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Friday

  1. heise onlineSelected

    Meta Releases 816B Open-Source Model Muse Spark Open, Partnering with Apple for Local Execution

    Meta has released the open-weight model Muse Spark Open, which uses a MoE architecture with 256 experts, activates about 42B parameters per token, has a context window of 1 million tokens, and supports text, image, video, and audio input but outputs text only. Meta has partnered with Apple to run the approximately 530 GByte four-bit quantized version on two interconnected Mac Studio M5 Ultra machines, distributing computation via the MLX framework and Thunderbolt 5, achieving about 25 output tokens/second at an 8192-token context. Artificial Analysis tests show that it scores 39 on the Intelligence Index, making it the strongest American open-weight model currently available, but it trails MiMo-V2.6-Pro's 46 points and GLM-5.3's 45 points, and ranks last in four Agent tests. The model weights are available on Hugging Face in two versions: 16-bit at approximately 1.6 TByte and four-bit at approximately 530 GByte, with API pricing at $1.25 per million input tokens and $4.25 per million output tokens.

    Meta has released the open-weight model Muse Spark Open, which uses a MoE architecture with 256 experts, activates about 42B parameters per token, has a context window of 1 million tokens, and supports text, image, video, and audio input but outputs text only. Meta has partnered with Apple to run the approximately 530 GByte four-bit quantized version on two interconnected Mac Studio M5 Ultra machines, distributing computation via the MLX framework and Thunderbolt 5, achieving about 25 output tok

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Thursday

  1. OpenRouter

    NVIDIA Nemotron 3.5 Super VL Launches on OpenRouter

    NVIDIA Nemotron 3.5 Super VL is now available on OpenRouter. It is an open-source 120B-A12B multimodal model designed for long-running agents that need to observe, reason, and act across text, images, documents, GUIs, and video, with support for a 1M context. The model uses a Hybrid Mamba-Transformer MoE architecture and supports multi-token prediction to speed up output, targeting scenarios such as document intelligence, web research, customer service, and video understanding.

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