6 AI Browser Agents Compared: Features, Pricing & Use Cases

AI browser agents can carry out tasks on websites from instructions you describe in plain language. Instead of clicking through every page yourself, you give the agent a goal—find an invoice, compare delivery options, or check an application status—and it works through the website to reach the result.

The tools available come in a few different forms. Some are APIs that connect to an existing application, others are frameworks for building your own agent, and some are assistants that work directly in your everyday browser. These differences shape how you begin a task, how much control you have, and who is responsible for maintaining the automation.

This guide compares six AI browser agents across their capabilities, practical uses, limitations, and pricing. We also explain how browser agents work and what to check before relying on one for recurring tasks.

What is an AI browser agent?

An AI browser agent uses a language model to interpret a goal and decide which browser actions to take. It observes the page, chooses a next step, performs an action, and checks what changed before continuing.

For example, you could ask an agent to find the latest paid invoice in a supplier portal and return its number, date, and total. The agent would need to recognize the invoice area, apply the right filters, open the matching record, and read the details. Your application would still need to check that the returned invoice meets the request.

A typical agent follows this loop:

1. Read the goal: Identify the requested outcome and any constraints.
2. Inspect the page: Use a screenshot, page structure, or other browser information to understand what is available.
3. Choose and perform an action: Click, type, scroll, follow a link, or extract information.
4. Check progress: Observe the result, then continue, change approach, or stop.
5. Return an outcome: Provide the requested information, confirmation, or an explanation of why the task could not finish.

Skyvern’s concepts guide, for example, describes a loop that combines screenshots and interactive page elements with model-selected browser actions. Implementations differ, but this repeated observation and action is what lets an agent work through a path that was not fully specified in advance.

Browser agents, AI assistants, and automation scripts

These terms describe different responsibilities:

A product can include more than one of these capabilities. The important question is whether it can perform the task or only provide information and browser access to another system.

For a closer look at building your own agent, see our Browser Use alternatives guide. If you already have the agent and need hosted browsers, see our cloud browser infrastructure comparison.

What can you use browser agents for?

Browser agents are worth evaluating when a task requires interpreting pages and taking actions across a website. Common task patterns include:

• Retrieving records from portals: Find an invoice, check a claim status, or collect an order reference from an account page.
• Completing forms: Enter supplied information, choose relevant options, and prepare a submission for review.
• Comparing information: Open several listings or product pages and return options that meet stated criteria.
• Checking business workflows: Inspect whether a registration, support request, or account update reached the expected state.

The goal should include a concrete completion check. “Find my invoice” leaves room for ambiguity. “Return the latest paid invoice for account 4821, including its number, date, total, and source URL” makes the expected result clearer.

An agent is not necessary for every web task. If a supported API returns the data directly, or a short script reliably follows a known route, that may be the simpler implementation. Agent-driven interaction is more useful when the next step depends on reading and interpreting the page.

AI browser agents at a glance

6 AI browser agents compared

Each section covers what the tool does, its key capabilities, trade-offs, pricing, and best fit. Start with the way you intend to use the agent: inside an application, as a reusable business workflow, or directly in your browser.

1. TinyAgent for browser tasks inside an application

TinyAgent, the TinyFish web agent, takes a website URL and a goal, performs the browser work, and returns a result. It is designed for applications that need to delegate a web task without implementing the agent’s decision loop themselves.

For a supplier-status check, your application could provide the portal URL, an order number, and the fields it needs back. TinyAgent would handle navigating the site, while your application decides how to validate and use the returned information.

Key capabilities

• The Agent API supports synchronous, asynchronous, streamed, and batch execution. An output schema can define the shape of the returned JSON.
• Browser Context Profiles preserve signed-in state. When paired with a matching Vault credential, they can support signing in again after a session expires.

