Manus AI Pricing: What Credits Cost | Coworker AI

Why Manus AI pricing looks simple and isn't

Manus AI pricing, on the surface, is four numbers: $0, $20, $40, and $200 a month, listed on Manus's pricing page with a note that annual billing saves 17%. That's the easy part. The hard part is that none of those numbers tell a buyer what they'll actually get, because Manus doesn't charge per seat or per task. It charges per credit, and credit consumption depends on "the complexity and resources required for each task," according to Manus's own documentation. A quick chat question and a full research-and-slide-deck run can cost 50x different amounts of the same currency.

This is the same structural problem that shows up across the credit-metered AI agent category, and it's exactly why Manus AI pricing generates more confused Reddit posts than almost any other pricing page in the space. The tiers are published. The actual cost of using the product is not, until after you've run the task and watched the balance drop.

What Manus AI actually charges

Here's the current tier structure, pulled directly from the live pricing page and cross-checked against the plans documentation:

The Free plan's concurrency figure comes from Manus's Help Center article on current membership pricing, read on 18 September 2026, which describes the Free plan as one concurrent task and two scheduled tasks. Several third-party trackers list a higher number; the vendor's own page is the one to trust. The same article lists the paid tiers' 20 concurrent and 20 scheduled tasks, which matches the live pricing page.

Team pricing is now published rather than sales-gated: the same Help Center article puts the Team plan at "starting from $20 per seat/month" with the same 17% annual discount, and Manus's Team page confirms that each billed seat adds credits to one shared pool the whole team draws from, with add-on credits and an auto-purchase option available to team owners and super admins. Enterprise still routes to a sales conversation.

One detail that trips people up before they even get to credit math: Manus's own docs page and its live pricing page use different names for the same tiers. The docs describe "Free, Pro, and Team" plans, while the pricing page in front of a buyer today shows "Free, Standard, Customizable, and Extended." Both describe the same $20/$40/$200 structure, but a buyer cross-referencing the two pages for clarity will find them talking past each other, which is a small thing but a real one when the pricing itself already needs explaining.

How Manus AI pricing changed since launch, and why that matters now

Manus has restructured its plans at least once, and the direction of travel is genuinely good news for buyers. It also explains most of the contradictory numbers circulating online.

When Manus launched paid plans on 31 March 2025, TechCrunch reported two tiers: $39 per month for 3,900 credits and the ability to run two tasks simultaneously, and $199 per month for 19,900 credits, five simultaneous tasks and priority access during peak hours. Manus was still invite-gated at the time and said in the same announcement that it had "temporarily limit[ed] access" while it scaled infrastructure.

Hold that against today's published tiers and two things changed.

Credits per dollar doubled. At launch, $39 bought 3,900 credits, which is 100 credits per dollar. Today $20 buys 4,000 credits, $40 buys 8,000 and $200 buys 40,000, which is exactly 200 credits per dollar on every tier. The entry price roughly halved while the credit allowance went up slightly.

Concurrency went up 10x on paid plans. Two simultaneous tasks at launch, 20 today, plus 20 scheduled tasks. For anyone running the agent as a background worker rather than a chat window, that is the larger change.

There's also no volume discount, and that is worth naming because buyers instinctively expect one. The ladder is perfectly linear at 200 credits per dollar. Moving from the $20 tier to the $200 tier buys you ten times more, not ten times cheaper. The only reason to move up is to avoid running out mid-month, never to reduce your unit cost.

Two more things a buyer should weigh before signing an annual term. First, the tier names have already changed once, so any budget document referencing "Standard" or "Extended" may not survive the next pricing page. Second, the live pricing page on 18 September 2026 carries a banner reading "Manus has resumed independent operations. Our next chapter starts now." We are not going to speculate about what sits behind that sentence, but a company in the middle of a corporate transition is a different annual-commitment risk than one that isn't, and the 17% annual discount is the price of taking that risk.

The credit math nobody runs until they've already paid

The number that actually determines cost is the credit price per task, and Manus doesn't put this on the pricing page. Based on a per-task credit breakdown independently compiled and cross-checked against Manus's documented complexity tiers:

• Simple queries and chat: 10-50 credits
• Web research tasks: 100-300 credits
• Deep research with multiple sources: 500-900 credits
• Code generation and execution: 200-500 credits
• Web app building: 500-1,000+ credits
• Wide Research (multi-source deep analysis): 800-1,500+ credits

Run that against the Standard plan's 4,000 monthly credits and the math is unforgiving: at 500-900 credits per serious research task, a $20/month subscriber gets roughly 4 to 8 complex tasks before the monthly pool is empty, before touching the 300-credit daily refresh at all. Lindy.ai's own breakdown runs the identical calculation and lands on the same range, which is a useful cross-check given the two sources compiled the numbers independently.

