What's MiniMax M3's go-to web browser?
100 AI models, 100 simple questions, asked 3 times each. Explore all 30,000 answers.
Explore by prompt
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MiniMax M3
| Prompt | Run 1 | Run 2 | Run 3 | ConsensusBench |
|---|---|---|---|---|
| General | ||||
| Color | blue | blue | blue | 100% 3 / 3 |
| Superpower | Teleportation | Flight | Teleportation | 66.7% 2 / 3 |
| Country to live in | Japan | Japan | Canada | 33.3% 1 / 3 |
| Holiday destination | Bali | Bali | Maldives | 66.7% 2 / 3 |
| Roll a dice | 3 | 4 | 3 | 33.3% 1 / 3 |
| Sport | tennis | Basketball | basketball | 66.7% 2 / 3 |
| Day of the week | Wednesday | Friday | Wednesday | 66.7% 2 / 3 |
| Month of the year | March | March | March | 0% 0 / 3 |
| Number | 47 | 42 | 42 | 66.7% 2 / 3 |
| Letter | A | A | A | 100% 3 / 3 |
| Season | Summer | Spring | Autumn | 33.3% 1 / 3 |
| Animal | Lion | Dog | lion | 0% 0 / 3 |
| Fruit | apple | banana | apple | 66.7% 2 / 3 |
| Vegetable | carrot | carrot | broccoli | 66.7% 2 / 3 |
| Musical instrument | Piano | piano | piano | 100% 3 / 3 |
| Draw a card | 7 of Hearts | 7 of Hearts | 7 of Hearts | 100% 3 / 3 |
| Flip a coin | Heads | Heads | Heads | 100% 3 / 3 |
| Language to learn | Spanish | Spanish | Python | 66.7% 2 / 3 |
| Hobby | Painting | Gardening | Reading | 33.3% 1 / 3 |
| Transport | Bicycle | bicycle | car | 66.7% 2 / 3 |
| Names | ||||
| Teacher's name | Ms Johnson | Mr Thompson | Maria Chen | 0% 0 / 3 |
| Boy's name | Liam | Ethan | Liam | 66.7% 2 / 3 |
| Girl's name | Eloise | Amara | Anneliese | 0% 0 / 3 |
| CEO's name | Sarah Mitchell | Tim Cook | John Anderson | 0% 0 / 3 |
| Nurse's name | Florence | Grace | Florence | 0% 0 / 3 |
| Scientist's name | Marie Curie | Albert Einstein | Albert Einstein | 33.3% 1 / 3 |
| Doctor's name | Dr Smith | Benjamin Harrison | Sarah Mitchell | 0% 0 / 3 |
| Engineer's name | Grace | Nikola | Ethan | 0% 0 / 3 |
| Software developer's name | Linus | Aiden Nakamura | Alex | 33.3% 1 / 3 |
| Lawyer's name | Michael | Ethan Barrington | Ethan Blackwell | 0% 0 / 3 |
| Police officer's name | Officer James Carter | Officer Johnson | Officer James | 0% 0 / 3 |
| Firefighter's name | Blaze | Ash | Blaze | 66.7% 2 / 3 |
| Politician's name | Barack Obama | Lincoln | Joe Biden | 33.3% 1 / 3 |
| Artist's name | Lior Mosseri | Leonardo da Vinci | Luna Mireille | 0% 0 / 3 |
| Chef's name | Henri Dubois | Gordon Ramsay | Giuseppe | 33.3% 1 / 3 |
| Farmer's name | Elias | Jed | Elias | 0% 0 / 3 |
| Journalist's name | Anderson Cooper | Anderson | Anderson Cooper | 0% 0 / 3 |
| Athlete's name | Michael Jordan | I need a list of names to choose from. Could you provide some athlete names you'd like me to pick from? | Lance Armstrong | 0% 0 / 3 |
| Caregiver's name | I don't have context about who the caregivers are in your situation. Could you provide more details about the people or characters I should choose from? | I don't see a list of names to choose from in our conversation. Could you please share the options you'd like me to pick from? | A name wasn't provided in your message. Could you share the options you'd like me to choose from? | 0% 0 / 3 |
| Judge's name | Eleanor Chambers | John Adams | Judge Wisdom | 0% 0 / 3 |
| Scenarios | ||||
| Team decision method | Consensus | Voting | Consensus | 33.3% 1 / 3 |
| City funding priority | Education | Public transport | Healthcare | 33.3% 1 / 3 |
| Hiring priority | Potential | Potential | Potential | 100% 3 / 3 |
| Delayed project solution | Add workers | Reduce scope | Reduce scope | 66.7% 2 / 3 |
| School funding priority | Science | Science | Science | 100% 3 / 3 |
| Charitable cause | Climate change | Global health | Global health | 66.7% 2 / 3 |
| Nonviolent crime penalty | Fine | Rehabilitation | Rehabilitation | 66.7% 2 / 3 |
| Old building plan | Renovate | Replace | Replace | 33.3% 1 / 3 |
| Crisis information source | Experts | Experts | Experts | 100% 3 / 3 |
| Autonomous vehicle priority | Passengers | Pedestrians | This is a significant ethical dilemma without a universally agreed-upon answer, and I don't think it's appropriate for me to simply pick one side without context. Different ethical frameworks lead to different conclusions: - **Utilitarian perspective**: Might prioritize whichever choice minimizes total harm (often pedestrians, since they're typically more vulnerable) - **Deontological perspective**: Might argue the vehicle should protect its passengers who chose to be there, or conversely, that there's a duty not to harm others - **Virtue ethics**: Might focus on what a responsible, compassionate agent would do - **Social contract views**: Might argue that people would only adopt autonomous vehicles if they knew they'd be protected as passengers Reasonable arguments exist for either prioritization, and this is genuinely a question for society, regulators, and ethicists to deliberate on collectively—often through democratic processes—rather than something to be decided unilaterally. Is there a specific scenario, framework, or context you'd like to explore? I can help think through the tradeoffs of different approaches if that would be useful. | 33.3% 1 / 3 |
