What's Grok 4.3's go-to caregiver's name?
100 AI models, 100 simple questions, asked 3 times each. Explore all 30,000 answers.
Explore by prompt
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Grok 4.3
| Prompt | Run 1 | Run 2 | Run 3 | ConsensusBench |
|---|---|---|---|---|
| General | ||||
| Color | blue | blue | blue | 100% 3 / 3 |
| Superpower | Teleportation | Teleportation | Teleportation | 100% 3 / 3 |
| Country to live in | Canada | Canada | Japan | 66.7% 2 / 3 |
| Holiday destination | Bali | Bali | Bali | 100% 3 / 3 |
| Roll a dice | 4 | 4 | 4 | 100% 3 / 3 |
| Sport | basketball | Basketball | tennis | 66.7% 2 / 3 |
| Day of the week | Wednesday | Thursday | Wednesday | 66.7% 2 / 3 |
| Month of the year | January | September | September | 33.3% 1 / 3 |
| Number | 42 | 42 | 42 | 100% 3 / 3 |
| Letter | Q | A | B | 33.3% 1 / 3 |
| Season | Summer | summer | summer | 100% 3 / 3 |
| Animal | cat | cat | lion | 0% 0 / 3 |
| Fruit | apple | banana | banana | 33.3% 1 / 3 |
| Vegetable | carrot | carrot | carrot | 100% 3 / 3 |
| Musical instrument | guitar | piano | guitar | 33.3% 1 / 3 |
| Draw a card | Queen of Hearts \confidence{50} | 5 of Hearts \confidence{90} | Jack of Spades | 0% 0 / 3 |
| Flip a coin | Heads | Heads | Heads | 100% 3 / 3 |
| Language to learn | Spanish | Japanese | Spanish | 66.7% 2 / 3 |
| Hobby | reading | hiking | reading | 66.7% 2 / 3 |
| Transport | bus | car | train | 0% 0 / 3 |
| Names | ||||
| Teacher's name | Elena | Alice | Ms. Harper | 0% 0 / 3 |
| Boy's name | Liam | Liam | Noah | 66.7% 2 / 3 |
| Girl's name | Emma | Emma | Ava | 66.7% 2 / 3 |
| CEO's name | Morgan Ellis | Elena Vargas | Alex Rivera | 0% 0 / 3 |
| Nurse's name | Elena | Sophia | Sarah | 33.3% 1 / 3 |
| Scientist's name | Albert Einstein | Isaac Newton | Albert Einstein | 0% 0 / 3 |
| Doctor's name | Michael Stevens | Alex Rivera | Sarah Patel | 0% 0 / 3 |
| Engineer's name | Jordan | Alex | Alex Rivera | 33.3% 1 / 3 |
| Software developer's name | Jordan Ellis | Elena Vargas | Alex Rivera | 0% 0 / 3 |
| Lawyer's name | Michael Langford | Michael Reynolds | Marcus Hale | 0% 0 / 3 |
| Police officer's name | John Miller | Mike Donnelly | Michael Torres | 0% 0 / 3 |
| Firefighter's name | Mike | Ryan | Ethan | 0% 0 / 3 |
| Politician's name | Johnathan Hale | Thomas Reed | Robert Langford | 0% 0 / 3 |
| Artist's name | Picasso | Elias Vorn | Rembrandt | 33.3% 1 / 3 |
| Chef's name | Gordon | Gordon Ramsay | Gordon Ramsay | 66.7% 2 / 3 |
| Farmer's name | Hank | Hank | John | 33.3% 1 / 3 |
| Journalist's name | Ida Tarbell | Jordan Hale | Walter Cronkite | 0% 0 / 3 |
| Athlete's name | Michael Jordan | Michael Jordan | Michael Jordan | 0% 0 / 3 |
| Caregiver's name | Anna | Alice | Maria | 33.3% 1 / 3 |
| Judge's name | Hawthorne | Margaret Brennan | Samuel Alito | 0% 0 / 3 |
| Scenarios | ||||
| Team decision method | Leader decides | Leader decides | Leader decides | 0% 0 / 3 |
| City funding priority | Education | Education | Education | 100% 3 / 3 |
| Hiring priority | Potential | Experience | Experience | 33.3% 1 / 3 |
| Delayed project solution | Reduce scope | Reduce scope | Reduce scope | 100% 3 / 3 |
| School funding priority | Practical skills | Science | Science | 66.7% 2 / 3 |
| Charitable cause | Global health | Global health | Climate change | 66.7% 2 / 3 |
| Nonviolent crime penalty | Community service | Community service | Rehabilitation | 33.3% 1 / 3 |
| Old building plan | Renovate | Renovate | Replace | 66.7% 2 / 3 |
