本页目录8 个章节
Editorial snapshot from September 2026. Prices, models and interface labels may change; this is a practical guide, not a live product feed.
Current international plans, included usage and the difference between a free tier and unlimited access.
These are the current international prices on trae.ai. China-region billing and existing account benefits may differ. Downloading the app is not a promise of unlimited free model access.
Monthly USD prices, checked 2026-09-21
| Plan | Subscription | Included monthly usage | Access |
|---|---|---|---|
| Free | $ 0 / month | Limited; Auto mode | Auto mode and limited usage. |
| Pro | $ 20 / month | $20 | All models; up to 10 concurrent TraeWork cloud tasks. |
| Pro+ | $ 60 / month | $60 | Up to 15 concurrent TraeWork cloud tasks. |
| Ultra | $ 200 / month | $200 | Early model access; up to 20 concurrent cloud tasks. |
Why older guides show different prices
The February 13, 2026 announcement introduced a token-based lineup with Lite, Pro, Pro+ and Ultra, ranging from $3 to $100. That announcement is historical. The current public price page lists Free, Pro, Pro+ and Ultra at the amounts above. We prioritize the current price page for new subscriptions.
What to check before paying
- Confirm that you are using the right regional product and account.
- Check included usage, model availability and any bonus expiration.
- Review whether additional usage is enabled, how it is billed and how to set a spending limit.
- For annual billing, compare the total commitment rather than a monthly-equivalent headline.
Is the free plan enough?
Use a short representative task and inspect the balance afterward. The current Free plan lists Auto-only access and limited usage. Paid access expands the allowance; it does not make every workload unlimited.
A complete first task: change, verify and review
-
Choose a small repository that already builds. Save a clean Git checkpoint and write down the command that currently passes. This gives you a baseline for distinguishing an existing problem from a generated regression.
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Describe one observable result: for example, add a required field to an existing form and show an error without submitting invalid data. Include the relevant files, existing validation helper and the behavior that must stay unchanged.
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Ask for a short plan before editing. Check that it names the affected components, data flow and verification command. Resolve missing context before allowing a broad refactor.
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Review the diff in small batches. Check dependencies, generated files, environment variables and error handling as well as the visible result. Run the project checks and exercise both the successful and failing paths.
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Inspect the usage record after the task. Record the accepted outcome, review time and usage consumed. Repeat on a second representative task before choosing a paid plan or moving a team workflow.
A task brief you can adapt
Goal: describe the user-visible change.
Context: list the relevant files and existing implementation.
Constraints: keep the public API and use the existing dependencies.
Verification: run the repository's documented checks and test the failure path.
Completion: summarize changed files, checks performed and remaining limitations.When the result is not usable
A successful request does not prove the code works. If the agent edits the wrong files, reduce the scope and supply the entry point explicitly. If a command fails, reproduce it in the same terminal environment before changing the prompt. If an MCP connection fails, separate server startup, credentials and client configuration. If usage is exhausted, check the account balance and selected model before repeating the same request. Keep a failed patch small enough to revert without losing unrelated work.
Common questions before you switch
Does a paid subscription mean unlimited agent work?
No. Subscription price, included usage, model access and additional usage are different things. A plan with unlimited autocomplete does not imply unlimited model requests or cloud tasks.
Should I connect every MCP server at once?
Start with the one integration needed by your current task. Confirm that it starts, exposes the expected tools and receives only the intended project context before adding another.
How should I compare two AI editors?
Use the same repository, task and acceptance checks. Compare correct changes, review effort, setup friction and recorded usage. A long feature list does not establish which editor produces better code for your project.
International monthly USD snapshot checked on October 3, 2026. Taxes, annual billing, regional products and additional usage may differ. Included usage is not an unlimited token allowance.
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