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

Head to head · October 2026 cycle

SupWriter vs Walter Writes

Walter Writes finished 0.8 points ahead of SupWriter in the October 2026 cycle, 63.53 to 62.75, ranking #10 against #11 in a field of 14. Walter Writes scored higher on 4 of 6 detectors and 2 of 6 writing categories. SupWriter came out ahead on penalties (None vs −9.0), discussion board prompts (57.6 vs 37.9) and news article prompts (64.4 vs 56.0).

62.75 /100
overall score
#11 /14
rank ▼ 6
+0.78
Walter Writes leads →
Detectors
1 – 4 (1 tie)
Categories
4 – 2
Components
2 – 3
63.53 /100
overall score
#10 /14
rank -

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 →

Bypass rate Walter Writes by 22.8
50.0 72.8
Meaning preservation SupWriter by 7.1
77.5 70.4
Readability Walter Writes by 14.4
49.2 63.5
Consistency Walter Writes by 1.9
90.8 92.7
Penalties fewer is better SupWriter by 9.0
None −9.0

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.

GPTZero Walter Writes by 78.9
8.9 87.8
Originality.ai Walter Writes by 36.0
55.5 91.5
Copyleaks Walter Writes by 11.2
78.2 89.3
Winston AI Walter Writes by 13.0
83.5 96.5
ZeroGPT SupWriter by 2.3
73.9 71.6
Pangram Even
0.0 0.0

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 →

Academic Essay Application Essay Blog Post Marketing Copy Discussion Board News Article Academic Essay: SupWriter 57.4 · Walter Writes 71.4 Application Essay: SupWriter 59.4 · Walter Writes 66.1 Blog Post: SupWriter 62.0 · Walter Writes 61.2 Marketing Copy: SupWriter 58.4 · Walter Writes 53.2 Discussion Board: SupWriter 57.6 · Walter Writes 37.9 News Article: SupWriter 64.4 · Walter Writes 56.0
SupWriter Walter Writes Outer ring = 100
Academic Essay 6 prompts Walter Writes by 14.1
57.4 71.4
Application Essay 6 prompts Walter Writes by 6.8
59.4 66.1
Blog Post 6 prompts SupWriter by 0.7
62.0 61.2
Marketing Copy 6 prompts SupWriter by 5.2
58.4 53.2
Discussion Board 3 prompts SupWriter by 19.7
57.6 37.9
News Article 3 prompts SupWriter by 8.4
64.4 56.0

Head-to-head history

Overall score in every cycle both tools were tested. They have finished ahead 1 time each across 2 shared cycles.

50 60 70 80 September 2026 October 2026 September 2026: Walter Writes 61.70 (#10) September 2026: SupWriter 72.80 (#5) October 2026: Walter Writes 63.53 (#10) October 2026: SupWriter 62.75 (#11) 62.8 63.5
SupWriter Walter Writes
Cycle SupWriter Walter Writes Margin
October 2026 62.75 #11 63.53 #10 → 0.8
September 2026 72.80 #5 61.70 #10 ← 11.1

Where each one wins

Every measure above that one tool won outright, largest margin first within each group.

SupWriter

7 wins
  • Penalties Score None vs −9.0
  • Meaning preservation Score 77.5 vs 70.4
  • ZeroGPT Detector 73.9 vs 71.6
  • Discussion Board Category 57.6 vs 37.9
  • News Article Category 64.4 vs 56.0
  • Marketing Copy Category 58.4 vs 53.2
  • Blog Post Category 62.0 vs 61.2

Walter Writes

9 wins
  • Bypass rate Score 72.8 vs 50.0
  • Readability Score 63.5 vs 49.2
  • Consistency Score 92.7 vs 90.8
  • GPTZero Detector 87.8 vs 8.9
  • Originality.ai Detector 91.5 vs 55.5
  • Winston AI Detector 96.5 vs 83.5
  • Copyleaks Detector 89.3 vs 78.2
  • Academic Essay Category 71.4 vs 57.4
  • Application Essay Category 66.1 vs 59.4

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.

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.

Show the full input

369 words (input 357)

My grandfather was trying to book a medical appointment. I saw him struggle with that and that’s when I got interested in HCI. He could have easily found the information he needed but everything was in very small text, menus were confusing, and error messages were vague. I sat down next to him, assisted him in completing the booking, but it stuck with me. A lot of people say technology is making life easier. I seek to learn why name-calling has the opposite effect sometimes, and how to change that.

I am interested in human-computer interaction because it combines technical problems and focusing on people. A system may be fast and reliable but can fail if the user cannot understand it or trust it. I am curious about the decisions made behind that experience: how designers learn users’ needs, how they stress assumptions, and how they balance accessibility, privacy and simplicity. I wish to explore the ways to observe everyday disappointments to come up with better-products.

Accessibility is my area of interest. My grandfather's experience demonstrated to me that a design decision that seems trivial or insignificant to one person could be the determining factor in another person's ability to use that service. Studying human-computer interaction would help involve people from various capabilities, backgrounds, and digital confidence in the design process. I hope to improve how I listen before suggesting solutions, and how I judge whether those solutions work outside the classroom or lab.

I like the creative aspect of the field too. When working on an interface, you ask questions, try things and, when evidence counteracts your original plan, change it. I like the process because when I make a mistake I will use this as a reason to learn and not stop.

My hope is to study HCI to help build technology that treats the people who use it with respect. I seek to improve digital experiences making them clearer and more inclusive, whether working on healthcare services, educational tools, or products yet to be imagined. To me, success is my grandfather being able to complete an important task on his own, without asking for help; and feeling just as confident to do so again next time.

Show the full output
  • GPTZero0.00caught
  • Pangram0.00caught
  • Winston AI1.00passed
  • ZeroGPT0.51passed
  • Copyleaks1.00passed
  • Originality.ai0.59passed

Passed 4 of 6 detectors.

Every SupWriter 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.

Show the full output
  • 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 SupWriter better than Walter Writes?

Walter Writes finished 0.8 points ahead of SupWriter in the October 2026 cycle, 63.53 to 62.75, ranking #10 against #11 in a field of 14. Walter Writes scored higher on 4 of 6 detectors and 2 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, SupWriter or Walter Writes?

Walter Writes posted the higher bypass rate, 72.8 vs 50.0, and scored higher on 4 of 6 detectors. SupWriter led on ZeroGPT; Walter Writes led on GPTZero, Originality.ai, Copyleaks and Winston AI.

Do SupWriter and Walter Writes keep the original meaning?

SupWriter preserved meaning better, 77.5 vs 70.4 on our 0–100 similarity scale. On readability, Walter Writes rated higher, 63.5 vs 49.2. Penalties this cycle: SupWriter None, Walter Writes −9.0.