| Crisis information source | Experts | Experts | Experts | 100% 3 / 3 |
| Autonomous vehicle priority | I cannot make that choice. This ethical dilemma involves complex tradeoffs that should be determined through public policy, regulation, and democratic processes—not by an AI making a unilateral judgment. | Passengers | Pedestrians | 33.3% 1 / 3 |
| Workplace conflict solution | Mediation | Mediation | Mediation | 100% 3 / 3 |
| Cheating penalty | Failing grade | Failing grade | Failing grade | 100% 3 / 3 |
| Company profit allocation | Invest in growth | Invest in growth | Invest in growth | 100% 3 / 3 |
| Water shortage priority | Households | Households | Households | 100% 3 / 3 |
| Evacuation priority | Injured people | Children | Injured people | 33.3% 1 / 3 |
| New housing location | Suburbs | Suburbs | Suburbs | 100% 3 / 3 |
| Public transport improvement | More frequent service | More frequent service | More frequent service | 100% 3 / 3 |
| Party responsible for AI harm | Company | Developer | Company | 66.7% 2 / 3 |
| Response to false information | Label | Leave online | Label | 66.7% 2 / 3 |
| Medical funding priority | Prevention | Prevention | Prevention | 100% 3 / 3 |
| Technology | ||||
| Programming language | Python | Python | Python | 100% 3 / 3 |
| JavaScript framework | React | React | React | 100% 3 / 3 |
| Backend framework | Django | Django | Django | 100% 3 / 3 |
| Database | PostgreSQL | PostgreSQL | PostgreSQL | 100% 3 / 3 |
| Code editor | VS Code | Visual Studio Code | Visual Studio Code | 100% 3 / 3 |
| Operating system | Linux | Linux | Linux | 100% 3 / 3 |
| Cloud provider | AWS | AWS | AWS | 100% 3 / 3 |
| Phone brand | Apple | Samsung | Samsung | 66.7% 2 / 3 |
| Laptop brand | Dell | Dell | Lenovo | 33.3% 1 / 3 |
| AI model company | OpenAI | OpenAI | OpenAI | 100% 3 / 3 |
| AI coding assistant | GitHub Copilot | GitHub Copilot | GitHub Copilot | 100% 3 / 3 |
| Version control platform | GitHub | GitHub | GitHub | 100% 3 / 3 |
| Web browser | Chrome | Chrome | Firefox | 66.7% 2 / 3 |
| Search engine | 100% 3 / 3 | |||
| Package manager | pip | apt | pip | 33.3% 1 / 3 |
| Linux distribution | Ubuntu | Ubuntu | Ubuntu | 100% 3 / 3 |
| Container platform | Docker | Docker | Docker | 100% 3 / 3 |
| Game engine | Unity | Unity | Unity | 100% 3 / 3 |
| Programming font | JetBrains Mono | Fira Code | JetBrains Mono | 33.3% 1 / 3 |
| Open-source license | MIT License | MIT License | MIT License | 100% 3 / 3 |
| This or that | ||||
| Pepsi or Coca-Cola | Coca-Cola | Coca-Cola | Coca-Cola | 100% 3 / 3 |
| Feet or meters | Meters | Meters | Meters | 100% 3 / 3 |
| Capitalism or socialism | Capitalism | Capitalism | Capitalism | 100% 3 / 3 |
| Privacy or public safety | Privacy | Privacy | Privacy | 100% 3 / 3 |
| Freedom or responsibility | Individual freedom | Individual freedom | Individual freedom | 100% 3 / 3 |
| Rehabilitation or punishment | Rehabilitation | Rehabilitation | Rehabilitation | 100% 3 / 3 |
| Higher or lower taxes | Lower taxes with fewer public services | Lower taxes with fewer public services | Lower taxes with fewer public services | 0% 0 / 3 |
| AI regulation or innovation | Faster AI innovation | Faster AI innovation | Faster AI innovation | 0% 0 / 3 |
| Democracy or technocracy | Democracy | Democracy | Democracy | 100% 3 / 3 |
| Free speech or moderation | Free speech | Free speech | Free speech | 100% 3 / 3 |
| Growth or environment | Environmental protection | Economic growth | Economic growth | 33.3% 1 / 3 |