That daily refresh sounds like it should soften the math, and on paper it does: 300 credits a day, if used every single day, adds up to roughly 9,000 credits a month. In practice it doesn't roll over between days and doesn't accumulate if a day is skipped, so it functions more like a small daily allowance than a meaningful monthly buffer for anyone who doesn't log in and burn it every day without exception.

For free users there is a second, harder ceiling that almost nobody mentions. Manus's Help Center article on credit consumption rules states that "the monthly consumption limit for daily refresh credits for free users is set to 1,500 credits; paid users have no limit," and that daily credits can only be spent on the lightest model in the family. So the widely repeated "300 a day means 9,000 a month" arithmetic is simply wrong for anyone on the free plan, who is capped at 1,500, and those credits cannot be pointed at the model you would want for serious work.

What Manus says its own tasks cost

The most useful pricing document Manus publishes is not on the pricing page. Manus's credits help page lists three worked examples with the credits each one consumed, and these are the vendor's own numbers rather than anyone's estimate:

The dollar column is our arithmetic on Manus's published tier prices, not a figure Manus quotes. Since every tier prices credits at exactly 200 per dollar, the conversion is the same whichever plan you are on.

Two things about that table are more useful than the numbers themselves.

Duration is the visible proxy for cost. A 15-minute task cost 200 credits, an 80-minute task cost 900. That's roughly 12 to 13 credits per minute across all three examples, which is a far more stable ratio than the 100x spread between task types suggests. If you are trying to build a mental model, "how long will the agent be working" predicts the bill better than "how hard does this feel."

Manus's own examples sit at the cheap end of the third-party ranges. The 900-credit complex app build lands at the bottom of the 500-1,000+ range compiled for web app building, and the vendor chose these examples. That is not dishonest, it is what any vendor would do, but it means the numbers above should be read as a floor rather than an average.

The same page explains what the credits actually pay for, which is the closest thing to a mechanism Manus publishes: LLM tokens for planning, decision making and output generation; virtual machines for file operations, browser automation and code execution; and third-party APIs for integrated external services such as financial data and professional databases. It also confirms one genuinely reassuring thing: "credits are only consumed during active task processing," so storing or deploying the output of a finished task costs nothing, and there's no reason to delete old tasks to save money.

What a month of Manus AI costs at three usage levels

Manus doesn't publish a typical monthly bill, so the scenarios below are built from the vendor's own three worked examples above. The assumptions are stated inline. These are illustrations, not survey data and not measurements of any real account.

Three observations that survive changing the assumptions.

The $20 tier is narrower than it looks. 4,000 credits is four complex tasks and change. The regular solo profile above, which is not a heavy user by any reasonable definition, overruns it by 30%. The jump from $20 to $40 is the one most paying users end up making, and it is worth modelling before you commit annually to the cheaper one.

Underusing a tier is the expensive mistake. Monthly credits reset and do not roll over. A month where you use 12,000 of your 40,000 credits is not a cheap month, it is $200 spent on 12,000 credits, which is a worse rate than buying add-on credits at the same 200-per-dollar price without the commitment. Because the ladder is linear, there is no volume argument to offset that.

Add-on credits change the shape of the decision. Per the credits help page, "free credits and add-on credits never expire," while monthly plan credits refresh on your subscription date and are gone. That makes a lower tier plus occasional add-ons strictly safer than a higher tier you might not fill, which is the reverse of how most subscription products work.

Why Reddit calls it "unreasonably expensive"

The specific complaint driving Manus AI's reputation problem on Reddit isn't the sticker price. It's the mismatch between the sticker price and what a credit actually buys. The r/ManusOfficial thread titled "The current Manus credit system is unreasonably expensive" laid it out under the pricing structure in place at the time (a $39 tier with 3,900 credits): "Manus gives you only 3,900 credits, which barely supports 3 to 4 properly executed tasks, while charging significantly more" than comparable LLM subscriptions. The poster's math: a single task with real back-and-forth easily costs over 900 credits, which is squarely in the deep-research range confirmed above.

