Muse Spark Open
Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.
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Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL is an open, customizable multimodal AI model designed for complex reasoning, autonomous agents, and enterprise workflows. The model uses a 120-billion-parameter mixture-of-experts architecture that activates approximately 12 billion parameters per token to balance computational efficiency with model capabilities. It combines text, image, document, and video understanding with instruction following, coding, and external tool use. Its multimodal capabilities support document analysis, chart interpretation, optical character recognition, video understanding, and automated information extraction. Developers can customize the model through supervised fine-tuning, low-rank adaptation, and reinforcement learning using NVIDIA NeMo. Nemotron 3.5 Super VL supports deployment in local, cloud, and data center environments for applications such as software engineering, financial document processing, cybersecurity analysis, and enterprise automation.
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MiMo-V2.6-Pro
MiMo-V2.6-Pro is Xiaomi MiMo’s most capable open-source omnimodal AI model, built for coding, general agent workflows, visual tasks, research, and multimodal creation. The model combines strong software engineering capabilities with computer use, 3D spatial reasoning, visual perception, and tool use for complex multi-step work. MiMo-V2.6-Pro can build interactive 3D environments, generate Blender models, create frontend interfaces and presentations, and coordinate agents to refine outputs through visual feedback. It also supports research workflows such as literature review, computational experimentation, materials discovery, and formal mathematical proof development. Xiaomi trained the model with large-scale reinforcement learning across coding, general agents, visual tasks, and cybersecurity environments and has open-sourced the technical report, training environments, and RL code.
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GLM-5.3
GLM-5.3 is Z.ai’s frontier coding model designed for complex software engineering, long-horizon agent tasks, and advanced post-training research. The model uses the same base model as GLM-5.2, with improvements coming from scaled post-training across more environments, more diverse tasks, and larger compute investment. GLM-5.3 delivers stronger coding performance, better task ownership, improved benchmark results, and greater efficiency across realistic development workflows. It is built to handle complex coding tasks, production-style engineering work, research environments, automation tasks, and agentic workflows that require multi-step execution. The model also shows emergent cyber capabilities in vulnerability discovery and exploitation-chain reasoning, with safety evaluation and hardening planned before open-weight release.
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