Multimodal prompting
The model is presented in an image-text-to-text workflow: an image and a written prompt are provided, and the model returns text.
Muse Spark Open
Muse Spark Open is a Meta vision-language model on Hugging Face that combines an image with a text prompt to generate a textual response. It is intended for visual question answering, image description, multimodal assistant workflows, and permitted model adaptation, subject to its license and Usage Policy.
Muse Spark Open overview
Muse Spark Open is a Meta model distributed on Hugging Face as an image-text-to-text, or vision-language, model. Its core workflow combines an image with a text prompt and produces a textual response, making it suitable for asking questions about visual inputs rather than limiting use to fixed image captioning.
The supplied evidence does not include a complete model card with architecture, parameter specifications, benchmarks, context length, deployment requirements, provider availability, or model-specific setup instructions. Readers should therefore treat the task-level capabilities as workflow context, not as confirmation of every capability or performance characteristic of this release. The Muse Model License permits commercial and noncommercial handling of the software, including fine-tuning and derivatives, subject to attribution, usage-policy, and Model as a Service conditions.
Key features
Conversation-oriented interaction
Image-text-to-text systems can support conversational interactions that retain the image as context across multiple turns, although the supplied evidence does not confirm every conversational behavior for this specific release.
Visual question answering
The workflow can be used to ask questions about visual content, generate descriptions, and interpret image details through natural-language prompts.
Document and layout understanding
The broader task category supports document question answering and information extraction from layouts, charts, tables, and images without requiring a separate OCR step; model-specific document performance is not documented in the supplied evidence.
Permitted model adaptation
The license explicitly permits modification, including fine-tuning, and creation of derivative models, subject to the license and Usage Policy.
Licensed distribution on Hugging Face
The model is distributed through a Hugging Face model page under the Muse Model License, with access gated by a form requesting legal and organizational information.
Potential workflows
Image analysis and description
Provide an image and ask for a natural-language description of its contents, objects, or relationships. This is a general workflow supported by the image-text-to-text task category; release-specific quality is not documented.
Visual question answering
Use a visual input as context for questions about what appears in an image, including details or relative positions that can be expressed in text.
Document question answering
Prompt a vision-language model with pages, charts, tables, or other formatted material to retrieve information in text. The evidence describes this as a category-level workflow and does not establish Muse Spark Open’s document accuracy.
Multimodal assistants
Use image-and-prompt interactions as part of an assistant that maintains visual context over multiple turns, provided the implementation and model behavior support that pattern.
Research and model adaptation
Adapt the released software for a specialized application through fine-tuning or derivative-model development, while observing the license, attribution requirement, and Usage Policy.
Pros and Cons
Pros
- Accepts an image together with a natural-language prompt and returns text.
- Supports a broad vision-language workflow that can extend beyond fixed captioning to visual questions and descriptions.
- The license permits copying, modification including fine-tuning, and creation of derivative works, subject to its conditions.
- Hosted on Hugging Face, providing a public model-distribution page and access workflow.
Cons
- The supplied product evidence does not provide architecture details, benchmarks, resource requirements, context length, quantization information, or deployment instructions.
- Some image-text-to-text capabilities described for the broader task category are not confirmed as model-specific features.
- Use is subject to a Usage Policy, required attribution, and additional conditions for qualifying Model as a Service offerings.
FAQ
What kind of input and output does Muse Spark Open use?
Muse Spark Open accepts image-and-text inputs in an image-text-to-text workflow, where the model generates text in response to a prompt. The supplied evidence does not document a model-specific chat template or setup command.
Can the model be modified or fine-tuned?
The license permits use, copying, modification including fine-tuning, derivative works, distillation, merging, publication, distribution, sublicensing, and sale, subject to the license and Usage Policy.
What attribution is required?
Users must prominently display “Built with Muse Spark Open” in the user interface of each product or service using the software or its derivatives, or in accompanying documentation, website, or settings menu.
Are there special terms for offering the model through an API?
The supplied license says that if a licensee or affiliate offers the software or a derivative through a Model as a Service business and aggregate gross revenue exceeds 20 million US dollars, the licensee must notify Meta and enter a separate written agreement before offering it in that business. The provision does not apply to internal use, research, non-Model-as-a-Service commercial activity, or use as a component of the licensee’s own product or service.
What usage restrictions should deployers review?
The Usage Policy prohibits unlawful activity, harassment, discrimination or harmful conduct in essential services, unauthorized professional practice, unlawful handling of sensitive information, rights infringement, malicious code, circumvention of safeguards, and specified activities involving risks of death or bodily harm. Deployers are responsible for safe use in context, and the model is not intended for people under 18.
Quick Facts
- Product type
- Vision-language model
- Primary task
- Image-text-to-text
- Publisher
- Meta
- Distribution
- Hugging Face model page
- License
- Muse Model License
- Release date stated in source
- October 15, 2026
Alternatives à Muse Spark Open
Grok 4.7
Grok 4.7 is an xAI model for software development and knowledge work, including extended coding tasks and professional analysis. It is available through Grok Build, Cursor, the Grok API, and other developer platforms, with token pricing starting at $2 per million input tokens and $6 per million output tokens.
AakarDev AI
AakarDev AI helps teams manage AI provider access, project-level setups, logs, and analytics from one dashboard. It supports BYOK workflows and lists providers including OpenAI, Google Gemini, Anthropic, Groq, Mistral AI, and Perplexity AI.
Snapmark
Snapmark is a VS Code extension that lets you annotate clipboard screenshots before pasting them into AI chats. It supports blur redaction, numbered callouts, and automatic resizing for large images.
BookAI.chat
BookAI vous permet de discuter avec vos livres en utilisant l'IA en fournissant simplement le titre et l'auteur.
Skills Janitor
Skills Janitor is a GitHub-hosted set of slash commands for auditing, tracking, and managing Claude Code and OpenAI Codex skills. It helps users find duplicates, broken links, and unused skills, then clean them up with self-contained commands.
Arduino VENTUNO Q
Arduino VENTUNO Q is an edge AI computer for AI and robotics applications. It combines AI inference and deterministic control on a single board and is designed to work with Arduino App Lab.