Trade-offs

Your team still defines the task boundaries and verifies the result. Structured output makes information easier to consume; it does not establish that the agent selected the correct record. If session recordings are required for review, confirm account access: the API restricts that capture option to enabled custom or enterprise accounts.

Pricing

• TinyAgent costs $0.016 per step, including model inference. Standard accounts allow two concurrent runs. Usage draws from a prepaid Wallet with no recurring subscription or monthly minimum; higher concurrency is available through sales.

Best fit: Developers who want to call a managed browser agent from their application and receive structured results.

2. Browser Use for building your own agent

Browser Use is an open-source Python framework for browser agents. You supply a task and configure the agent within your application, with control over its model and custom tools.

That matters when browser work is part of a larger application process. A custom tool could let the agent consult an internal service while working through a website, rather than forcing the entire task into browser interactions.

Key capabilities

• The Python library supports model selection, custom tools, and structured output, allowing developers to adapt the agent to their application.
• The project distinguishes the open-source library, a CLI for giving existing agents browser access, and a fully hosted service that runs the agent and browser.

Trade-offs

The framework gives you implementation responsibility as well as flexibility. For a self-managed deployment, plan authentication, execution limits, failure handling, and result validation. Choosing a hosted browser alone does not transfer responsibility for the agent loop you run in your own application.

Pricing

• The Python library is free and MIT-licensed. Model inference and hosted infrastructure are separate costs; Browser Use’s cloud services charge for usage. A local setup also carries hardware and maintenance requirements.

Best fit: Python developers who need to inspect, extend, and own the agent’s behavior.

3. Skyvern for repeatable business workflows

Skyvern combines browser agents with reusable workflows. You can define the surrounding process while letting an agent interpret and act on pages within individual tasks.

For invoice collection, a workflow could separate login, document discovery, and processing each returned invoice. That makes the business process explicit instead of asking one open-ended prompt to handle every step.

Key capabilities

• Workflows combine browser tasks with blocks for loops, conditions, file handling, and calls to other systems. They accept reusable inputs and can run from the app or code.
• Runs expose outputs and a history of browser actions. Skyvern offers managed execution and an open-source self-hosting path.

Trade-offs

Reusable workflows still require design and maintenance. Your team needs to decide where the agent can interpret the page and where the process should follow fixed rules. Check plan requirements for authentication and intervention features before building around them.

Pricing

• Hobby costs $29 per month, with 30,000 monthly credits and 10 concurrent runs. Pro costs $149 per month, with 150,000 credits and 25 concurrent runs.
• Self-serve plans start with a 14-day trial. Credits are a usage allowance, not a fixed number of completed workflows; self-hosting has separate model and operating costs.

Best fit: Teams that need a repeatable process around browser tasks, particularly portal and form-based operations.

4. Browserbase Agents for reusable hosted agents

Browserbase Agents lets you create a hosted agent by describing its goal and configuring the expected output. You can test it in the dashboard, then trigger runs through the API or SDK.

Its official quickstart builds a job-finding agent that searches a company’s official listings and returns a matching role. The example illustrates an important pattern: keep the agent configuration reusable while changing the inputs for each run.

Key capabilities

• Saved agent instructions and a JSON Schema define the task and expected result format.
• The run view shows actions, reasoning, a timeline, and the live browser. An optimization tool can suggest instruction changes based on previous runs.

Trade-offs

Reusable instructions need testing across different inputs. A valid schema does not prevent the agent from returning an incorrect match, so check outputs against their sources. Treat optimization suggestions as changes to evaluate rather than proof of improved performance.

Pricing

• The free plan includes three Agent runs. Developer costs $20 per month and includes 15; Startup costs $99 per month and includes 50.
• These are platform plans with multiple usage components. Check the applicable Agent run and overage terms before estimating a recurring workload; the subscription is not an unlimited agent allowance.

Best fit: Teams that want reusable, API-triggered browser agents with hosted execution and dashboard-based inspection.

