Head to head · October 2026 cycle
StealthGPT vs SupWriter
StealthGPT finished 11.8 points ahead of SupWriter in the October 2026 cycle, 74.50 to 62.75, ranking #2 against #11 in a field of 14. StealthGPT scored higher on 6 of 6 detectors and 5 of 6 writing categories. SupWriter came out ahead on penalties (None vs −3.0), meaning preservation (77.5 vs 61.8) and discussion board prompts (57.6 vs 57.2).
- Detectors
- 6 – 0
- Categories
- 5 – 1
- Components
- 3 – 2
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 →
Detector by detector
Share of each tool's outputs that a detector classified as human-written. StealthGPT took 6 of 6.
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. They have finished ahead 1 time each across 2 shared cycles.
| Cycle | StealthGPT | SupWriter | Margin |
|---|---|---|---|
| October 2026 | 74.50 #2 | 62.75 #11 | ← 11.8 |
| September 2026 | 65.10 #9 | 72.80 #5 | → 7.7 |
Where each one wins
Every measure above that one tool won outright, largest margin first within each group.
StealthGPT
14 wins- Bypass rate Score 88.1 vs 50.0
- Readability Score 72.6 vs 49.2
- Consistency Score 90.9 vs 90.8
- GPTZero Detector 94.8 vs 8.9
- Pangram Detector 69.9 vs 0.0
- Originality.ai Detector 96.3 vs 55.5
- Copyleaks Detector 100.0 vs 78.2
- Winston AI Detector 90.4 vs 83.5
- ZeroGPT Detector 77.3 vs 73.9
- News Article Category 84.0 vs 64.4
- and 4 more
SupWriter
3 wins- Penalties Score None vs −3.0
- Meaning preservation Score 77.5 vs 61.8
- Discussion Board Category 57.6 vs 57.2
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 gemini-3-8-flash · 336 words
My fascination with Human-Computer Interaction began not in a computer lab, but while watching my grandmother struggle to use a telehealth application during a medical emergency. The technology to save her life was there, but the interface alienated her. In that moment of panic, poor contrast, ambiguous icons, and convoluted navigation transformed a lifesaving tool into an impenetrable wall. This experience cemented my conviction that the most advanced technology is entirely futile if it fails to account for human emotion, cognitive limits, and diversity.
Throughout my undergraduate studies, I sought to understand both sides of this equation—the technical constraints of software and the psychological realities of the user. In my coursework and independent projects, I found myself consistently drawn to the friction points where user intent clashed with algorithmic execution. While collaborating on a mobile application for local transit, I realized that writing efficient code was only half the battle; conducting user interviews, mapping user journeys, and redesigning the information architecture were what actually made the tool viable. Technology, I realized, should adapt to the messiness of the human experience, not force humans to adapt to the rigidity of machines.
I want to pursue a graduate degree in Human-Computer Interaction to bridge the gap between computational power and human empathy. I am particularly eager to explore how emerging paradigms—such as voice interfaces, multimodal AI, and ambient computing—can be designed to be accessible rather than exclusive. As artificial intelligence becomes deeply woven into the fabric of daily life, the need for thoughtful, ethical, and inclusive interaction design has never been more urgent.
Your program offers the ideal interdisciplinary environment for me to deepen this inquiry. By combining rigorous user research methodologies with cutting-edge technical prototyping, I hope to investigate how adaptive interfaces can empower underserved populations, including the elderly and digitally illiterate. Ultimately, I do not just want to build systems that work; I want to design intuitive, equitable experiences that make technology feel less like an obstacle and more like an effortless extension of human capability.
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390 words (input 336)
My goal is to learn how to make these capabilities resonate with users’ emotions, mental models, and physical and cognitive constraints. The importance of Human-Computer Interaction became clear for me during a medical emergency. My grandmother’s medical emergency required immediate contact with her doctor using a new telehealth application. Watching her become alienated by low contrast colors, inscrutable icons, and convoluted navigation made me realize that all of an application’s technical capabilities are futile if its interface is poorly designed.
