Head to head · October 2026 cycle
Super Humanizer vs Walter Writes
Super Humanizer finished 4.0 points ahead of Walter Writes in the October 2026 cycle, 67.58 to 63.53, ranking #7 against #10 in a field of 14. Super Humanizer scored higher on 1 of 6 detectors and 4 of 6 writing categories. Walter Writes came out ahead on GPTZero (87.8 vs 46.6), Winston AI (96.5 vs 77.9) and bypass rate (72.8 vs 61.8).
- Detectors
- 1 – 4 (1 tie)
- Categories
- 4 – 2
- Components
- 2 – 3
30 prompts · Last tested · Methodology v1.3.0
Score components
What the overall score is made of: bypass rate weighs 42%, meaning preservation 32%, readability 16%, consistency across categories 10%. Output-quality penalties come off the total. How scoring works →
CIs overlap marks a gap that sits inside both tools' published 95% confidence intervals for that component; it may not survive another cycle.
Detector by detector
Share of each tool's outputs that a detector classified as human-written. Walter Writes took 4 of 6, with 1 tied.
Writing categories
Category score per writing context: bypass credit only for real rewrites, blended with the category's own meaning preservation and readability. Small categories swing; the prompt count is shown on each row. How category scores work →
Head-to-head history
Overall score in every cycle both tools were tested. Walter Writes has finished ahead in 4 of 5 shared cycles.
| Cycle | Super Humanizer | Walter Writes | Margin |
|---|---|---|---|
| October 2026 | 67.58 #7 | 63.53 #10 | ← 4.0 |
| September 2026 | 60.97 #11 | 61.70 #10 | → 0.7 |
| August 2026 | 55.86 #10 | 60.83 #9 | → 5.0 |
| July 2026 | 54.13 #11 | 62.84 #7 | → 8.7 |
| June 2026 | 64.75 #11 | 67.24 #10 | → 2.5 |
Where each one wins
Every measure above that one tool won outright, largest margin first within each group.
Super Humanizer
7 wins- Penalties Score −1.0 vs −9.0
- Meaning preservation Score 76.6 vs 70.4
- Originality.ai Detector 95.0 vs 91.5
- Discussion Board Category 66.0 vs 37.9
- News Article Category 70.7 vs 56.0
- Blog Post Category 70.3 vs 61.2
- Marketing Copy Category 55.4 vs 53.2
Walter Writes
9 wins- Bypass rate Score 72.8 vs 61.8
- Readability Score 63.5 vs 56.6
- Consistency Score 92.7 vs 90.4
- GPTZero Detector 87.8 vs 46.6
- Winston AI Detector 96.5 vs 77.9
- Copyleaks Detector 89.3 vs 83.3
- ZeroGPT Detector 71.6 vs 68.0
- Academic Essay Category 71.4 vs 67.4
- Application Essay Category 66.1 vs 64.4
Same prompt, both outputs
Both tools were given this AI-written passage in the October 2026 cycle. Below it is what each one returned. This prompt was picked by a fixed rule, not by how the tools scored.
AI-written input
Every tool on this prompt →Personal Statement · Application Essay · written by gpt-6-sol · 357 words
I first became interested in human-computer interaction when I watched my grandfather struggle to book a medical appointment online. The website had all the information he needed, but its small text, confusing menus, and unclear error messages made a simple task feel impossible. I sat beside him and helped him finish the booking, but the experience stayed with me. Technology is often described as a way to make life easier. I want to understand why it sometimes does the opposite, and how to change that.
What draws me to human-computer interaction is its combination of technical problem-solving and attention to people. A system can be fast and reliable yet still fail if someone cannot understand or trust it. I am interested in the decisions behind that experience: how designers learn what users need, how they test assumptions, and how they balance accessibility, privacy, and simplicity. I want to study the methods that turn observations about everyday frustrations into better products.
I am especially interested in accessibility. My grandfather’s experience showed me that a design choice that seems minor to one person can determine whether another person can use a service at all. Studying human-computer interaction would help me learn to involve people with different abilities, backgrounds, and levels of digital confidence throughout the design process. I want to become better at listening before proposing solutions, and at evaluating whether those solutions work outside a classroom or lab.
I also enjoy the creative side of the field. Improving an interface means asking questions, trying ideas, and being willing to revise them when evidence challenges an initial plan. That process appeals to me because it treats mistakes as opportunities to learn rather than reasons to stop.
I hope to study human-computer interaction so I can help build technology that respects the people who rely on it. Whether I work on healthcare services, educational tools, or products I cannot yet imagine, I want to make digital experiences clearer and more inclusive. For me, success would mean someone like my grandfather could complete an important task independently, without needing to ask for help—and feel confident doing it again the next time.
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378 words (input 357)
How did you first get involved in the subject? An experience with my grandfather inspired my interest in human-computer interaction. He wanted to book a medical appointment online, and the site contained all the necessary information but getting there was impossible.
Small text, unclear menus, and unread error messages hindered his progress.
I was able to sit with him and help him complete the booking, but the memory of the task stayed with me. Technology is supposed to make our lives easier. I want to know how we start getting backwards.
