OpenAI Dots vs. Meta Muse: Which Agent Wins?

Two of the biggest AI labs shipped the same idea three weeks apart: an AI agent that doesn't wait for your next prompt. Instead of answering one question at a time, it has its own computer in the cloud, keeps working toward the goals you give it, and messages you when it needs a decision.

Meta went first with Muse, a consumer agent it describes as "built for everyone." OpenAI followed at DevDay with Dots, which it pitches as always-on agents that can keep working toward your goals 24/7.

On paper, the two sound almost identical. In practice, they make different bets about who the user is, where the agent should live, and how much control you need over it.

In this article, I compare them across models, architecture, safety, integrations, pricing, and availability. I finish with a recommendation for which one to try first. 

The short version: People think of it this way:

• Dots are built for work. They plug into workplace tools, offer fine-grained admin rules, and are heading toward specialist enterprise agents.
• Muse is built for life admin: shopping, booking, and errands, with payment protection through Stripe and a free way in.

If you're new to agentic AI, our AI Agent Fundamentals track covers the concepts behind both products.

What Are OpenAI Dots?

A dot is a persistent agent inside ChatGPT. You give it ongoing responsibilities, such as tracking competitor pricing every Monday, triaging an inbox, or preparing weekly reports, and it keeps working on them between your conversations.

Key facts:

• Model: GPT-6 Astra.
• Compute: Each dot has its own cloud computer and browser. You can open that computer to watch what it's doing, and you can optionally connect the dot to your laptop.
• Where you reach it: ChatGPT on desktop, web, and mobile (including voice calls), plus Slack and Teams. Context carries over between them.
• Apps: More than 4,000 through OpenAI's plugin ecosystem.
• Specialist dots (preview): Enterprise agents with their own identity, credentials, and system access. They're being piloted for procurement, invoice processing, email marketing, customer support, and contracting.

What Is Meta Muse?

Muse is Meta's personal AI agent. It's designed to take on goals like "find and book a weekend trip under $800" or "turn this saved recipe reel into a grocery order," then carry them out across your connected apps.

Key facts:

• Model: Muse Spark 1.3, with a 1M-token context window.
• Compute: A dedicated Muse Secure VM in Meta's cloud, with its own browser, file system, and terminal. You can watch the browser as it works.
• Where you reach it: The Muse app on iOS and Android, muse.ai, and WhatsApp. AI glasses support and Muse Charm, a small keychain device for using Muse without a phone, were announced on September 23.
• Commerce partners: Stripe, Shopify, Best Buy, Gap, Sephora, Walmart, Wayfair, Expedia, Instacart, and more.
• Personalization: You can set your agent's name, avatar, and communication style.

OpenAI Dots vs. Meta Muse: Head-to-Head

Let me compare them across a few categories:

Model and intelligence

Dots run on GPT-6 Astra, and Muse runs on Muse Spark 1.3. Both companies claim frontier-level agentic performance. However, Meta's parity claims against OpenAI and Anthropic rely on its own numbers, and there are no independent agent benchmarks for either product yet. 

One practical difference: Muse's top reasoning mode was held back at launch pending safety testing. Dots get the full Astra model.

Architecture: two kinds of cloud computer

Both agents run on a remote machine instead of your device. That lets them keep working while your laptop is closed.

• Dots give each agent its own cloud computer, kept separate from yours unless you connect them. A monitoring system can pause or stop a dot if it detects a safety concern.
• Muse puts the agent and your data on a dedicated VM. A second agent, Sentinel, runs on the same machine but is isolated from Muse at the system level. Muse can't reach the internet without Sentinel's approval, and Sentinel asks you when it's unsure.

Muse's gatekeeper design is the more distinctive idea. 

Safety and permissions

Dots give you a rules engine:

• Custom Rules let you allow, require approval for, or block specific actions.
• Auto-review checks any action that could affect your accounts or share information. You can't turn it off.
• Proactive research runs with read-only tools by default, so the dot can't send messages, change content, or control a browser while doing background work.

