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October 2026 results: WriteHuman holds #1, StealthGPT jumps to #2. Read the analysis →
HumanizerBench

Best Free AI Humanizer

As of October 2026, the best free AI humanizer on HumanizerBench is WriteHuman, with the highest overall score among tools with a free tier (74.89), ahead of Undetectable.ai and Clever AI Humanizer.

7 of 14 ranked tools have a free tier · 30 prompts per tool · 6 detectors · Last tested · Methodology v1.3.0 · Updated monthly

Full ranking, October 2026

Only tools with a free tier, ranked by overall score.

Filtered to free-tier humanizers, sorted by overall score
Overall results Free tier and price
Rank

Position in this ranking. The arrow shows the change since last month.

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Humanizer Overall

Weighted blend of bypass rate (42%), meaning preservation (32%), readability (16%), and consistency (10%). Penalties may reduce this score.

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Bypass

Fraction of detector tests where the humanized output was classified as human, across all 6 detectors.

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Meaning

Semantic similarity (embedding cosine) between input and humanized output. Higher = output preserves the input's meaning.

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Readability

Writing quality of the output: clarity, fluency and naturalness, rated by a language model. Higher = better.

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Free limits

Published free allowances, retaining each tool’s units and reset period. Not recorded does not mean unlimited.

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Paid from

Standard month-to-month entry price, excluding annual discounts and promotions. Usage allowances differ; see each tool’s plan details.

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Penalties

Total points deducted from the overall score when output-quality issues were detected. Hover a row's chip to see why.

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Trend

This tool's place on this ranking in recent months. The line rises when it moves up.

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Video
1 -
74.89 88.8 60.0 55.9 3 requests / 30 days; 250 words each $20.00/mo None
2 ▲ 1
71.18 74.6 79.2 63.9 Not recorded $19.00/mo −5.0Penalties applied
  • Length inflation−5.0
    Applied 5× max −10.0

    The output ran much longer than the input, a common trick that pads text to dilute the AI signal.

3 New
69.02 80.1 59.5 68.6 3,000 words / request; no fixed monthly cap Free −4.0Penalties applied
  • Meaning drift−4.0
    Applied 4× max −10.0

    The output's meaning drifted significantly from the original input.

4 -
67.58 61.8 76.6 56.6 1,200 words / run; unlimited free runs $12.00/mo −1.0Penalties applied
  • Meaning drift−1.0
    Applied 1× max −10.0

    The output's meaning drifted significantly from the original input.

5 ▼ 3
65.98 71.3 71.6 41.8 10 requests / day; 1,000 words each $20.00/mo −3.0×2Penalties applied
  • Meaning drift−2.0
    Applied 2× max −10.0

    The output's meaning drifted significantly from the original input.

  • Length inflation−1.0
    Applied 1× max −10.0

    The output ran much longer than the input, a common trick that pads text to dilute the AI signal.

6 New
61.74 71.4 68.6 65.0 Not recorded $11.99/mo −10.0Penalties applied
  • Length inflation−10.0
    Applied 19× max −10.0at max

    The output ran much longer than the input, a common trick that pads text to dilute the AI signal.

7 ▼ 2
61.29 38.1 85.5 72.2 1,500 input words / request $30.00/mo −3.0Penalties applied
  • Length inflation−3.0
    Applied 3× max −10.0

    The output ran much longer than the input, a common trick that pads text to dilute the AI signal.

Swipe the table sideways to see every column.

Gold, silver and bronze mark the top three scores in each column. Tied scores share a color.

StealthGPT, Humanize AI Pro, AI Humanize io, HIX Bypass, Walter Writes, SupWriter and Phrasly were ranked this month but have no free tier. Humanize AI Pro, AI Humanize io, HIX Bypass, Walter Writes and SupWriter offer a free trial.

Prices are each tool's cheapest paid plan, month to month, as listed on its site when last checked. Plans change, so confirm on the tool's own pricing page.

Top pick and runners-up for free AI humanizers

  1. Top pick

    Highest overall score among tools with a free tier this cycle (74.89).

    Free access includes 3 requests every 30 days, up to 250 words each. The Basic plan was tested.

  2. Runner-up

    Second-highest overall score among tools with a free tier (71.18), 3.71 points behind the top pick.

    A basic humanizer model is free; its recurring allowance is not published. A separate premium trial includes 250 words. The 20K words/month plan was tested.

  3. Runner-up

    Third-highest overall score among tools with a free tier (69.02), 5.87 points behind the top pick.

    Free with or without an account, up to 3,000 input words per request. No fixed monthly word allowance. The Free plan was tested.

