Reflection AI launched Beam, an open-weight sparse Mixture-of-Experts model for agentic coding and long-horizon software tasks. Beam has 501 billion total parameters, with 23 billion active parameters per forward pass. The release adds new options to deploy Beam on AWS—using SageMaker JumpStart or Kubernetes-native SageMaker HyperPod Inference—and to choose BF16, FP8, or NVFP4 checkpoint formats with corresponding memory and scaling tradeoffs.
Meta unveiled Muse Spark Open, an open-weight AI model with 816 billion parameters built to run on consumer hardware. In its benchmarks, Meta reports running it on two paired M5 Ultra Mac Studios while activating 42 billion parameters per token. The release expands Meta’s open-weights options with a model architecture and hardware pairing aimed at making large-scale inference more accessible.
Meta released Muse Spark Open, an open-weight multimodal coding/agent model, and made its weights available for download and API use. The release includes 816B total parameters with a 1M-token context window, and it runs on two Apple M5 Ultra Mac Studios together with MLX. This enables developers to run and customize the model locally (and on more inference engines) rather than relying only on hosted closed models.
StepFun launched a preview of its open-weight Mixture-of-Experts model, Step 5 Preview, for coding, financial research, and long-running agents. It has 600B total parameters with 27B active per token and a 1M-token context. The model is offered with deployment support for vLLM, SGLang, and Transformers.
Meta Superintelligence Labs released Muse Spark Open, the open-weight version of its Muse Spark model, with support for text plus image, video, and audio inputs. The model is 816B parameters total and has a 1M-token context window. Developers can deploy it on multiple engines and hosted APIs, with hardware options ranging from 2 Apple M5 Ultra Mac Studios (via MLX) to data-center setups using NVFP4 on Blackwell Ultra or H200 GPUs.
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