Muse uses a permission model:

• You connect apps one at a time and choose the access level for each. For example, you can let it read email but not send it.
• It checks with you before sensitive actions such as sending email or making a purchase.
• It keeps an audit trail of completed and planned actions.

Both products let the agent use saved logins without exposing passwords to the model. OpenAI does this through ChatGPT's credential handling, and Meta through secure storage.

Bottom line: If you need precise control over what an agent can do, especially across a team, Dots offer more options. Muse is easier to understand at a glance, but reviewers have asked for finer-grained permissions, such as limiting access to specific Instagram accounts.

Integrations and where they live

Dots live where knowledge workers already are: ChatGPT, Slack, and Teams, with 4,000+ app connections and a Microsoft Agent 365 integration in progress.

Muse lives where consumers already are: its own app, WhatsApp, Instagram, and soon Meta's AI glasses. Its integrations lean toward commerce. Checkout goes through Link by Stripe, which issues a one-time card so the agent never sees your real card number. Meta says Muse is the first AI agent covered by Link's purchase protections, including coverage for lost or damaged items and no-fee returns.

That focus on commerce has also caused friction. On September 21, Amazon blocked Muse from its retail site, saying the agent didn't identify itself. Meta disputed Amazon's account. 

Meta has since launched Muse for Small Business, which connects the agent to tools like Slack, Zoom, and Salesforce.

Memory and proactivity

Both agents remember context :

• Dots learn from feedback, run scheduled checks, and do proactive research. At launch, though, you can't view or edit individual memories.
• Muse remembers details you mention only once and makes unprompted suggestions. You can tell it to "forget" specific things.

Privacy and data use

• Dots: Business, Enterprise, and Edu workspace data isn't used for training by default. Personal plan users can choose whether theirs is.
• Muse: Interactions are used for training by default, and you can opt out in settings. In October, a security group reported that shared Muse chats could be discovered through public DNS records, and Meta suspended chat sharing in response.

For regulated or sensitive work, OpenAI's workspace defaults are the safer starting point today.

Pricing and Availability

The pricing gap is the clearest difference between the two. You can try Muse for free today if you're in the US. Getting a dot means paying for a top-tier ChatGPT plan.

Which One Should You Choose?

Choose OpenAI Dots if:

• You already pay for ChatGPT Pro or Business Premium.
• The work you want to hand off happens in Slack, Teams, docs, and SaaS tools.
• You need detailed approval rules, or your organization needs admin controls and training-data defaults that protect workspace content.
• You're outside the US, but in an eligible OpenAI market.

Choose Meta Muse if:

• You're in the US and want to try an agent without paying for a premium plan.
• Your to-do list is mostly personal: shopping, bookings, travel, and household tasks.
• You value purchase protection and one-time cards for agent checkouts.
• You live in WhatsApp and Instagram more than in Slack.

Choose neither if:

• You don’t want an AI agent acting on your behalf, whether that’s clicking, buying, or sending messages.
• You’d spend as much time checking the agent’s work as you’d spend doing the task yourself.
• You’re not comfortable giving software access to your accounts, payment methods, or workspace content.
• Your tasks are infrequent or simple enough that a to-do list, a calendar, or a saved checkout does the job.

Consider building your own agent instead if you need per-task cost control, reproducible evaluations, or a workflow neither product supports. Neither Dots nor Muse has an API yet. Our OpenAI API tutorial and Muse Spark 1.3 tutorial are good starting points.

Final Thoughts

OpenAI is betting on work. Dots live in your workplace tools, rely on detailed rules, and point toward a future of specialist agents with their own credentials inside companies. Meta is betting on everyday life. Muse lives in your messaging apps, handles payments, and comes with a free tier that puts an agent in front of millions of people.

Both are early. Neither has independent benchmarks, both companies say their agents will make mistakes, and both have unpublished usage terms that could change the value calculation. My advice is to start with one bounded, recurring task, review what the agent does closely, and only expand its access once it has earned your trust.

To learn the fundamentals behind both products, check out our AI Agent Fundamentals track and our Introduction to Agent Skills course.