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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.
  2. Artificial Analysis full articleSelected

    Reflection Releases Its First Model Beam, Scoring 30 on the Artificial Analysis Intelligence Index

    Reflection has released its first model, Beam, an open-weight model with 501B total parameters and 23B activated parameters. It scores 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). Beam consumes about 26k output tokens per Intelligence Index task, of which about 19k are used for reasoning and 7k for answering; it scores 48.5% on AutomationBench-AA, but only 3.0% on Terminal-Bench 4.0. On AA-Omniscience, it answers 33% of questions correctly, with a hallucination rate of 47% and a net index score of 1.5.

    Reflection has released its first model, Beam, an open-weight model with 501B total parameters and 23B activated parameters. It scores 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). Beam consumes about 26k output tokens per Intelligence Index task, of which about 19k are used for reasoning and 7k for answering; it scores 48.5% on AutomationBench-AA, but only 3.

    Matched fieldsSummary、Body

    #company#Model releases#Open-source ecosystem#Evaluations / benchmarks

Thursday

  4. 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.

    Matched fieldsSummary

    #hot-signal#Product updates#Multimodal#Agents