Muse Video Description
Muse Video is Meta’s upcoming AI video generation model developed by Meta Superintelligence Labs as part of the company’s new media generation lineup. Previewed with Muse Image, the model is built on the same pretraining base and is designed to produce visually detailed videos with native audio support. Muse Video is focused on generating clips that follow prompts closely, maintain strong visual fidelity, and preserve temporal consistency across motion and scene changes. It can create realistic short videos with clear beginnings, actions, and payoffs, such as animals moving through a scene, handheld first-person footage, product commercials, and UGC-style social ads. The model supports audio-rich outputs that may include environmental sound, foley, music, voiceover, and synchronized spoken dialogue. Meta highlights Muse Video’s ability to handle cinematic prompts, vertical ad formats, realistic camera movement, product demonstrations, and emotionally engaging creative concepts. The company is still investing in improvements for difficult areas such as audio-video sync and physically accurate fast motion. Muse Video is expected to become available to creators and in Meta AI, expanding Meta’s generative AI tools from image creation into video. As part of Meta’s broader creative ecosystem, Muse Video is built to help users, creators, and businesses turn prompts into dynamic, shareable video content.
Muse Video Alternatives
Most AI video tools hand you a black box: closed weights, a subscription, and no way to see what is happening under the hood. LTX takes the opposite approach. Built by Lightricks, LTX is an open foundation model that generates and simulates across video, audio, and the physical world, and it puts the weights, the code, and the control in your hands.
At the center of the model is LTX-2.5, a 22B-parameter dual-stream diffusion transformer that produces native 4K video at up to 50 frames per second, with audio and video generated together in a single pass rather than stitched together afterward. Artificial Analysis, an independent benchmarking group, currently ranks LTX among the top three AI video models in the world.
You choose how you want to use it. Download the open weights and run LTX-2.5 on your own hardware. License the model for on-premise deployment backed by enterprise support. Or build directly on LTX Studio, the production suite that turns the model into a full creative workflow. Companies like ElevenLabs, Asteria Film Co., Magnopus, and NVIDIA already rely on LTX for their own work.
LTX is not built for one-off social clips. It is infrastructure for teams that generate motion, audio, and physical environments as part of their own products and pipelines.
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Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search across ChatGPT, AI Overview, AI Mode, Gemini, Claude, Perplexity, Meta, DeepSeek and Copilot.
We're building the first marketing platform for AI search as a channel. We show enterprise brands exactly where they stand when customers discover them through AI — then give them the precise playbook to show up stronger. This is Generative Engine Optimization, also known as AI SEO.
Using applied AI and data science at scale, we give brands statistical confidence in our actionable insights. We decode what gets brands mentioned more and ranked higher, provide reliable brand monitoring and competitive intelligence, then deliver actionable content strategies that move the needle. Our AI SEO and AI search engine optimization tools are built for how LLMs actually work.
Why Leading Enterprise Marketers Choose Evertune:
Data Science at Scale: We prompt across every major LLM at volumes that capture response variations and ensure statistical significance for comprehensive brand monitoring and competitive intelligence.
Actionable Strategy, Not Just Dashboards: Specific content, messaging and distribution tactics that increase your AI search visibility.
Dedicated Customer Success: Hands-on training and strategic guidance to turn insights into improved performance in AI search.
Built for AI search as a channel: Organic visibility today, paid advertising and commerce tomorrow.
Proven Leadership: Founded by The Trade Desk veterans who pioneered data-driven digital advertising. Backed by data scientists from OpenAI, Meta and other AI leaders.
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Muse Spark 1.2
Muse Spark 1.2 is Meta’s newest coding-focused model, released alongside Muse Code as part of Meta’s AI developer platform. The model improves on Muse Spark 1.1 with stronger code generation, complex debugging, codebase understanding, and full developer workflow performance. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan changes, write code, validate results, and coordinate persistent background subagents. The model was co-trained with Muse Code so it performs well inside the agentic coding runtime and tool environment. Its training included scaled coding compute, broader training environment diversity, rejection-sampled harness trajectories, recipe optimizations, and Muse Code toolset integration. Muse Spark 1.2 is designed for long-horizon coding tasks such as whole-repository generation, large end-to-end projects, auto-research, and extended optimization work. It uses planning to sequence work, goal conditioning to stay aligned with the user’s objective, and context compaction to preserve useful knowledge over long sessions. The model also benefits from a self-improvement loop where Muse Spark 1.1 generated challenging coding environments and instruction-following templates for training. By combining coding specialization, agentic workflow support, long-horizon training, subagent compatibility, and Meta Model API availability, Muse Spark 1.2 helps developers build, debug, and optimize software more effectively.
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Muse
Meta Muse is a personal AI agent built to help users complete everyday tasks rather than only answer questions in a chat interface. The service operates through a persistent secure virtual machine equipped with its own browser so it can navigate websites and carry out online workflows. Muse can help with activities such as scheduling appointments, completing forms, interacting with customer service, and making arrangements on the user’s behalf. Users can communicate with the agent through the Muse app or directly in WhatsApp using a conversational messaging interface. The agent can connect with services such as email, calendars, Instagram, and other frequently used applications to work across a broader set of personal tasks. Muse can turn goals into action plans, track progress, and proactively suggest additional steps based on what the user is trying to accomplish. For consequential actions such as sending emails or completing purchases, the system can request approval before proceeding and provides an audit trail of agent activity. Login credentials are stored in a secure credential system that the agent itself cannot read, while checkout workflows can use one-time card numbers so the user’s primary payment information is not exposed. Muse is designed for people who want an AI agent that can actively execute tasks, coordinate across apps, and continue working toward goals with user oversight.
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Integrations
Company Details
Company:
Meta
Year Founded:
2004
Headquarters:
United States
Website:
meta.ai
Media
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support
Muse Video Features and Options
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