5. Comet Assistant for tasks in your everyday browser

Comet is Perplexity’s browser, with an assistant that can help read pages and perform browser tasks. It suits users who want to delegate work while staying close to the tabs and accounts they already use.

The distinction from a developer framework is the starting point: you ask for help inside the browser rather than build an application around an agent API.

Key capabilities

• Comet Assistant can work across tabs and interact with websites. Perplexity demonstrates tasks such as finding jobs and comparing travel options.
• The assistant asks permission before interacting with the browser, letting you decide whether it should carry out the task there.

Trade-offs

A browser assistant’s workflow is centered on the user and their browsing context. Evaluate it for the work you intend to supervise directly. If you need application-triggered jobs, a defined output contract, or recurring processing across many accounts, assess those requirements separately.

Pricing

• Perplexity Pro costs $20 per month or $200 per year. Comet Assistant’s browser-agent usage depends on the subscription’s allowances; check the plan comparison rather than assuming free search access includes agent tasks.

Best fit: Individuals who want assistance with multi-tab research and browser tasks without building an integration.

6. Manus Browser Operator for an existing signed-in browser

Manus Browser Operator connects Manus to a local browser through an extension. It lets the agent work in an environment you authorize, including websites where you already have an active session.

That is useful when the browser itself contains part of the setup: a paid account, required extensions, or access through your organization’s network. You can delegate the task without first recreating that environment in a separate cloud browser.

Key capabilities

• Browser Operator requests authorization and opens a dedicated task tab. You can observe the work, intervene, or stop it.
• Manus also offers a preferred-browser setting, allowing supported accounts to use a chosen authorized Chrome environment when starting work from another computer.

Trade-offs

Local-browser work depends on the device and its access state. The preferred browser needs to remain open and online, and availability varies by account and rollout. An existing login can help the agent start, but it does not guarantee that every interaction will succeed or that the session will never expire.

Pricing

• Manus offers a free plan with 300 daily refresh credits and one concurrent task. Pro starts at $20 per month with 4,000 monthly credits.
• These are Manus membership allowances, not a fixed price per browser task. Check the credits consumed by your intended work and the current features available to your account.

Best fit: Users who want an agent to work in an authorized browser with existing sign-ins and local access.

How to choose an AI browser agent

Start with how the task enters your workflow. If an application needs to trigger it and consume the result, look for an API and a clear output contract. If a person will delegate and supervise the task, a browser assistant may be more convenient. For a repeatable business process, examine how inputs, branching, and exceptions are represented.

Then test one task with a defined outcome. For an invoice-status check, require the account, invoice number, status, and source link. Include a case where the invoice does not exist, so a valid “not found” result can be distinguished from a failed search.

Evaluate three things:

• Completion: Did it return the correct result, and how often did someone need to intervene?
• Recovery: What happened when login expired, the page changed, or the task could not be completed? Could you understand the failure afterward?
• Cost: What did the full set of attempts consume, including retries, model calls, credits, and review time?

For tasks that modify accounts or submit information, define where the agent must pause for review. Limit its access to what the task requires, and keep credentials and approval rules outside the prompt alone. Webpage content should be treated as task data, not authority to expand what the agent may do.

Start with a task you can verify

Browser agents are useful when a website task requires interpretation as well as interaction. The right tool depends on where that work belongs: inside your application, within a repeatable process, or in a browser you supervise.

Begin with one complete task and a clear definition of success. Check the result, inspect an unsuccessful attempt, and measure the effort needed to keep the workflow running. That gives you a practical basis for expanding the automation—and a way to recognize when a simpler approach would serve you better.

Try a browser task with TinyAgent

Give TinyAgent a website, a goal, and the result you expect. Start with a task your team already understands, then inspect the outcome before connecting it to a wider workflow.

Try TinyAgent in the Playground →

Keep reading:

• Browser Use alternatives: Agent frameworks and platforms
• Browserbase alternatives: Cloud browser infrastructure