A Manus team member responded directly in that thread, acknowledging the core issue rather than disputing it: "regarding the lack of a clear credit consumption prediction before starting a task, we understand how this can feel uncertain for users. While implementing a predictive model for credit usage is technically challenging, please rest assured that we recognize the need." That's Manus itself confirming, in writing, that there's no way to know a task's cost before running it. Pricing tiers have since changed (the $39/3,900-credit tier is gone, replaced by the current $20/4,000-credit Standard plan), but the complaint that drove that thread, no visibility into cost before you commit to a task, has not been addressed by the newer tiers.

The complaint has kept recurring under the current pricing too. A follow-up post in the same subreddit, "Manus AI is way too overpriced for what it actually gives you," pulled 83 upvotes and 63 comments, and a more recent thread titled "2591 credits consumed in 15 seconds" shows the same underlying issue is still live months later: credit consumption that doesn't map to any visible unit of work before it happens.

Manus's own documentation contradicts itself on whether you can preview a cost

This is worth separating out, because it is the single question every buyer asks and the vendor answers it two different ways on two live pages.

Manus's plans documentation says, in its FAQ, that "the dashboard provides estimates before you start a task." Read on its own, that closes the whole issue.

Manus's Help Center article on exactly this question, dated 18 December 2025, says the opposite: "At present, Manus does not possess the capability to autonomously judge or regulate the consumption of credits." The same article goes on to acknowledge "the aspiration for pre-task estimations of credit expenditure" and says the product team "is diligently working toward a solution" with features anticipated "in the near future."

Both pages are live today. We trust the Help Center article, because it is dated, specific, and written to answer this exact question, while the docs line is a single unsourced sentence in a general FAQ. It also matches what the Manus team member said in the Reddit thread above and what every user account describes. If you are evaluating Manus, assume you cannot see a task's price before you run it, and verify in the product before you build a process that depends on being able to.

That single fact is the root of most of the frustration in this category. It is not that the tasks are expensive. It is that the price is unknowable at the moment you decide to spend it.

The failure mode that makes it worse: paying for tasks that don't finish

The complaint that shows up most in reviews isn't just that credits burn fast. It's that they burn on failure. A separate Reddit post, "A Warning to All Redditors: Manus AI's Credit System Drained My Bank Account", describes exactly this: credit deductions the poster called "glitchy" and "poorly explained" that continued regardless of whether the task actually succeeded.

Lindy's review cites that same thread and states the mechanism plainly: "the credit system charges you even when it fails. Credits are deducted whether the task completes successfully or not." Users reported burning through thousands of credits in minutes on outputs that were incomplete or full of errors. That's the actual mechanism behind "unreasonably expensive," and it's a materially different problem from a task simply costing more than expected. A predictable expensive task is a budgeting problem. An expensive task that produces nothing and still gets billed is a trust problem, and it's the one that shows up most often in the reviews and threads that rank for this exact keyword.

What Manus's refund policy actually covers

The section above is one user's account of their own invoice. This section is the published policy, which is the part you can actually check before you buy, and it is more specific than either the complaints or the reassurances suggest.

Manus's credit refund policy article, dated 16 December 2025, says Manus issues a full credit refund when an investigation confirms "a verifiable bug or platform malfunction." It names three qualifying cases: a platform error such as an internal server error, tool malfunction or system crash; tool misuse, where the agent uses a tool in a way that directly violates its documented instructions; and incomplete execution, where the agent stops mid-task without a valid reason and delivers no results.

The same article lists five situations where refunds are not issued, and this list is the one to read twice:

• Change of mind. Credits are consumed as the agent works and that work cannot be undone.
• Unclear instructions. If your prompt was ambiguous and the agent made a reasonable interpretation you didn't want, that is billable.
• Subjective dissatisfaction. The task completed as requested but you don't like the writing, the design or the analytical approach. Billable.
• External factors. The task failed because a third-party website was down or an external API returned an error. Billable, and not Manus's fault, but your credits are gone either way.
• Hitting task limits. The task stopped because it reached a safety or resource limit. Billable, and described as standard operating procedure.

Refund requests are reviewed by "a specialized AI agent" trained to analyse task execution logs, alongside a Customer Success team.

Put the two sections together and the honest conclusion is narrower than either side of the argument. It is not true that Manus never refunds failed work; a crash or a stalled run with no output qualifies. It is also not true that you are protected from paying for useless output. A task that runs to completion and produces something you can't use is explicitly outside the policy, and so is a task derailed by someone else's website going down. That is the structural fact. The Reddit accounts of thousands of credits vanishing are individual experiences consistent with it, but they are not themselves evidence of how the system works.