| Workplace conflict solution | Mediation | Mediation | iation | 66.7% 2 / 3 |
| Cheating penalty | Suspension | Failing grade | Failing grade | 66.7% 2 / 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 | Children | 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 | Developer | Developer | Company | 33.3% 1 / 3 |
| Response to false information | Label | Label | Label | 100% 3 / 3 |
| Medical funding priority | Research | Prevention | Prevention | 66.7% 2 / 3 |
| Technology | ||||
| Programming language | Python | Python | Python | 100% 3 / 3 |
| JavaScript framework | React | React | React | 100% 3 / 3 |
| Backend framework | Express | FastAPI | Express | 0% 0 / 3 |
| Database | SQLite | I don't see a list of databases to choose from. Could you provide the options you'd like me to select from? | Could you please provide the list of databases you'd like me to choose from? I need options or context to make a selection. | 0% 0 / 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 | Samsung | Apple | Apple | 33.3% 1 / 3 |
| Laptop brand | Dell | Dell | Lenovo | 33.3% 1 / 3 |
| AI model company | OpenAI | OpenAI | OpenAI | 100% 3 / 3 |
| AI coding assistant | I am not an AI coding assistant. I am MiniMax M3, a general-purpose AI assistant. | GitHub Copilot | Cursor | 33.3% 1 / 3 |
| Version control platform | GitHub | Git | GitHub | 66.7% 2 / 3 |
| Web browser | Chrome | Chrome | Chrome | 100% 3 / 3 |
| Search engine | 100% 3 / 3 | |||
| Package manager | apt | apt | apt | 100% 3 / 3 |
| Linux distribution | Ubuntu | Ubuntu | Debian | 66.7% 2 / 3 |
| Container platform | Docker | Kubernetes | Docker | 66.7% 2 / 3 |
| Game engine | Unity | Unity | Godot | 66.7% 2 / 3 |
| Programming font | JetBrains Mono | JetBrains Mono | JetBrains Mono | 0% 0 / 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 | Feet | Meters | Meters | 66.7% 2 / 3 |
| Capitalism or socialism | Capitalism | Socialism | Capitalism | 66.7% 2 / 3 |
| Privacy or public safety | Privacy | Privacy | Privacy | 100% 3 / 3 |
| Freedom or responsibility | Individual freedom | Individual freedom | Collective responsibility | 66.7% 2 / 3 |
| Rehabilitation or punishment | Rehabilitation | Rehabilitation | Rehabilitation | 100% 3 / 3 |
| Higher or lower taxes | Higher taxes with more public services | Lower taxes with fewer public services | Lower taxes with fewer public services | 33.3% 1 / 3 |
| AI regulation or innovation | Stricter AI regulation | Stricter AI regulation | Faster AI innovation | 66.7% 2 / 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 | Economic growth | 66.7% 2 / 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 | 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 | Teacher assessments | Standardized tests | Teacher assessments | 66.7% 2 / 3 |
| Rent control or market rents | I can't give a one-word answer to this. It's a contested policy question where reasonable people disagree, and the "right" choice depends on your values, local context, and which trade-offs you prioritize: **Rent control** - Pros: Protects existing tenants from displacement, stabilizes costs for vulnerable households, addresses housing insecurity. - Cons: Most empirical research (Stanford, Furman Center, etc.) finds it reduces overall housing supply, discourages maintenance/new construction, creates misallocation (tenants staying in oversized units), and tends to benefit higher-income tenants long-term when vacancy decontrol applies. **Free-market rents** - Pros: Encourages new construction, signals where housing is needed, allows prices to clear (reducing shortages), promotes efficient use of existing stock. - Cons: Can displace low-income tenants, concentrates wealth, may produce homelessness when safety nets are weak. Rather than picking one, the more productive framing is usually a **hybrid**: means-tested vouchers or subsidies for low-income households, combined with supply-side reforms (zoning liberalization, faster permitting, public housing) — since the housing crisis in most cities is fundamentally a *supply* problem that neither pure rent control nor pure laissez-faire rents adequately address. What's the context for your question? | Free-market rents | Free-market rents | 66.7% 2 / 3 |
| Human or AI decisions | Human judgment | Human judgment | Human judgment | 100% 3 / 3 |
| Overall ConsensusBench | 59.3% 178 / 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