OpenAI Dots vs Meta Muse: Which The Better AI Agent?

OpenAI introduced Dots on September 29, three weeks after Meta launched Muse. Both promise an assistant that keeps working after the chat ends. The meaningful question is not which mascot looks friendlier, but which agent can finish the work you actually delegate, within permissions you understand. On the companies' published evidence, Dots has the clearer workplace proposition; Muse is the more accessible starting point for US consumers. Neither has won an independent head-to-head test.

Same Idea, Different Jobs

OpenAI says Dots runs on GPT-6 Astra, with its own cloud computer, browser and access to more than 4,000 apps through plugins. It can follow a project across ChatGPT, Slack and Teams, investigating a reported bug or preparing drafts for review. That makes it closer to the persistent work assistant discussed in our guide to building AI agents than a chatbot waiting for a prompt.

Meta's Muse uses a dedicated cloud computer and Muse Spark 1.3 to tackle travel, shopping and longer-term personal plans through its app or WhatsApp. Do not confuse that standalone agent with the earlier agent features in Meta AI. Its reach into everyday messaging gives Meta a different distribution advantage, though distribution alone says little about task completion.

Which Agent Fits a Real Workflow?

Dots' cross-app context could help a team coordinate documents, coding and approvals. It is an attractive fit when work already flows between business systems, but connecting many services also expands the permission decisions an administrator must make. Our reporting on agent plugin interoperability explains why a long integration list is not itself evidence of reliable execution.

Muse has a more concrete consumer pitch: plan a dinner, book travel or pursue a recurring goal without learning a workplace tool stack. In a CNN hands-on account, the reviewer used Muse to arrange a date night and prepare a moving schedule. That is useful evidence of one person's experience, not a controlled comparison with Dots. It also differs from Meta's broader open-AI ambitions.

Control Matters More Than Personality

Both agents need access to accounts. OpenAI says Dots' background research uses read-only tools, while action checks, approval rules and an activity view govern more consequential work. Meta describes a separate Sentinel permission system around Muse's isolated cloud machine, with controls over connected apps and an audit trail. These are vendor-described safeguards, not guarantees against mistakes or malicious instructions.

Muse asks permission before sending email or buying goods. Meta points to Link purchase protections for eligible purchases, but their coverage has conditions; its proposed Confidential VM is a future feature, not a launch-day privacy guarantee. OpenAI likewise says users should review consequential outputs. For another model of external agent controls, see our report on NVIDIA's agent safety architecture.

Price, Access and the Verdict

Meta says Muse is rolling out in the US on mobile and web, free for most needs with paid plans for heavier use; it has not given a universal price for every workload. OpenAI's getting-started guidance says Dots is gradually arriving for eligible Pro and Business Premium users, with an enterprise beta. Initial Pro availability excludes the UK, Switzerland and European Economic Area. Your location and existing subscription may settle the choice before any feature comparison.

The Verge calls Dots a Muse competitor, but the products are not interchangeable. Choose Dots first if your priority is supervised, multi-app professional work and you already qualify for access; choose Muse if your priority is everyday assistance in the US. Test either on reversible tasks before granting spending or messaging authority. AI provenance concerns in our watermarking coverage are another reminder that accountable output matters. Without matched tests of reliability, cost and safety, there is no defensible overall winner.