Brave Leo AI Browsing
Also known as: Brave Leo, Leo AI, Brave AI Browsing
Brave's privacy first assistant Leo offers opt in AI browsing, an agent that drives the browser in an isolated profile, with a second model checking each action and asking permission for risky ones. Leo supports local or remote bring your own model and on device memories, and AI browsing is in early testing.
Brave Leo is the AI assistant built into the Brave browser on desktop and mobile. It summarizes and answers questions about webpages, PDFs, Google Docs and Sheets, grounds answers in Brave Search, and lets users pick models from Mixtral, Anthropic's Claude and Meta's Llama or bring their own local or remote model. Memories keep facts and preferences the user enters on the device, Skills turn favorite prompts into shortcuts, and chats are not retained or used for training, with no account needed for the free tier.
AI browsing, Leo's agentic mode, is in early testing across all release channels behind an opt in flag and must be invoked manually. The agent works in an isolated browser profile with no access to the user's regular logins, in an open tab the user can inspect and pause. A second alignment checker model compares each action with the user's intent, and actions it flags require the user's explicit permission. Brave pays double bug bounties for agentic findings during early testing and has published research on prompt injection across the agentic browser category.
Vendor details
Canonical URL
https://brave.com/leo/
Category
Browser / computer-use agent
Funding status
Leo is a product of Brave Software, Inc. It launched in 2023, and AI browsing entered early testing across all release channels on 5 May 2026.
Company status
first party product
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
Leo is built into the Brave browser with page awareness across webpages, PDFs, Google Docs, Google Sheets and YouTube, and is grounded by Brave Search. Bring Your Own Model connects local or remote models, including OpenAI compatible endpoints. There are no connectors or developer API for the agent.
In practice
A shopper wants the best price on a pair of headphones across several stores. With AI browsing turned on, Leo visits the sites in an open tab, compares the products and checks promo codes, in a profile kept apart from the shopper's own logins.
A researcher wants a quick read of a long PDF and two Google Docs. Leo summarizes and analyzes the documents in view, pulling in Brave Search results where they help, without retaining the chat.
A developer runs a model on their own machine. Bring Your Own Model points Leo at that local model, so prompts never leave hardware the developer controls.
Sources & related URLs
Research sources
Agentic Index coverage score
6.0 / 14 capabilities · 43%
| Integrations & Tool Calling | Not documented |
|---|---|
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AI browsing runs in an isolated profile where cookies, logged in state and caches from regular browsing do not carry over, so it acts on websites as a browser rather than through the user's accounts. Leo reads PDFs, Google Docs and Sheets as page context. Brave names no connector, tool calling route or authenticated action framework. SourceBrave, brave.com/blog/ai-browsing and brave.com/leoread 2026-10-06 |
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| Workflow Orchestration | Partial |
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AI browsing carries out one multi step task per session, such as researching across several sites, comparing products or checking promo codes, in an open tab. Brave names no multi agent or composed workflow. The feature sits behind an opt in flag in early testing. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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| Knowledge Grounding & RAG | Partial |
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Leo grounds answers in Brave Search results and in the page, PDF, Google Doc or Sheet in view, assembled per query, and can summarize, translate and analyze that content. Brave names no maintained index over the user's own knowledge. SourceBrave, brave.com/leoread 2026-10-06 |
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| Human Oversight & Guardrails | Full |
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A second model checks each action against the user's intent, and actions it flags as misaligned trigger a warning and require the user's explicit permission before they run. Users can inspect and pause sessions, and browsing happens in an open tab. The alignment checker sees the system prompt, the user's prompt and the task model's response, and permission requests are kept for specific actions it judges risky rather than asked site by site. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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| Security, Identity & Governance | Not documented |
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Protections include the isolated agent profile, no retention of chats and no training on them, no collection of identifiers such as IP addresses, and doubled bug bounty rewards for agentic findings. Brave names no access model or attestation for Leo, and no roles or SSO for who can run the agent. SourceBrave, brave.com/blog/ai-browsing and brave.com/leoread 2026-10-06 |
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| Observability & Auditability | Partial |
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Users can inspect AI browsing sessions, the agent cannot delete its own session logs, and all agent browsing happens in a visible open tab rather than a sidebar, which shows what happened. Brave names no audit trail or trace of why the agent acted. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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| Memory & State Persistence | Partial |
