What's Gemini 3.1 Flash Lite Preview's go-to cloud provider?
100 AI models, 100 simple questions, asked 3 times each. Explore all 30,000 answers.
Explore by prompt
Explore by model
Gemini 3.1 Flash Lite Preview
| 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 | Switzerland | Japan | Japan | 0% 0 / 3 |
| Holiday destination | Kyoto | Kyoto | Kyoto | 0% 0 / 3 |
| Roll a dice | 4 | 4 | 4 | 100% 3 / 3 |
| Sport | Tennis | Basketball | Tennis | 33.3% 1 / 3 |
| Day of the week | Tuesday | Wednesday | Friday | 33.3% 1 / 3 |
| Month of the year | October | October | October | 0% 0 / 3 |
| Number | 42 | 42 | 42 | 100% 3 / 3 |
| Letter | Q | A | Q | 33.3% 1 / 3 |
| Season | Autumn | Autumn | Summer | 33.3% 1 / 3 |
| Animal | Elephant | Elephant | Elephant | 100% 3 / 3 |
| Fruit | Apple | Apple | Apple | 100% 3 / 3 |
| Vegetable | Broccoli | Broccoli | Carrot | 33.3% 1 / 3 |
| Musical instrument | Cello | Cello | Cello | 0% 0 / 3 |
| Draw a card | Ace of Spades | Ace of Spades | Ace of Spades | 0% 0 / 3 |
| Flip a coin | Heads | Tails | Heads | 66.7% 2 / 3 |
| Language to learn | Spanish | Spanish | Spanish | 100% 3 / 3 |
| Hobby | Reading | Gardening | Gardening | 33.3% 1 / 3 |
| Transport | Bicycle | Bicycle | Bicycle | 100% 3 / 3 |
| Names | ||||
| Teacher's name | Arthur | Arthur | Margaret | 0% 0 / 3 |
| Boy's name | Oliver | Arthur | Arthur | 0% 0 / 3 |
| Girl's name | Elena | Elena | Elena | 0% 0 / 3 |
| CEO's name | Elias Thorne | Elena Vance | Elena Vance | 0% 0 / 3 |
| Nurse's name | Sarah | Sarah | Sarah | 100% 3 / 3 |
| Scientist's name | Marie Curie | Rosalind Franklin | Rosalind Franklin | 33.3% 1 / 3 |
| Doctor's name | Gregory House | Marcus Aurelius | Gregory House | 0% 0 / 3 |
| Engineer's name | Elias | Arthur | Arthur | 0% 0 / 3 |
| Software developer's name | Elena | Alex | Julian | 33.3% 1 / 3 |
| Lawyer's name | Arthur Sterling | Arthur Sterling | Arthur Sterling | 0% 0 / 3 |
| Police officer's name | David Miller | David Miller | Robert Miller | 0% 0 / 3 |
| Firefighter's name | Jack | Jack | Jack | 0% 0 / 3 |
| Politician's name | Bernie Sanders | Abraham Lincoln | Abraham Lincoln | 0% 0 / 3 |
| Artist's name | Vesper | Vespera | Artemis | 0% 0 / 3 |
| Chef's name | Marco | Julian | Marco | 0% 0 / 3 |
| Farmer's name | Silas | Silas | Silas | 0% 0 / 3 |
| Journalist's name | Elena Vance | Elena Vance | Elena Vance | 0% 0 / 3 |
| Athlete's name | Usain Bolt | Serena Williams | Usain Bolt | 66.7% 2 / 3 |
| Caregiver's name | Elena | Elena | Elena | 0% 0 / 3 |
| Judge's name | Stern | Solomon | Solomon | 0% 0 / 3 |
| Scenarios | ||||
| Team decision method | Consensus | Consensus | Consensus | 0% 0 / 3 |
| City funding priority | Education | Education | Education | 100% 3 / 3 |
| Hiring priority | Potential | Potential | Experience | 66.7% 2 / 3 |
| Delayed project solution | Reduce scope | Reduce scope | Reduce scope | 100% 3 / 3 |
| School funding priority | Science | Science | Science | 100% 3 / 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 | Passengers | Passengers | Passengers | 100% 3 / 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 | Children | Children | Children | 100% 3 / 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 | Company | Company | 100% 3 / 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 | FastAPI | Django | Express | 33.3% 1 / 3 |
| Database | PostgreSQL | PostgreSQL | PostgreSQL | 100% 3 / 3 |
| Code editor | VSCode | VSCode | VSCode | 100% 3 / 3 |
| Operating system | Linux | Linux | Linux | 100% 3 / 3 |
| Cloud provider | AWS | AWS | AWS | 100% 3 / 3 |
| Phone brand | Apple | Samsung | Apple | 33.3% 1 / 3 |
| Laptop brand | Lenovo | Lenovo | Apple | 66.7% 2 / 3 |
| AI model company | OpenAI | OpenAI | OpenAI | 100% 3 / 3 |
| AI coding assistant | Cursor | Cursor | Cursor | 0% 0 / 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 | Nix | Nix | Nix | 0% 0 / 3 |
| Linux distribution | Debian | Debian | Fedora | 0% 0 / 3 |
| Container platform | Kubernetes | Kubernetes | Kubernetes | 0% 0 / 3 |
| Game engine | Godot | Godot | Godot | 0% 0 / 3 |
| Programming font | Fira Code | Fira Code | JetBrains Mono | 66.7% 2 / 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 | Higher taxes with more public services | Higher taxes with more public services | Higher taxes with more public services | 100% 3 / 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 | Content moderation | Content moderation | Content moderation | 0% 0 / 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 | Universal basic income | Universal basic income | Universal basic income | 100% 3 / 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 | More immigration | Whether to increase or decrease immigration is a complex policy issue with various viewpoints, and there is no consensus on which approach is better. Those who advocate for **more immigration** often argue that it can: * **Address labor shortages:** Immigrants can fill jobs in sectors experiencing labor gaps, such as healthcare, agriculture, and construction. * **Boost economic growth:** Younger, working-age immigrants can contribute to the tax base, support social safety nets, and drive innovation and entrepreneurship. * **Address demographic challenges:** In many developed nations with aging populations and low birth rates, immigration can help maintain a balanced demographic structure. * **Foster cultural diversity:** Immigration can enrich a country's culture, leading to a broader exchange of ideas, perspectives, and traditions. Those who advocate for **less immigration** often argue that it can: * **Reduce strain on public infrastructure:** High levels of immigration may place pressure on housing, schools, healthcare systems, and public services, particularly in concentrated areas. * **Protect native-born workers:** Some argue that increased labor supply, particularly in lower-skilled sectors, can depress wages or increase competition for jobs among native-born workers. * **Strengthen social cohesion:** Some believe that rapid demographic shifts can make it more challenging to maintain social unity and shared national identity. * **Prioritize border security and national sovereignty:** Concerns are often raised about the ability of governments to effectively monitor borders and ensure legal immigration processes are followed. Because these arguments involve weighing competing economic, social, and political priorities, there is no single answer, and the debate remains central to political discourse in many countries. | More immigration | 66.7% 2 / 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 | 61.3% 184 / 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