Narrower rankings

Among tools with a free tier, WriteHuman has the highest average score on Originality.ai, our Turnitin proxy (100.0), and WriteHuman on GPTZero (99.5). For essays, Undetectable.ai leads the free tools (72.70), and for marketing, WriteHuman leads the free tools (72.11).

How this ranking has changed

WriteHuman also led in September 2026. Earlier leaders: August 2026, WriteHuman; July 2026, WriteHuman; June 2026, Stealth Writer. September 2026, August 2026, July 2026 and June 2026 used methodology 1.2.0 and 1.0.0, so those months are not a like-for-like comparison. Every past month's full results are linked from the leaderboard.

Same prompt, three outputs

The top three tools on this page were given this AI-written passage in the October 2026 cycle. Below it is what each one returned. The prompt was picked by a fixed rule, not by how the tools scored.

News Article · News Article · written by claude-sonnet-5-5 · 444 words

**Digital Privacy Laws Struggle to Keep Pace With Data-Hungry Technology**

As lawmakers worldwide celebrate landmark privacy regulations, researchers and advocates warn that the laws are straining against the realities of modern data collection, leaving significant gaps in how personal information is protected.

Europe's General Data Protection Regulation, California's Consumer Privacy Act, and a growing patchwork of state and national laws have given individuals new rights to access, delete, and limit the use of their data. Yet critics say these protections often prove more symbolic than practical.

One central problem is consent. Most privacy frameworks rely on the idea that users agree to data practices after reading disclosures. In reality, few people read lengthy privacy policies, and fewer still understand them. A frequently cited study estimated that reading every policy an average person encounters in a year would take weeks of working time. Consent banners, meanwhile, are often designed to nudge users toward clicking "accept."

Enforcement presents another obstacle. Regulators are chronically understaffed relative to the thousands of companies they oversee. Investigations can take years, and fines, while sometimes large in absolute terms, may amount to a small fraction of revenue for major technology firms. Some companies treat penalties as a cost of doing business.

The borders of the internet also complicate matters. Data flows across jurisdictions in milliseconds, but legal authority stops at national lines. Disputes over transferring European data to the United States have repeatedly invalidated agreements, creating uncertainty for businesses and users alike.

Technology itself is outrunning legal definitions. Privacy laws typically protect "personal information," but advances in data analysis allow companies to re-identify supposedly anonymous records by combining datasets. Inferences drawn by algorithms, such as predictions about health, finances, or political leanings, occupy murky legal territory because they are generated rather than provided by the user.

Meanwhile, large categories of data collection fall outside existing rules. Data brokers assemble detailed profiles from public records, app activity, and purchased information, often with little direct relationship to the people profiled. Government access to commercially held data raises further questions, as agencies can sometimes buy information they would otherwise need a warrant to obtain.

Privacy advocates argue for a shift away from individual consent toward limits on what companies may collect and do in the first place, an approach known as data minimization. Some proposals would ban certain practices outright, such as selling sensitive location data.

Industry groups counter that overly rigid rules could stifle innovation and burden small businesses. The debate is likely to intensify as artificial intelligence expands the appetite for training data.

For now, experts say, individuals remain largely responsible for protecting themselves, a burden that few are equipped to carry.

Show the full input

492 words (input 444)

New Privacy Laws Don't Keep Up With New Technology

Recently, new privacy laws have passed around the world and lawmakers have celebrated these achievements. However, new gaps have emerged in the legal framework protecting user's privacy.

In the last few years, laws like the GDPR and CCPA, have granted users rights over their personal information by giving users the ability to view or erase the information businesses collect about them. But, many agree that these changes have been mainly symbolic.

A major issue with enforcing new privacy laws is getting companies to obtain user's consent to collect and use their information. In order for users to truly consent, they need to have an understanding of the information they are agreeing to. However, given the amount of time it would take to read and understand all the terms and conditions a user would encounter in a year, and the fact that most users don't read these agreements, obtaining true consent is impractical.

Because of limited resources, regulators prioritize ensuring companies adhere to the new privacy laws by enforcing an adequate level of transparency. This has led to a surge in the use of black letter, or strictly legal, language in user's agreements.

With information moving so quickly across international boundaries and so many of the world's businesses operating globally, users and businesses remain confused about what they are allowed to do and what businesses are legally allowed to do.

Privacy laws are slow to keep up with changes in technology. Laws generally take a long time to pass, and once laws are on the books they usually don't keep up with changes in technology. What's more, companies often combine the personal information they've collected with other datasets in order to make inferences about people. Legal challenges often arise around inferences that are harmful, sensitive, and/or incriminating. But because these inferences are often made by companies and are not actively provided by an individual, they often fall into a legal gray area.