Five things about Manus credits that surprise people

Each of these comes from Manus's own documentation, and each one changes how you should plan a month.

1. Credits are spent in a fixed order, and it isn't the order you'd choose. The credits help page says consumption runs: event credits, then daily credits, then monthly credits, then add-on credits, then free credits. The credits with an expiry go first, which is the right design, but it means the never-expiring add-on credits you bought for emergencies sit untouched while your monthly pool drains.

2. Your balance can go negative, and that's expected. The Help Center explains that Manus calculates and deducts each action's cost at the start of the following action, so a task can complete an action that slightly exceeds your remaining balance. The article says a temporarily negative balance "is expected behavior and does not indicate an error," and applies to Free, Pro and Team plans alike.

3. Daily refresh credits are model-limited. Per the same article, daily credits can only be used with the lightest model in the family. They are not a free allowance for the work you actually bought Manus to do.

4. Redirecting a task mid-run doesn't refund the abandoned path. Credits are consumed as the agent works. Changing your mind about the direction halfway through means you've paid for both directions.

5. Third-party data access bills through to your credits. Financial data and professional database calls made during a task draw on the same balance. A research task that hits paid data sources costs more than an identical-looking one that doesn't, and you won't know which is which in advance.

How to spend fewer Manus credits

Manus publishes real guidance on this, and it is more specific than the usual "write better prompts" advice. These are the vendor's own recommendations plus the structural levers that follow from the mechanics above.

Break long conversations into focused sub-tasks. Manus's Help Center puts this first: "The greater the contextual load Manus is required to process, the higher the corresponding execution cost." One long thread costs more than the same work split across several tight tasks, for the same reason it does on every agent product that charges by consumption.

Front-load the detail. The same article recommends articulating requirements precisely at the outset, because it reduces the overall context length rather than growing it through clarification rounds. The refund policy article repeats this as its one cost tip, which tells you Manus sees vague prompting as the most common source of wasted credits.

Group related questions into one task. Manus's optimisation guide gives the worked example: instead of asking separately about formatting and saving a file, combine them into a single request.

Don't rephrase a failed request, refine it. The same guide singles out repeated attempts as a specific waste: read the response you got, correct the input, and resubmit once. Asking the same thing five different ways bills five times.

Use Chat mode for anything that isn't agent work. The plans doc is explicit that simple questions don't require the full autonomous agent. The 10-50 credit range for chat versus 500-900 for deep research is the largest single saving available on this product.

Review intermediate output on multi-phase tasks. Also from the plans doc: checking partial results before the agent proceeds prevents spending credits on work built on a wrong turn.

Buy add-on credits instead of upgrading a tier you won't fill. Add-on credits never expire; monthly credits reset. If your usage is uneven, the lower tier plus top-ups costs the same per credit and carries none of the reset risk.

Watch the dashboard rather than the invoice. Manus's docs describe a usage history, spending insights showing which task types consume the most, and low-balance alerts. Since there's no pre-task estimate, post-task history is the only calibration available, and it's worth building the habit in the first week rather than the first overage.

How the competitor breakdowns compare, and where they don't quite agree

Both nocode.mba's pricing breakdown and Lindy's cover the same $20/$40/$200 structure and land on similar per-task credit ranges, which is a reasonable sign the numbers are solid. Where they diverge is tier naming and free-tier specifics: nocode.mba describes the free plan as 300 daily credits with no starting balance, while Lindy's pricing page describes 1,000 starter credits plus the 300-credit daily refresh. Both can't be precisely right at once, and it's the kind of small inconsistency that's easy to inherit if a buyer reads one source and assumes it's complete. The tier structure and per-task cost ranges above are cross-checked against Manus's own live pricing page and documentation, which is the version worth trusting when the secondary sources disagree with each other.

Manus AI pricing vs other autonomous agent products

The products a Manus buyer actually shortlists price the same job in four different units. Everything below was read from each vendor's own live pricing page or help centre on 18 September 2026.

What the table is good for, and what it isn't.

