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Friday

  1. Baseten Engineering BlogSelected

    Reflection's Open-Weight Model Beam Launches on Baseten: 501B MoE with 1M Context

    Reflection's first open-weight model, Beam, is now available on the Baseten platform, with day-0 support through Baseten Model APIs and Dedicated Inference. Beam uses a MoE architecture with 501B total parameters and 23B activated per token, a context window of up to 1 million tokens, and is aimed at coding and agent workflows. During training, Reflection used longer RL rollouts and added a length penalty to encourage the model to complete tasks with fewer tokens; users can also adjust reasoning effort via a parameter to control how much reasoning the model invests.

    Beam

    Reflection's first open-weight model, Beam, is now available on the Baseten platform, with day-0 support through Baseten Model APIs and Dedicated Inference. Beam uses a MoE architecture with 501B total parameters and 23B activated per token, a context window of up to 1 million tokens, and is aimed at coding and agent workflows. During training, Reflection used longer RL rollouts and added a length penalty to encourage the model to complete tasks with fewer tokens; users can also adjust reasoning

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    #editorial#Product updates#Reasoning#English text is being prepared.
  11. Rohan PaulSelected

    Meta open-sources 816B-parameter model Muse Spark Open on Hugging Face

    Meta has released the model weights of Muse Spark Open on Hugging Face, an 816B-parameter model aimed at coding and agent tasks. The open-source version shares the same base model as Muse Spark 1.3, with additional safety post-training to reduce the risk of misuse when used standalone without system guardrails, reversing Meta's strategy of its first proprietary closed frontier model in April this year. The model has 62 layers, each containing 256 expert networks, with each token routed to 8 of them, so deployment requires the memory of an 816B-parameter model but runs at the speed of a 42B model. A 3-bit quantized version tested on a 512GB M3 Ultra occupies about 344 GB, with generation speed of about 21 tok/s under short prompts.

    Meta has released the model weights of Muse Spark Open on Hugging Face, an 816B-parameter model aimed at coding and agent tasks. The open-source version shares the same base model as Muse Spark 1.3, with additional safety post-training to reduce the risk of misuse when used standalone without system guardrails, reversing Meta's strategy of its first proprietary closed frontier model in April this year. The model has 62 layers, each containing 256 expert networks, with each token routed to 8 of t

    Matched fieldsSummary

    #ai-news#Model releases#Open-source ecosystem#English text is being prepared.
  12. Unite.AISelected

    Meta open-sources 816B-parameter multimodal model Muse Spark Open

    On October 15, Meta released the weights of Muse Spark Open, a natively multimodal open-source model with 816B total parameters, 42B activated parameters, and a 1M token context window, targeting coding and long-horizon agent tasks. The model uses a MoE Transformer plus Perception Encoder architecture, can be invoked through API platforms such as Baseten, Fireworks AI, and Groq, with weights downloadable from Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, and elsewhere; running the NVFP4 version locally requires at least 700GB of VRAM. Meta claims it is the first model of its class that can run on desktop, carried by two Mac Studios equipped with M5 Ultra paired with the MLX framework; the model card shows its Artificial Analysis Intelligence Index at 39, lower than GLM 5.3's 45 and Kimi K3's 44 in the table.

    On October 15, Meta released the weights of Muse Spark Open, a natively multimodal open-source model with 816B total parameters, 42B activated parameters, and a 1M token context window, targeting coding and long-horizon agent tasks. The model uses a MoE Transformer plus Perception Encoder architecture, can be invoked through API platforms such as Baseten, Fireworks AI, and Groq, with weights downloadable from Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, and elsewhere; running th

    Matched fieldsSummary

    #hot-signal#Model releases#Multimodal#Open-source ecosystem
  14. The New StackSelected

    Meta releases 816B open-source model Muse Spark Open

    Meta releases Muse Spark Open, an open-weight model with 816B parameters and 42B activated parameters, using a 1 million token context window, callable via APIs such as Baseten, Fireworks AI, Groq, and OpenRouter, with weights downloadable from Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, and others. Meta says it targets coding and agent tasks and leads Kimi K3, GLM 5.3, and Qwen3.8 on agent and tool-calling benchmarks such as JobBench and MCP-Atlas, but trails on coding benchmarks such as Terminal-Bench 2.1 and DeepSWE 1.1. The model uses the Muse Model License; companies with annual revenue over $20 million must first notify Meta and sign a separate agreement to offer model services, and users must prominently label Built with Muse Spark Open in product interfaces.

    Meta releases Muse Spark Open, an open-weight model with 816B parameters and 42B activated parameters, using a 1 million token context window, callable via APIs such as Baseten, Fireworks AI, Groq, and OpenRouter, with weights downloadable from Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, and others. Meta says it targets coding and agent tasks and leads Kimi K3, GLM 5.3, and Qwen3.8 on agent and tool-calling benchmarks such as JobBench and MCP-Atlas, but trails on coding benchma

    Matched fieldsSummary

    #hot-signal#Model releases#Open-source ecosystem#Reasoning

Thursday