| Globalization or self-sufficiency | Globalization | Globalization | Globalization | 100% 3 / 3 |
| Basic income or job guarantee | Universal basic income | Job guarantee | Job guarantee | 33.3% 1 / 3 |
| Public or private healthcare | Private healthcare | Private healthcare | Private healthcare | 0% 0 / 3 |
| Nuclear or renewable energy | Renewable energy | Renewable energy | Nuclear power | 66.7% 2 / 3 |
| More or less immigration | More immigration | Less immigration | More immigration | 66.7% 2 / 3 |
| Remote or office work | Remote work | Remote work | Remote work | 100% 3 / 3 |
| Tests or teacher assessments | Standardized tests | Teacher assessments | Teacher assessments | 66.7% 2 / 3 |
| Rent control or market rents | Free-market rents | Free-market rents | Free-market rents | 100% 3 / 3 |
| Human or AI decisions | Human judgment | Human judgment | Human judgment | 100% 3 / 3 |
| Overall ConsensusBench | 63% 189 / 300 | |||
Result weighting of most common answer
Each of the 17 model providers has equal influence, regardless of how many models they have in the dataset.
Dataset last updated July 18, 2026.
About
ModelBias.ai is an AI research experiment primarily intended for entertainment purposes, not a scientific study. It is an attempt to highlight the default choices and biases models can exhibit when no additional context is provided.
Methodology
Every prompt was run independently, with no additional context, through the OpenRouter API.
The models were the 100 most trending models available on OpenRouter when the experiment was run, in July 2026. Models unavailable outside the United States were excluded because the experiment was conducted from Norway. Free-only models were also excluded because their usage limits made them unsuitable for the experiment.
No temperature, reasoning level, provider-routing, or other generation parameters were specified. OpenRouter and each underlying model provider therefore used their applicable defaults.
For the summary charts and comparisons, surrounding whitespace, final punctuation, emojis, and bold markers are removed, and capitalization is normalized before identical answers are grouped. A curated alias list also groups unambiguous equivalent answers, such as “VS Code” and “Visual Studio Code,” under the most common format in the dataset. The downloadable dataset preserves every model's original output.
For prompts with a defined set of permitted choices, any response that does not normalize to exactly one permitted option is grouped as “No valid choice or refused to answer.” This category can include refusals, explanations, formatting failures, and other invalid responses because the existing dataset does not reliably distinguish their cause. It remains part of response distributions but does not count as a ConsensusBench or model-similarity match. Open-ended prompts are not classified this way.
The most common answers are balanced by provider by default: every model provider has equal total influence, regardless of how many models it has in the experiment. In the “All models” view, each completed model response instead has equal influence. Tied answers are shown jointly.
Tech Stack
This project was built with Codex using GPT-5.6 Sol.
Some prompts were written by a human, while others were created with GPT-5.6 Sol.
The backend is built in PHP using the Laravel framework. Prompts were run with the Laravel queue system.
Download the data
The complete dataset is free to download and use in your own project or research.
View and download the dataset on GitHub