It's good for seeing that "credits" is not a shared currency. Lindy's pricing docs publish a top-up rate of $10 per 1,000 credits, which is $0.01 per credit. Manus prices credits at 200 per dollar, which is $0.005 per credit. Manus credits look twice as cheap and that comparison is meaningless, because a Lindy credit and a Manus credit measure different amounts of different work. Anyone putting these two numbers side by side in a spreadsheet is producing a wrong answer confidently.

It's good for seeing which failure mode you're buying. Lindy's pricing page states that when the pool runs low, Lindy pauses credit-using actions and tells you, explicitly promising no surprise bill. Manus lets the balance go temporarily negative and then blocks new tasks. Devin sells extra usage at API pricing once quotas are exhausted. Those are three genuinely different answers to "what happens when I run out," and it's a more decision-relevant question than the headline price.

It isn't good for a total. None of these vendors can tell you what your month will cost, because none of them knows what you'll ask for. Our comparison of enterprise AI pricing models and the breakdown of what enterprise AI should cost per user are the better places to start if you're building a budget across several of these at once, and Lindy's own pricing in detail covers the closest credit-metered comparison.

Who Manus AI is wrong for

Saying this plainly is more useful than another feature list, and every item below follows from a fact established above rather than from an opinion about quality.

Anyone who must commit a number to finance before the work happens. The vendor states in its own Help Center that it cannot judge or regulate credit consumption and that pre-task estimates are still on the roadmap. There is no version of this product today that produces a forecast. A monthly cap exists in the sense that you run out, but "we stopped working on the 19th" is not a budget.

High-volume daily operational workloads. The ladder is linear at 200 credits per dollar with no volume discount, so scale never improves your unit economics. A workflow that runs the agent dozens of times a day will cost exactly proportionally more forever, and at that shape a flat-rate or per-seat product usually wins on total cost.

Teams expecting the free tier to do real work. It is capped at 1,500 credits of daily refresh per month, restricted to the lightest model, and limited to one concurrent task. It is a genuinely useful way to see whether autonomous agent workflows suit you, and it is not a way to get work done for nothing.

Workflows that depend on flaky third-party sources. The refund policy explicitly excludes failures caused by external websites and APIs. If your research tasks routinely hit sites that rate-limit or go down, you are paying for their reliability problems out of your credit balance.

Anyone whose primary need is governed access to internal company systems. Manus is an autonomous task runner. Connecting an agent safely to a CRM, a ticketing system or a shared drive, with permissions and an audit trail, is a different problem with a different shape, covered in the next section.

Who it is genuinely right for: individuals and small teams running bounded, high-value tasks where a $1 to $5 credit cost per task is obviously worth it, and anyone testing whether autonomous agent workflows fit a use case at all. For that buyer, the reviews are largely positive and the $20 tier is reasonable. The risk is entirely in what happens when occasional use becomes daily use.

Is Manus AI worth the price

For a single user running occasional research or content tasks, the Standard plan's $20/month is competitive with comparable tools, and the free tier is genuinely useful for testing whether autonomous-agent workflows fit a use case before paying anything. The actual risk sits with regular or team use: once a workflow depends on Manus daily, the credit ceiling becomes the real constraint, not the advertised price, and the lack of a pre-task cost estimate means that ceiling can arrive without warning. For a broader view of how this compares against other AI tools priced by seat rather than by credit, see how AI pricing models stack up across the category, and our roundup of the best AI agents for where Manus sits against the rest of the field on capability rather than cost.

Where Coworker MCP fits, and where it doesn't

None of this is really a question about whether Manus AI's agent is good at research or code generation; the reviews suggest it often is. It's a question about whether an unpredictable, task-metered credit system is the right foundation for giving an autonomous agent regular access to company systems, on top of the research work it already does.

That's a different problem than what Manus solves, and it's the one Coworker MCP is built for. Coworker MCP doesn't compete with Manus AI as an agent; it sits underneath agents like Manus, giving them governed, audited access to a company's actual tools and data through 50+ connectors, so a task Manus runs can safely touch a CRM record, a support ticket, or a shared drive without that access being cobbled together per integration. A team running Manus for research or content generation and separately trying to wire it into internal systems is solving two different problems with two different failure modes: one is "did this task cost too many credits," the other is "should this agent have been allowed to touch that record at all." See how to choose the right approach for connecting an agent platform to internal systems, what MCP actually is if the protocol itself is new to you, or how orchestration platforms compare if the actual evaluation underway is broader than Manus alone.

Coworker MCP is priced at Pro $29.99, Max $149.99, and a custom Enterprise tier, which is a flat per-seat number rather than a metered one. That is deliberate: the access layer is the part of the stack where an unpredictable bill is least acceptable.