Since then, I’ve been fascinated by HCI’s ability to bridge the gap between technical capabilities and empathetic design. My undergraduate coursework and projects allowed me to explore how to reconcile technical considerations in software with the needs of users. For example, I worked on a mobile app to facilitate the use of local transportation options. User studies, information architecture, and journey mapping proved equally important as technical feasibility and efficient coding. This project allowed me to consider HCI’s role in making technology that is effective and viable. The solution to this problem, and many others, requires a holistic perspective: users will never fit neatly within computing systems; computing systems must better fit users’ complexity and diversity.
HCI is poised to tackle these challenges. In graduate school, I want to delve deeper into the technical and psychological considerations for HCI, especially regarding accessibility in multimodal AI, ambient computing, and voice interfaces. I want to learn how to leverage the latest developments in computing to create interfaces that adapt to the needs of users who have been underserved by current technology: those who are digitally illiterate and the elderly. Ultimately, I want to be able to holistically approach problems from a user-centered, ethical perspective: considering how to make computing and AI accessible to all.
This means learning to be an effective researcher and a skilled technologist. As an undergraduate, I’ve taken classes and done independent work in HCI, human-centered design, UX/UI design, and programming. For my own projects, I’ve done user research and technical prototyping. I’ve seen firsthand that balancing technical considerations with user-centeredness makes technology resonate with users. I want to continue that work at the graduate level. I want to understand what makes technology resonate with people. I want to create computing experiences that people can rely upon. I’m eager to learn from your faculty and contribute to your community.
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- GPTZero1.00passed
- Pangram0.51passed
- Winston AI1.00passed
- ZeroGPT0.85passed
- Copyleaks1.00passed
- Originality.ai1.00passed
Passed 6 of 6 detectors.
Every StealthGPT run in October 2026 →342 words (input 336)
The fascination with Human-Computer Interaction began not in a lab but when I saw my grandmother struggling with a telehealth app during an emergency. The interface design made it difficult to save her life with existing technology. At that moment of panic, I could not read the GPS because of insufficient contrast, unclear icons and complicated navigation. My experience showed that no matter how advanced technology is, it amount to nothing if it did not factor in human emotion, brain capacity and diversity.
During my undergraduate degree, I wanted to familiarise myself with this equation software limitations and the psychological reality of the user. Throughout my studies and independent projects, I became fascinated with friction points that arose between user intent and algorithmic execution. While my teammate and I were working on a mobile application for local transit, I observed that writing efficient code was not enough. Analyzing user interviews, mapping user journeys, and redesigning the information architecture was what made the tool viable. I understood that technology should be messy and should help the human around it become messy as well.
I want to study for a graduate degree in human-computer interaction to bridge the gap between “what” computers can do and “how” we may design them to act in an agency (manner). I am eager to discover ways to design the new paradigms, which include voice interfaces, multimodal AI and ambient computing, to be accessible rather than exclusive. As artificial intelligence becomes a part of daily life and become a necessity, the interaction design must be thoughtful, ethical design and inclusive.
Your program offers the best interdisciplinary setting for me to further this inquiry. Through rigorous user research methodologies coupled with advanced technical prototyping, I hope to explore how adaptive interfaces can empower disadvantaged groups, including the elderly and digitally illiterate individuals. In the end, I don’t just want to build functioning systems; I want to create experiences that are intuitive and equitable. I want users to not feel as if they are battling technology, but rather utilising it effortlessly.
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- GPTZero0.00caught
- Pangram0.00caught
- Winston AI0.96passed
- ZeroGPT0.80passed
- Copyleaks1.00passed
- Originality.ai0.13caught
Passed 3 of 6 detectors.
Every SupWriter 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 StealthGPT better than SupWriter?
StealthGPT finished 11.8 points ahead of SupWriter in the October 2026 cycle, 74.50 to 62.75, ranking #2 against #11 in a field of 14. StealthGPT scored higher on 6 of 6 detectors and 5 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, StealthGPT or SupWriter?
StealthGPT posted the higher bypass rate, 88.1 vs 50.0, and scored higher on 6 of 6 detectors. StealthGPT led on GPTZero, Originality.ai, Copyleaks, Winston AI, ZeroGPT and Pangram.
Do StealthGPT and SupWriter keep the original meaning?
SupWriter preserved meaning better, 77.5 vs 61.8 on our 0–100 similarity scale. On readability, StealthGPT rated higher, 72.6 vs 49.2. Penalties this cycle: StealthGPT −3.0, SupWriter None.