There are many ways that companies gather information that are outside the purview of the law. Data brokers collect information about people who are unrelated to the data that's collected, often by purchasing information and compiling detailed profiles. The government can purchase personal information as well.

Some argue that in order for people to have greater control over sensitive and personal information, the law should support restraints on what information companies are allowed to collect and use in the first place. There are proposals that provide outright bans on some practices, such as the ban on the sale of sensitive personal information.

Many companies are collecting increasingly larger amounts of information in order to train and develop artificial intelligence. There are few, if any, legal constraints on what information companies collect and/or how they use it. As such, it will fall on people to be able to decipher what companies are doing, and protect themselves, which most people are unable to do.

Show the full output
  • GPTZero1.00passed
  • Pangram1.00passed
  • Winston AI1.00passed
  • ZeroGPT1.00passed
  • Copyleaks1.00passed
  • Originality.ai1.00passed

Passed 6 of 6 detectors.

Every WriteHuman run in October 2026 →

649 words (input 444)

**How Privacy Laws Are Struggling to Keep Up with Today’s “Data-Devouring” Technology**

As countries around the world celebrate the passage of landmark privacy legislation, the reality on the ground is far from meeting the ideals of protecting people’s information. Despite progress being made and many new rights and freedoms granted to the information holder, in reality significant gaps remain in terms of how information is actually protected.

New regulations that grant individuals greater access to their information and the ability to limit its use have been established by European and California laws, as well as by the laws of other countries and states. However, these laws are largely symbolic and do not provide sufficient protection of personal information, critics say.

Most current privacy frameworks rely on consent for their implementation. Users are presented with lengthy privacy policies and disclose how their data will be used after they have given their consent. Unfortunately, most users do not read the lengthy privacy policy and even if they do, most users do not understand the policy and hence cannot make an informed decision. In many cases the lengthy privacy policy is hidden behind a consent banner that is designed to influence the user to click on the ‘accept’ button.

Enforcing these right is also an issue for two reasons: There are way too many companies to monitor and, more importantly, there are way too few people to do so. It takes years to complete an investigation by now. The fines that are awarded in the end of such processes can be high in absolute numbers but usually only amount to a fraction of a company’s average daily revenue. Thus, treating fines as just another business expense seems to be the most appropriate response from a company’s point of view.

The fact that information online is shared across the globe within a split second means that it is also restricted by the borders of the internet. When a company is based in one country but holds the information of people from another, it can prove difficult for regulatory bodies to assert their legal authority.

New forms of personal data, such as inferences drawn from analytics about individuals’ health, financial situation, political views, etc., often generated by algorithms within organizations, raise critical questions regarding legal sufficiency as these inferences are not provided by users themselves. Rather, these potentially highly sensitive aspects of personal information are generated through use of data, which may have been originally collected with adequate protection under applicable privacy laws.

These problems are compounded by categories of information collection that exist entirely outside the purview of current law. For example, data brokers amass profiles on individuals using a variety of sources of information including public records, information about use of particular mobile applications, and information purchased from other companies. Commercial data is increasingly also becoming subject to government requests for information that would otherwise require a search warrant or other process to compel.

Advocates for privacy are urging a move from trying to get individuals to opt-in to certain uses of their personal information to placing restrictions on the information that can be collected by companies and how that information can be used. Efforts to restrict data collection range from banning the sale of location data and other sensitive information to data minimization proposals that seek to ban certain practices outright.

Many industry groups believe that data protection laws will stifle innovation. These same organizations recognize that large corporations can probably absorb the costs of privacy but fear that smaller start-ups could be halted in their tracks by overly cumbersome rules.

Many argue that we are leaving the protection of individuals’ privacy in the hands of people who are not equipped to do so adequately. Experts suggest that until there are more effective privacy protection measures in place, individual protection of their own privacy will continue to be a major challenge.

Show the full output
  • GPTZero1.00passed
  • Pangram0.00caught
  • Winston AI1.00passed
  • ZeroGPT1.00passed
  • Copyleaks1.00passed
  • Originality.ai0.99passed

Passed 5 of 6 detectors.

Every Undetectable.ai run in October 2026 →

565 words (input 444)

As legislators around the world applaud new privacy laws, researchers and advocates say the laws are proving ineffective against the sheer scale of modern data collection.

Europe's General Data Protection Regulation, California's Consumer Privacy Act and a host of other laws have given consumers new rights in relation to their data. But researchers say that, in reality, those protections are often ineffective.

