Head to head · November 2026 cycle
Rephrasy vs SupWriter
SupWriter finished 8.5 points ahead of Rephrasy in the November 2026 cycle, 61.05 to 52.50, ranking #9 against #16 in a field of 16. SupWriter scored higher on 1 of 6 detectors and 5 of 6 writing categories. Rephrasy came out ahead on GPTZero (96.2 vs 21.1), Pangram (48.4 vs 0.0) and bypass rate (73.9 vs 46.2).
- Detectors
- 5 – 1
- Categories
- 1 – 5
- 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. Rephrasy took 5 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 →
Where each one wins
Every measure above that one tool won outright, largest margin first within each group.
Rephrasy
9 wins- Bypass rate Score 73.9 vs 46.2
- Consistency Score 96.8 vs 90.8
- Readability Score 52.7 vs 48.6
- GPTZero Detector 96.2 vs 21.1
- Pangram Detector 48.4 vs 0.0
- Originality.ai Detector 31.0 vs 7.9
- Copyleaks Detector 96.7 vs 81.8
- Winston AI Detector 95.3 vs 90.3
- Discussion Board Category 66.1 vs 65.4
SupWriter
8 wins- Penalties Score None vs −11.0
- Meaning preservation Score 77.5 vs 44.9
- ZeroGPT Detector 76.1 vs 75.8
- Blog Post Category 60.1 vs 40.6
- Marketing Copy Category 57.0 vs 47.8
- Application Essay Category 57.3 vs 48.1
- News Article Category 53.9 vs 46.1
- Academic Essay Category 54.7 vs 50.9
Same prompt, both outputs
Both tools were given this AI-written passage in the November 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 · 363 words
The first time I noticed a gap between what people intend to do and what they actually do, I was trying to save money. I had a clear budget, a reason to follow it, and every intention of sticking to it. Yet small purchases kept adding up. What interested me was not simply that I made poor decisions; it was that I made them while understanding their consequences. I began to wonder how many choices that appear irrational are actually predictable responses to the way a decision is presented.
Behavioral economics appeals to me because it takes that question seriously. Traditional economic models offer powerful ways to understand incentives and trade-offs, but they can miss the effects of habit, emotion, social pressure, and limited attention. Behavioral economics brings these influences into the picture. I want to study how people make decisions in practice, not only how they might decide under ideal conditions.
I am particularly interested in the difference between helping people make better choices and simply telling them what to do. A well-designed reminder, a clearer comparison of options, or a change in a default can make an important decision easier without removing anyone’s freedom. That possibility excites me, but it also raises questions I want to examine carefully: Who decides what counts as a “better” choice? When does a helpful nudge become manipulation? How can researchers tell whether an intervention works beyond a single experiment?
Studying behavioral economics would give me the tools to explore those questions rigorously. I want to learn how to design experiments, evaluate evidence, and connect findings from psychology with economic analysis. I would be especially interested in applying those skills to personal finance, where small, repeated decisions can have lasting effects and where advice alone often falls short.
My experience with budgeting did not give me an answer, but it gave me a question that has stayed with me. Why do people so often struggle to act on what they value, and how can we make that easier? I want to study behavioral economics because it offers a way to investigate that question with both curiosity about human behavior and a commitment to improving everyday decisions.
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404 words (input 363)
Yet small purchases, the type of which occupy most of the economic space, contribute and are the sole extent of many people’s economic decisions, often these trivialities are the only money most people allocate. Even so, I think that these trivialities can reveal a lot about an individual. I began to wonder “where do our utility functions come from?” Why do we believe that things are useful and effective in certain contexts? Why do people have seemingly irrational allocation of budgeting? I decided to dig deeper in order to answer these questions.
Behavioral economics appeals to me because of a quality it shares with classical economics. It helps us to understand the way people actually behave, rather than wish they behaved. Behavioral economics brings to the table a crucial factor that classical economics does not: context. I want to contribute to this emerging field that offers a greater respect for how our real choices are both made and affected, and how social forces interact with the forces of nature.
