Muse Ember
Muse Ember is an efficient multimodal AI model developed by Meta for autonomous agents, software engineering, complex reasoning, and high-volume task automation. The model specializes in repetitive agentic operations such as tool calling, code analysis, information extraction, workflow routing, and document processing. It supports text, images, audio, video, and PDF inputs with a one-million-token context window and a maximum output length of 512,000 tokens. Muse Ember can execute multistep business workflows, analyze large software repositories, perform coding tasks, and interpret visual information from documents and screenshots. Its cost-efficient architecture makes it suitable for multi-agent systems in which larger models handle planning while Muse Ember executes frequent subtasks. The model is available through Meta Model API and Muse Code, with API pricing starting at $0.10 per million input tokens and $0.50 per million output tokens.
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Muse Spark Open
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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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Kimi K3.1 Pro
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Kimi K3.1 Pro is a multimodal large language model developed by Moonshot AI for advanced reasoning, software development, 3D modeling, financial analysis, and autonomous AI agent workflows. The model uses a mixture-of-experts architecture with approximately 2.8 trillion total parameters and 104 billion active parameters, supporting a context window of one million tokens. Its coding capabilities include debugging existing applications, generating complete software projects, developing interactive websites, and creating applications with game engines. Kimi K3.1 Pro can analyze images, interpret spatial relationships, generate CAD scripts, and create three-dimensional assets from text descriptions or visual references. Its reasoning and tool-use capabilities support financial modeling, investment research, document analysis, and multistep business workflows. The model is available through Kimi's web and mobile applications, Kimi Work, Kimi Code, and the Kimi API, with a Highspeed variant.
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Gemini 4 Carbon
Gemini 4 Carbon is an advanced multimodal AI reasoning model developed by Google DeepMind for cybersecurity, software engineering, scientific research, and autonomous agent workflows. Building on Gemini 4 Argon, the model delivers improved performance in vulnerability discovery, exploit validation, secure code generation, and automated software patching. Its long-horizon reasoning capabilities enable AI agents to work through complex engineering problems over extended periods, including debugging large codebases and resolving low-level system issues. Gemini 4 Carbon also supports full-stack web development, multimodal understanding, technical analysis, and multistep task execution. The model incorporates safety mechanisms for prompt injection resistance, monitoring, and alignment while reducing unsupported claims and unauthorized actions.
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