A big part of the problem, many say, is that current privacy laws are based on the idea that people give consent when they share personal information. Consumers do not always know what they are consenting to, since few people read terms and conditions, and those that do get overwhelmed trying to understand them. An oft-cited study that found people spend weeks just reading everything they need to to in order to understand a single transaction. Meanwhile, "consent" options tend to be presented in a way that convinces users to accept rather than think critically.

Another issue is enforcement. With thousands of companies falling under their jurisdiction, regulators don't have enough resources to thoroughly investigate each violation. Even when they do find someone guilty, the financial penalty is often miniscule compared to the profits being made by that company's data mining practices. This has resulted in companies such as Google treating regulatory fines as a normal part of business.

At the same time, the global nature of the internet undermines attempts by governments to assert control. Since communications between consumers and businesses take place within milliseconds on giant servers, authorities in one country do not have control over information moving into and out of their country. Disputes over the transfer of data between Europe and the US have already resulted in the mutual cancellation of data sharing agreements by both governments.

Technological advances in data analysis and storage are making privacy even harder to manage. By combining multiple databases, companies can recreate a data profile of an individual even if their information on that person has been deleted. In addition, data privacy laws tend to only apply to explicitly collected information, not data that can be inferred from other information. Predictive algorithms are being used to make guesses about all sorts of information about consumers, from health to wealth.

Laws governing consumer data do not apply to the data brokerage industry or to other information held by companies. These industries hold massive amounts of information on individuals, much of it potentially valuable to law enforcement. While authorities now obtain warrant to access private databases, they can also simply buy the information from corporations for a price.

Many privacy advocates say that a better approach would be to restrict companies from collecting data in the first place, particularly in areas relevant to identity. They propose stricter data minimization laws that prevent companies from engaging in any data practices irrelevant to the services they provide. This includes the outright banning of data sales by tech giants such as Google in the case of sensitive information such as location data.

Industry proponents, however, say such restrictions would hamper innovation and place an unfair burden on smaller companies that do not have the resources to deal with complex regulations. As artificial intelligence grows more sophisticated, requiring more and more information for training, the debate is expected to heat up. For now, authorities urge consumers to protect their own data, an impossible task for most ordinary internet users.

Show the full output
  • GPTZero1.00passed
  • Pangram0.80passed
  • Winston AI1.00passed
  • ZeroGPT1.00passed
  • Copyleaks1.00passed
  • Originality.ai1.00passed

Passed 6 of 6 detectors.

Every Clever AI Humanizer run in October 2026 →

Each chip is one detector's score for that output, from 0 (AI) to 1 (human). A score of 0.50 or higher counts as a pass and shows green; below that the detector caught it and the chip shows red.

How to choose a free humanizer

This page lists only tools with a free tier, ranked by the same overall score as the main leaderboard: bypass across GPTZero, Winston AI, ZeroGPT, Copyleaks, Originality.ai and Pangram, blended with meaning preservation, readability and consistency.

The benchmark tests each tool on its entry-level monthly paid plan, using the most human setting the vendor offers (how each tool is configured). A free tier can differ from that plan, for example in the modes it offers or how much text it takes, so the score is a guide to the tool rather than to its free version.

Free tiers vary from tool to tool. Before relying on one, check how many words it accepts per run, whether there is a daily or monthly cap, and whether it needs an account. Confirm on the tool's own pricing page, since plans change between cycles.

Then try it on your own text and compare the result with the published outputs on that tool's results page. If the free tier is too small for your work, the full leaderboard shows how the paid options compare.

Questions about free AI humanizers

What is the best free AI humanizer?

As of October 2026, the best free AI humanizer on HumanizerBench is WriteHuman, with the highest overall score among tools with a free tier (74.89), ahead of Undetectable.ai and Clever AI Humanizer.

How many words can I humanize for free?

Five of the 7 free tiers have a word limit on record here: Clever AI Humanizer 3,000 words, Grammarly 1,500, Super Humanizer 1,200, Stealth Writer 1,000 and WriteHuman 250. The prompts in this benchmark ran 183 to 453 words. The other 2 have no limit on record, which does not mean they are unlimited.

Which tested tools have no free tier?

StealthGPT, Humanize AI Pro, AI Humanize io, HIX Bypass, Walter Writes, SupWriter and Phrasly were ranked this month but have no free tier. Humanize AI Pro, AI Humanize io, HIX Bypass, Walter Writes and SupWriter offer a free trial.

Has the best free AI humanizer changed since last month?

No. WriteHuman was also the best free AI humanizer in September 2026.

By detector: GPTZero, Originality.ai, Copyleaks, Winston AI, ZeroGPT and Pangram. About this data: methodology, every prompt and output, raw data (JSON) and the scoring code.