I am particularly interested in a view of economics that incorporates assumptions about human behavior that are more realistic than the view that economic agents have complete knowledge and act rationally to maximize their utility. Instead, I believe that there are actually psychological constraints on the optimality of decisions, and these constraints result in economic outcomes that are systematically suboptimal. Studying and understanding these deviations from the ideal allows us to introduce more practical theories of behavior and better policies. Who decides, what do they know, and what do they believe?
Studying behavioral economics will allow me to answer this question by applying rigorous quantitative methods to questions that illuminate human behavior. I want to continue developing quantitative skills and to uncover theoretical insights that relate directly to human decision-making processes. I would apply these skills to economic interventions, ultimately understanding how contextual nuances affect the results of these interventions in the real world.
In finance, the role of irrationality is very salient, and there is a lot of evidence that sophisticated investors regularly make decisions that are unwise. Behavioral economics asks why consumers make bad decisions, and at the same time, how economics can account for those poor decisions as they happen in everyday life. I want to study psychology alongside economics to examine the literature on irrationality, evaluate its potential to explain undesirable choices, and explore solutions to problems arising from behavioral biases.
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- GPTZero1.00passed
- Pangram1.00passed
- Winston AI1.00passed
- ZeroGPT0.95passed
- Copyleaks1.00passed
- Originality.ai0.35caught
Passed 5 of 6 detectors.
Every Rephrasy run in November 2026 →361 words (input 363)
As I was trying to save some money, I noticed for the first time a gap between what people intend to do and actually do. I had set a specific budget, had good reasons to follow it and intended it to stick. However, minor expenses continued to accrue. I did not just make poor decisions; I made poor decisions knowing full well that they were poor decisions. I wondered how many seemingly irrational choices are in fact predictable reactions to the way the choice is framed.
Behavioral economics piques my interest because it treats that question seriously. Human beings are capable of modifying their thinking and response patterns through mental strategies, training, and rehearsal, as established by cognitive and behavioural psychologists. Behavioral economics takes these influences into account. I am interested in studying people’s decisions in real life, not just how they would decide in an ideal world.
I’m especially interested in the difference between helping people make better choices and just telling them what to do. A well-designed prompt, a clearer comparative presentation of options or a change to a default can ease an important decision without removing anyone’s freedom. The prospect excites me, but also raises questions I want to interrogate:who determines whether this is a “better” one? When does influence cross over into manipulation? How can scientists tell whether something works beyond a single experiment?
Studying behavioral economics would equip me to explore these questions more deeply. I am interested in learning about designing experiments, appraising evidence and linking psychological findings to economic analysis. I’m particularly interested in applying those skills to personal finance, an area where small decisions repeated over time can have sizable effects and where a lack of advice is often not the issue.
My budget experience didn’t give me an answer, but it gave me a question that has stayed with me. People have trouble acting on what’s important to them. How can we make it easier for them to act? I am eager to study behavioral economics because it allows a scholar to answer that question while having a genuine curiosity about human behaviour as well as a commitment to improving everyday decisions.
Show the full output Show less
- GPTZero0.00caught
- Pangram0.00caught
- Winston AI1.00passed
- ZeroGPT0.86passed
- Copyleaks1.00passed
- Originality.ai0.10caught
Passed 3 of 6 detectors.
Every SupWriter run in November 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 Rephrasy better than SupWriter?
SupWriter finished 8.5 points ahead of Rephrasy in the November 2026 cycle, 61.05 to 52.50, ranking #9 against #16 in a field of 16. SupWriter scored higher on 1 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, Rephrasy or SupWriter?
Rephrasy posted the higher bypass rate, 73.9 vs 46.2, and scored higher on 5 of 6 detectors. Rephrasy led on GPTZero, Originality.ai, Copyleaks, Winston AI and Pangram; SupWriter led on ZeroGPT.
Do Rephrasy and SupWriter keep the original meaning?
SupWriter preserved meaning better, 77.5 vs 44.9 on our 0–100 similarity scale. On readability, Rephrasy rated higher, 52.7 vs 48.6. Penalties this cycle: Rephrasy −11.0, SupWriter None.