Brave Leo vs Gemini Advanced (2026): browser privacy or Google AI

Brave Leo: the assistant in Brave

Brave Leo lives in the Brave browser on desktop and mobile. It can answer questions about the current page, summarize webpages, PDFs, Google Docs and Sheets, translate text, and help draft or analyze content. Brave also offers Bring Your Own Model, which can use a local or remote model.

Brave’s stated privacy design is central here. It says Leo does not retain or share chats, does not use them for additional model training, and does not require an account for the free experience. Brave says it sends the prompt, conversation context, and necessary page context to generate a response without collecting identifiers that can be linked to the person. Optional history can be kept locally on the device.

Leo Premium is currently listed by Brave at $14.99 per month or $149.99 per year. Brave says it brings higher limits, more models, and early access to new features. Check the live page before buying because models and availability change.

Gemini: Google AI across its products

Gemini is a broader Google AI experience, available through the Gemini app and in selected Google products. Google’s AI plans page currently presents Google AI Pro and Google AI Ultra rather than a tier named “Gemini Advanced.” In the United States, Google lists AI Pro at $19.99 a month, but country availability and bundled benefits vary.

Google says Pro includes higher Gemini limits and access to a Pro model, Deep Research, Google Flow, Gemini features in Gmail, Docs and other products, and cloud storage. These are useful when your work already sits in Google’s ecosystem. They do not mean every feature is available in every country or account.

The privacy difference needs a closer read

“Private” is not one setting. Leo has a simple consumer promise from Brave: no server-side chat retention and no additional model training from chats. Gemini provides controls, but they affect what happens next.

Google’s Gemini Apps Privacy Hub says that, when Keep Activity is on, chats and shared content are saved in Gemini Apps Activity and may be used to improve Google services, including generative AI models. You can turn that setting off. Google says future chats are then not used to train its AI models unless you submit feedback, but they are retained for 72 hours to respond, protect users, and operate the service. Some connected apps are unavailable with Keep Activity off.

Connected apps need their own check. Google says Gemini Apps can use connected Google and third-party services, and each service may process data under its own policy. Do not connect an inbox, Drive, or third-party service just because an assistant is useful; first decide whether the account’s settings and organizational policy permit that use.

When each is the better tool

Pick Leo if the core task is understanding what is open in Brave, and the privacy model and no-account option fit your needs. It is especially practical for a quick question about a webpage or local document.

Pick Gemini if your work already uses Google products and you want its AI features, research tools, or app connections. Before you use it with company data, check the exact plan, workspace policy, Keep Activity setting, and connected apps.

Neither tool is a substitute for a support process. A support team still needs a grounded knowledge source, a handoff path, an accountable owner, and a way to test a change before customers see it.

A different workflow: inspect an eesel teammate from the terminal

For a defined support job, eesel provides an AI helpdesk teammate, not a general browser assistant. The teammate is managed in the dashboard but can also be operated through the eesel CLI. It is the same workspace and same teammate in both places.

Here is a concrete use for a support operations manager checking whether an approved policy from the team's Google documents is reflected in customer replies. In this fictional example, requests within 30 days of renewal can be reviewed for eligibility, later requests go to a person, and neither outcome guarantees a refund. The teammate asks for an account email only when missing. Before any test, the manager checks enabled actions in the eesel dashboard and downstream service permissions, restricting unwanted writes or outbound contact. They can then ask Codex, Cursor, or Claude Code to inventory the intended cancellations teammate:

npx @eesel/cli status --agent cancellations
npx @eesel/cli integrations --agent cancellations
npx @eesel/cli instructions --agent cancellations

The output is JSON. The coding agent can list connected sources, check reported download readiness, and read the current cancellation instruction. Supply the approved policy text separately for comparison; a connection list does not read every document. A proposed correction might be: “Ask for an account email only if missing. Do not promise a refund. Route requests more than 30 days after renewal to a person.” The owner verifies that wording against the real policy before approving it.

That proposal is not a production change. The owner confirms the actual policy and downstream permissions, then previews any supported write with --dry-run. For a fictional test after the permission check, create a named conversation and send a test prompt:

npx @eesel/cli new --name "cancellation-policy-review" --agent cancellations
npx @eesel/cli chat "Fictional policy evaluation. Test policy: refund requests within 30 days of renewal can be reviewed for eligibility; later requests go to a person. Never promise a refund. Ask for an account email only if missing. Customer demo@example.com requests a refund 45 days after renewal. Draft only the reply and proposed handoff. Do not look up this fictional account, contact anyone, change records or configuration, or approve actions." --agent cancellations

Chat is real, billed workspace work, not a sandbox; no-action wording does not disable actual permissions. The owner checks that the reply uses the supplied email without asking again, avoids promising money, and proposes the 45-day handoff. After an approved change, start fresh conversations without supplying the policy in the prompt. Test a 10-day request with no email and a 45-day request with the email present. Inspect activity, then verify delivery and escalation with safe native-channel test cases. Observation and setup commands are free. npx @eesel/cli requires Node.js 18.17 or newer.

The benefit is not “AI automation” in the abstract. A support manager can use the coding agent they already know to inspect, document, and propose changes to the same teammate they can see in the dashboard, while keeping approval and verification with the person responsible for customers.

Verdict

Leo is a strong fit for private, browser-contextual help. Gemini is the better fit when Google AI features and connected Google services are part of the job. The right option is the one whose data settings and workflow you have actually checked.

For customer support, start with the support job itself. An eesel teammate gives that job a defined knowledge base, an owner, and a reviewable operating path instead of adding another personal AI tab. Try eesel when you are ready to test that path.