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Leo Memories are facts and preferences the user enters, stored on the device, editable and deletable at any time, which Leo consults across chats, and chat history can also be saved locally and continued. The user maintains the memories, and Brave states no lifetime for them. Sourcebrave.com/whats-new/leo-memoriesread 2026-09-27 |
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| Deployment & Data Residency | Partial |
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Bring Your Own Model runs Leo on the user's own local or remote models, keeping inference on hardware the user controls, and the browser itself is a client on macOS, Windows, Linux, Android and iOS. Brave's own service offers no region or residency choice, and the free version needs no account. SourceBrave, brave.com/leoread 2026-10-06 |
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| Prebuilt Agents, Templates & Packs | Partial |
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Leo ships a handful of pre configured Skills, prompt shortcuts such as explaining a topic simply, beside Skills users write themselves. Skills are prompt templates, and Brave names no prebuilt agents. Sourcebrave.com/blog/leo-skillsread 2026-09-27 |
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| Triggers & Channel Coverage | Not documented |
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AI browsing has to be manually invoked by the user, a design choice Brave states, and it stays off until the user turns it on. Brave names no schedule, event or background trigger. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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| Model Flexibility & Routing | Full |
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The user chooses among models from Mixtral, Anthropic's Claude and Meta's Llama, with more on Premium, and Bring Your Own Model connects local or remote models, including third party APIs. Premium also raises usage limits, while free access can vary with traffic. SourceBrave, brave.com/leoread 2026-10-06 |
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| APIs, SDKs & MCP Extensibility | Not documented |
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Bring Your Own Model points Leo at other models. It does not let other software call Leo, and the Brave Search API is a separate product. Brave names no API, SDK or MCP server that drives Leo or AI browsing. SourceBrave, brave.com/leoread 2026-10-06 |
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| Testing, Debugging & Optimization | Not documented |
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For the agent, Brave names no evaluation harness, test cases or quality gate. Brave has published its own prompt injection research on agentic browsing. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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| Browser & Computer Use | Full |
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AI browsing drives the Brave browser itself in an isolated profile and open tab, visiting and analyzing sites, comparing products, checking promo codes, summarizing news and completing tasks. It is opt in, off by default and in early testing across all release channels. SourceBrave, brave.com/blog/ai-browsingread 2026-10-06 |
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The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Product updates
Leo conversations with the open weight GLM model are now end to end encrypted. The browser encrypts each prompt on the device so that only a trusted execution environment that has passed hardware attestation can read it, and Brave says the setup keeps prompts and responses from infrastructure operators, including Brave itself. It is available in Brave's Release, Beta and Nightly channels.
Bears on: Deployment / data residency
View sourcePricing
Free in the Brave browser, no account; Leo Premium $14.99 a month or $149.99 a year
freemium subscription
What is public
The freemium structure is public: Leo ships free in the Brave browser with open models and no account, and Leo Premium, at $14.99 a month or $149.99 a year, adds frontier models.
Variable cost rationale
Free base tier and flat Premium subscription; BYOM local models remove even model costs for self hosted users, the lowest cost exposure in the consumer agent tier.
Sales call required
No, self serve available
Free / trial
Free Leo with no account; Leo Premium offers a free trial
Lowest paid plan
Leo Premium, $14.99 a month or $149.99 a year
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Alternatives to Brave Leo AI Browsing
The closest documented capability profiles to Brave Leo AI Browsing among browser and computer-use agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Opera Neon7.5 / 14Adds documented Integrations & Tool Calling and Triggers & Channel Coverage, among othersBrave Leo AI Browsing vs Opera Neon →
- Sigma Browser3.5 / 14A lighter documented profile than Brave Leo AI Browsing
- AGI, Inc.6.0 / 14Adds documented Triggers & Channel Coverage and APIs, SDKs & MCP Extensibility
- Island9.0 / 14Adds documented Integrations & Tool Calling and Security, Identity & Governance, among others
- Stagehand7.0 / 14Adds documented Integrations & Tool Calling and APIs, SDKs & MCP Extensibility, among others
- Microsoft Scout10.5 / 14Adds documented Integrations & Tool Calling and Security, Identity & Governance, among others
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded