters of M5 Ultra-equipped Mac Studio machines, with Apple providing on-device inference through its MLX framework and multi-machine coordination. The article says the model has roughly 816 billion total parameters and about 42 billion active parameters, and that Apple's machine learning team found it needs more than 1.6TB of memory at native precision and still about 493GB with 4-bit quantization, requiring several Mac Studios in parallel. It places the move alongside Apple's earlier integration of ChatGPT into Siri and of Google Gemini into Apple Intelligence, arguing Apple wants more models to run well on its hardware while Meta trades open weights for developer adoption and enterprise deployment.

   虎嗅 AI · 🔥 12
3. 22h
   SGLang and Miles add day-0 support for Muse Spark Open

   An LMSYS blog post says SGLang and Miles have added day-0 support for Muse Spark Open, an open-weight multimodal mixture-of-experts model. Its text backbone has 816B parameters with roughly 42B active parameters per token, accepts text, image, video and audio inputs, supports a 1M-token context window, and ships NVFP4 and BF16 checkpoints. The SGLang integration adds sequence parallelism with NVFP4 MegaMoE for prefill, multimodal preprocessing optimizations and DFlash V2 speculative decoding; the team reports that on 8 NVIDIA B300 GPUs with the NVFP4 checkpoint, an OpenHands multi-turn agentic coding replay reaches 14.8K total tokens/sec per GPU at concurrency 1 and 80.3K at concurrency 128.

   LMSYS Blog · 🔥 5
4. 2d
   Meta releases Muse Spark Open, an 816B open-weight multimodal coding model

   Meta released Muse Spark Open, an open-weight mixture-of-experts model with roughly 816 billion total parameters and about 42 billion active per token, accepting text, images, audio and video with a context window of up to one million tokens. Meta says it is built for agentic coding and long-horizon tasks and calls it “the most capable US open-weight model to date,” adding that its own benchmarks show it beating GLM-5.3 and Kimi K3 on agentic and visual-reasoning tasks. Weights are available on Hugging Face, with day-one hosting from Together AI and Modal, while Bloomberg reports Meta kept its most advanced models closed.

   Hugging Face · 🔥 153
5. 2d
   vLLM ships day-0 support for Meta's Muse Spark Open 816B open-weight MoE model

   vLLM said it worked with Meta Superintelligence Labs to bring day-0 serving support to Muse Spark Open, an open-weight sparse mixture-of-experts model. According to the vLLM blog, the model has 816B total parameters with 42B active per token and a 1M-token context window, ships in BF16 and NVFP4 (AMD released MXFP4 weights), and handles image, video and audio input through the same Perception Encoder used by Muse Glimmer. vLLM also offers a DSpark speculative-decoding draft model trained by Inferact, support on NVIDIA, AMD Instinct MI355X and TPU, and a LoRA reinforcement-learning recipe that lifted AIME-2024 (mean@8) from 0.56 to 0.85 after 150 GRPO steps on 16 GB300 GPUs.

   vLLM Blog · 🔥 3
6. 2d
   Apple's MLX adds RDMA-distributed inference across Mac Studio clusters

   Apple's machine learning research team published benchmarks showing how the latest MLX release, combined with the low-latency RDMA over Thunderbolt 5 driver added in macOS 26.2, can run frontier-scale open-weight models across multiple Mac Studio computers. On four M5 Ultra Mac Studios, the 816B-parameter Muse Spark Open mixture-of-experts model (42B active, NVFP4) generates over 36 tokens per second at an 8,192-token context, while a single 512GB Mac Studio runs Qwen 3.8 27B and Mistral Medium 3.5 128B. Apple reports the M5 Ultra improves time to first token by up to 4.6x and decode speed by 1.6x versus M3 Ultra, and says pipeline parallelization lifted prefill by up to about 1.8x at 65,536-token contexts.

   Apple Machine Learning Research · 🔥 3

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