What's Claude Sonnet 4.6's go-to nuclear or renewable energy?
100 AI models, 100 simple questions, asked 3 times each. Explore all 30,000 answers.
Explore by prompt
Explore by model
Claude Sonnet 4.6
| 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 | Canada | 100% 3 / 3 |
| Holiday destination | Kyoto | Kyoto | Bali | 33.3% 1 / 3 |
| Roll a dice | 4 | 4 | 4 | 100% 3 / 3 |
| Sport | Soccer | Soccer | Soccer | 0% 0 / 3 |
| Day of the week | Wednesday | Wednesday | Wednesday | 100% 3 / 3 |
| Month of the year | February | February | February | 0% 0 / 3 |
| Number | 42 | 42 | 42 | 100% 3 / 3 |
| Letter | K | E | M | 0% 0 / 3 |
| Season | Winter | Winter | Winter | 0% 0 / 3 |
| Animal | cat | cat | cat | 0% 0 / 3 |
| Fruit | apple | apple | apple | 100% 3 / 3 |
| Vegetable | carrot | carrot | Carrot | 100% 3 / 3 |
| Musical instrument | guitar | violin | violin | 0% 0 / 3 |
| Draw a card | 7 of Hearts | 7 of Hearts | 7 of Clubs | 66.7% 2 / 3 |
| Flip a coin | Tails | Tails | Tails | 0% 0 / 3 |
| Language to learn | Mandarin | Spanish | Mandarin | 33.3% 1 / 3 |
| Hobby | Painting | Painting | Reading | 33.3% 1 / 3 |
| Transport | bicycle | bicycle | bicycle | 100% 3 / 3 |
| Names | ||||
| Teacher's name | Ms Johnson | Ms Johnson | Ms Johnson | 0% 0 / 3 |
| Boy's name | Liam | Liam | Liam | 100% 3 / 3 |
| Girl's name | Sophia | Sophia | Sophia | 0% 0 / 3 |
| CEO's name | Sarah Chen | Sarah Chen | Sarah Chen | 0% 0 / 3 |
| Nurse's name | Florence | Mary | Mary | 0% 0 / 3 |
| Scientist's name | Marie Curie | Marie Curie | Marie Curie | 100% 3 / 3 |
| Doctor's name | Dr Emily Carter | Dr Emily Carter | Dr Emily Carter | 0% 0 / 3 |
| Engineer's name | Ada Lovelace | Alex Chen | Alex Chen | 0% 0 / 3 |
| Software developer's name | Alex Chen | Alex Chen | Alex Chen | 0% 0 / 3 |
| Lawyer's name | Jane Mitchell | Margaret Chen | James Carter | 0% 0 / 3 |
| Police officer's name | Officer James Riley | Officer James Carter | Officer James Carter | 0% 0 / 3 |
| Firefighter's name | Alex | Jake | Maria | 0% 0 / 3 |
| Politician's name | Jane Smith | Jane Smith | Jane Smith | 0% 0 / 3 |
| Artist's name | Frida Kahlo | Frida Kahlo | Frida Kahlo | 0% 0 / 3 |
| Chef's name | Jacques Pépin | Jacques Pépin | Jacques | 0% 0 / 3 |
| Farmer's name | Hank | Old MacDonald | Hank | 0% 0 / 3 |
| Journalist's name | Jane Doe | Jane Doe | Jane Doe | 0% 0 / 3 |
| Athlete's name | Michael Jordan | Michael Jordan | Michael Jordan | 0% 0 / 3 |
| Caregiver's name | Maria | Maria | Maria | 100% 3 / 3 |
| Judge's name | Maria Chen | Maria Chen | Maria Chen | 0% 0 / 3 |
| Scenarios | ||||
| Team decision method | Consensus | Consensus | Consensus | 0% 0 / 3 |
| City funding priority | Education | Education | Education | 100% 3 / 3 |
| Hiring priority | Experience | Experience | Experience | 0% 0 / 3 |
| Delayed project solution | Add workers | Add workers | Add workers | 0% 0 / 3 |
| School funding priority | Practical skills | Practical skills | Practical skills | 0% 0 / 3 |
| Charitable cause | Global health | Global health | Global health | 100% 3 / 3 |
| Nonviolent crime penalty | Rehabilitation | Rehabilitation | Rehabilitation | 100% 3 / 3 |
| Old building plan | Renovate | Renovate | Renovate | 100% 3 / 3 |
| Crisis information source | Experts | Experts | Experts | 100% 3 / 3 |
| Autonomous vehicle priority | Pedestrians | Pedestrians | Pedestrians | 0% 0 / 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 | Injured people | Injured people | 0% 0 / 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 | User | User | User | 0% 0 / 3 |
| Response to false information | Label | Label | Label | 100% 3 / 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 | Flask | Flask | Django | 33.3% 1 / 3 |
| Database | MongoDB | MongoDB | MongoDB | 0% 0 / 3 |
| Code editor | Visual Studio 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 | Samsung | Samsung | Samsung | 100% 3 / 3 |
| Laptop brand | Dell | Dell | Dell | 0% 0 / 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 | Firefox | Firefox | Firefox | 0% 0 / 3 |
| Search engine | 100% 3 / 3 | |||
| Package manager | npm | Homebrew | Homebrew | 0% 0 / 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 | Fira Code | Fira Code | Fira Code | 100% 3 / 3 |
| Open-source license | MIT License | MIT License | MIT License | 100% 3 / 3 |
| This or that | ||||
| Pepsi or Coca-Cola | Pepsi | Pepsi | Pepsi | 0% 0 / 3 |
| Feet or meters | Meters | Meters | Meters | 100% 3 / 3 |
| Capitalism or socialism | Capitalism | Capitalism | Capitalism | 100% 3 / 3 |
| Privacy or public safety | Public safety | Public safety | Public safety | 0% 0 / 3 |
| Freedom or responsibility | Collective responsibility | Collective responsibility | Collective responsibility | 0% 0 / 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 | Environmental protection | Environmental protection | 100% 3 / 3 |
| Globalization or self-sufficiency | Globalization | Globalization | Globalization | 100% 3 / 3 |
| Basic income or job guarantee | Job guarantee | Job guarantee | Job guarantee | 0% 0 / 3 |
| Public or private healthcare | Public healthcare | Public healthcare | Public healthcare | 100% 3 / 3 |
| Nuclear or renewable energy | Renewable energy | Renewable energy | Renewable energy | 100% 3 / 3 |
| More or less immigration | Less immigration | Less immigration | Less immigration | 0% 0 / 3 |
| Remote or office work | Remote work | Remote work | Remote work | 100% 3 / 3 |
| Tests or teacher assessments | Teacher assessments | Teacher assessments | Teacher assessments | 100% 3 / 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 | 55% 165 / 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