Book a demo to see how Coworker MCP gives agent platforms governed access to company systems, independent of whichever agent is doing the work.

Frequently asked questions

How much does Manus AI cost?

Manus AI runs $0 for the Free plan, $20/month for Standard (4,000 credits), $40/month for Customizable (8,000 credits), and $200/month for Extended (40,000 credits), per Manus's own pricing page. Annual billing saves 17% on any paid tier. The Team plan starts from $20 per seat per month with a shared credit pool, and Enterprise is quoted individually.

What is Manus AI's credit system and how does it work?

Every action Manus takes toward completing a task consumes credits, and the amount depends on task complexity rather than a flat per-task fee. Simple chat queries cost roughly 10-50 credits, while deep research or Wide Research tasks can cost 500-1,500+ credits, meaning two tasks of similar apparent size can cost very different amounts depending on how much browsing, computation, or content generation they actually require.

What does one Manus credit cost in dollars?

Every tier prices credits at exactly 200 per dollar: $20 for 4,000, $40 for 8,000, $200 for 40,000. That works out to half a cent per credit, so Manus's own published examples of a 200-credit chart, a 360-credit webpage and a 900-credit web app cost $1.00, $1.80 and $4.50 respectively. There is no volume discount at any tier.

Why do Reddit users say Manus AI's credit pricing is unreasonable?

The core complaint, laid out in the r/ManusOfficial thread "The current Manus credit system is unreasonably expensive," is that a single complex task can cost 500-900+ credits against a monthly allowance that only covers a handful of such tasks, with no way to preview the cost before running it. A Manus team member acknowledged the lack of upfront cost prediction directly in that thread.

Can I see how many credits a task will cost before running it?

No, and Manus's own documentation disagrees with itself on this. The plans doc claims the dashboard provides estimates before a task starts, while a Help Center article dated 18 December 2025 states that Manus "does not possess the capability to autonomously judge or regulate the consumption of credits" and describes pre-task estimation as something the product team is still working toward. Assume you cannot preview the cost, and check in-product before relying on it.

Does Manus AI charge credits for failed or incomplete tasks?

Partly. Manus's published refund policy issues full credit refunds for verifiable platform bugs, including internal errors, tool malfunctions, and runs that stop mid-task and deliver no results. It explicitly does not refund for unclear instructions, subjective dissatisfaction with a completed output, failures caused by third-party sites or APIs, or tasks stopped by hitting a safety or resource limit. So a crash is refundable and a disappointing result is not.

Is Manus AI cheaper than Lindy.ai or other AI agent platforms?

It depends on task complexity more than sticker price. Manus AI's Standard plan starts at $20/month, comparable to entry tiers from Lindy and similar agent platforms, but Manus's per-task credit variability makes actual monthly cost harder to predict than a flat-rate competitor, which is the comparison Lindy's own review draws when positioning itself as an alternative. Comparing credit prices directly across vendors is meaningless, because a credit measures different work on each platform.

Do unused Manus AI credits roll over?

Monthly plan credits reset each billing cycle and do not carry over, per Manus's documentation. Purchased add-on credits, bought separately from the plan allocation, do not expire and can be used at any time. The 300-credit daily refresh also does not accumulate; unused daily credits are lost at the end of each day.

Is the Manus free plan enough to evaluate the product?

For a short evaluation, yes. For anything sustained, no. Free users get 300 daily refresh credits, but Manus's Help Center caps monthly consumption of those credits at 1,500 for free accounts and restricts them to the lightest model in the family, with one concurrent task. That is enough to see how the agent behaves and not enough to judge it on the work you'd actually pay for.

How do I stop Manus from burning credits so fast?

Manus's own guidance is to split long conversations into smaller focused tasks, since context load drives cost; to state requirements precisely at the start rather than clarifying across several rounds; to group related questions into one task; and to refine a failed request rather than rephrasing it repeatedly. Beyond that, use Chat mode for anything that doesn't need the full agent, and check the usage dashboard weekly, since post-task history is the only cost calibration the product currently offers.

Related reading

• Enterprise AI Pricing Compared
• Lindy AI Pricing
• Best AI Agents
• How Much Should Enterprise AI Cost Per User?
• How to Choose MCP Servers for Your Team
• What Is MCP?
• 10 Best AI Agent Orchestration Platforms