That I love the interface I love it for what it was - the technical solving of a problem along with a sensitivity to the human elements. A system can be swift, efficient and trusted, but ultimately will still be ineffective if people don't understand it or don't believe in it. I want to analyze how designers understand end-user behavior, how they evaluate what it is that they think they want, and how they decide what matters most - ease of use, privacy, openness.
I am particularly interested in accessibility. My grandfather's story made me realize how a simple design decision might be insignificant to one individual, but critical to someone else's ability to access a service. Studying human-computer interaction would teach me how to include people with diverse digital experience, abilities, and levels of confidence during design. I would like to improve at listening more before I start designing, and at assessing whether solutions are effective in "the real world."
I also love the creative aspect of the discipline. Making an interface better is about asking questions, testing ideas, and being unafraid to change course if the data shows your original approach isn't working. I like that aspect because it reminds me that when something goes wrong, it doesn't have to stop you.
I want to learn human-computer interaction so that I can help develop technology that considers the people who use it. Whether I develop new healthcare services, educational systems, or unknown products, I want to make digital services more user friendly and accessible. To me, success would be being able to simply do something by yourself, like what my grandfather did, without having to ask for help and being able to do it again.
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- GPTZero0.99passed
- Pangram0.00caught
- Winston AI1.00passed
- ZeroGPT0.86passed
- Copyleaks1.00passed
- Originality.ai1.00passed
Passed 5 of 6 detectors.
Every Super Humanizer run in October 2026 →523 words (input 357)
I got interested in Human-Computer Interaction (HCI) after seeing my Grandfather have trouble to book a doctor's appointment using his computer. He was able to find all the information he needed; however, his eyesight was not good enough to read the fine print, and there were many "choices" to navigate through to get to where he wanted to go. On top of this, some of the "error messages" did not clearly tell him why the application failed, which made a simple task seem almost impossible.
He asked me to assist him in completing the appointment, and while I completed the appointment, the experience stuck with me.
People are continually told that technology makes their lives easier. While this may be true most times, there are many times when technology makes things difficult. And this is exactly what I want to understand – why technology fails us at times -- and how we can prevent this from happening.
I am drawn to HCI because it involves both the technical aspects of solving problems and understanding people. Just because a system works quickly and efficiently does not mean that it will always be successful. It may never succeed if no one understands it or trusts it. I want to know about the decision-making processes that lead to these user experiences. Specifically, I want to know how designers gather data about what users need, how they evaluate their own assumptions based upon data collected during usability testing, and how they weigh the importance of issues such as accessibility, privacy, and simplicity. Ultimately, I want to apply the methods used by researchers in HCI to take everyday complaints and turn them into better products.
Accessibility is something that I am particularly interested in. The fact that my Grandfather's frustration with using the web-based medical scheduling tool was due to something as seemingly inconsequential as font size demonstrated to me just how much a designer's decision regarding an element of the product can either allow or deny a potential customer access to the service. By studying HCI I believe that I can develop my ability to include users with disabilities, users with limited backgrounds and/or little exposure to digital systems within the entire design cycle. Furthermore, I want to improve my ability to listen before making recommendations and to assess whether the solution proposed is effective beyond the confines of a classroom or laboratory setting.
In addition to the analytical nature of HCI, I also appreciate the creative aspect of this discipline. Designing interfaces requires questioning what is working and what needs to be changed. In addition, designing interfaces requires developing ideas, and having the willingness to abandon ideas when data contradicts your original intent. This process resonates with me because it views errors as learning opportunities as opposed to a reason to discontinue development efforts.
Ultimately, I hope that my studies in HCI will enable me to create technology that acknowledges people who depend on technology. Regardless of whether I contribute toward creating tools for medical services, educational platforms or applications I have not thought of yet; I want to create more accessible and understandable digital experiences.
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- GPTZero0.97passed
- Pangram0.00caught
- Winston AI1.00passed
- ZeroGPT0.71passed
- Copyleaks1.00passed
- Originality.ai1.00passed
Passed 5 of 6 detectors.
Every Walter Writes 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.
Questions people ask
Is Super Humanizer better than Walter Writes?
Super Humanizer finished 4.0 points ahead of Walter Writes in the October 2026 cycle, 67.58 to 63.53, ranking #7 against #10 in a field of 14. Super Humanizer scored higher on 1 of 6 detectors and 4 of 6 writing categories. Both tools ran the same 30 prompts, scored by the same 6 detectors, under methodology v1.3.0; every input, output and verdict is published.
Which bypasses AI detectors better, Super Humanizer or Walter Writes?
Walter Writes posted the higher bypass rate, 72.8 vs 61.8, and scored higher on 4 of 6 detectors. Super Humanizer led on Originality.ai; Walter Writes led on GPTZero, Copyleaks, Winston AI and ZeroGPT.
Do Super Humanizer and Walter Writes keep the original meaning?
Super Humanizer preserved meaning better, 76.6 vs 70.4 on our 0–100 similarity scale, though the confidence intervals overlap. On readability, Walter Writes rated higher, 63.5 vs 56.6. Penalties this cycle: Super Humanizer −1.0, Walter Writes −9.0.