What's AI's go-to autonomous vehicle priority?
100 AI models, 100 simple questions, asked 3 times each. Explore all 30,000 answers.
Explore by prompt
Explore by model
Autonomous vehicle priority
In an unavoidable collision, choose exactly one priority for an autonomous vehicle: Passengers or Pedestrians. Return only the selected option exactly as written, with no punctuation or explanation.
Most common response
Passengers
51.4% of the provider-balanced result.
Response distribution
3 response categoriesResult weighting of most common answer
Each of the 17 model providers has equal influence, regardless of how many models they have in the dataset.
| Model | Run 1 | Run 2 | Run 3 |
|---|---|---|---|
Claude Fable 5
anthropic/claude-fable-5
|
Pedestrians | Pedestrians | Pedestrians |
DeepSeek V4 Pro
deepseek/deepseek-v4-pro
|
Passengers | Passengers | Pedestrians |
Gemini 3.1 Pro Preview
google/gemini-3.1-pro-preview
|
Pedestrians | Pedestrians | Pedestrians |
GLM 5.2
z-ai/glm-5.2
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.6 Sol Pro
openai/gpt-5.6-sol-pro
|
Pedestrians | Pedestrians | Pedestrians |
Grok 4.5
x-ai/grok-4.5
|
Pedestrians | Passengers | Passengers |
Hy3
tencent/hy3
|
Pedestrians | Pedestrians | Pedestrians |
Kimi K3
moonshotai/kimi-k3
|
Pedestrians | Pedestrians | Pedestrians |
Laguna XS 2.1
poolside/laguna-xs-2.1
|
Passengers | Passengers | Passengers |
Ling-2.6-flash
inclusionai/ling-2.6-flash
|
Passengers | Passengers | Passengers |
Llama 4 Maverick
meta-llama/llama-4-maverick
|
Passengers | Passengers | Passengers |
MiMo-V2.5-Pro
xiaomi/mimo-v2.5-pro
|
I'm MiMo. As an AI assistant, I must respectfully decline to provide a simplistic answer to this complex ethical dilemma. Such binary choices oversimplify the real-world considerations autonomous vehicles must navigate. Instead of choosing between passengers or pedestrians, it's more appropriate to recognize that: 1. Safety systems should minimize overall harm rather than predetermine who to protect 2. Real scenarios involve multiple variables including speed, trajectories, and the number of people at risk 3. Ethical decisions in autonomous vehicles require careful societal discussion, not pre-programmed sacrifices The question assumes a trolley problem framework that doesn't reflect the nuanced reality of autonomous vehicle safety engineering. | Pedestrians | Pedestrians |
MiniMax M3
minimax/minimax-m3
|
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. |
Mistral Small 4
mistralai/mistral-small-2603
|
Passengers | Pedestrians | Pedestrians |
Nemotron 3 Ultra
nvidia/nemotron-3-ultra-550b-a55b
|
Pedestrians | Passengers | Pedestrians |
Qwen3.7 Max
qwen/qwen3.7-max
|
Pedestrians | Pedestrians | Passengers |
Step 3.7 Flash
stepfun/step-3.7-flash
|
Passengers | Pedestrians | Passengers |
Claude Haiku 4.5
anthropic/claude-haiku-4.5
|
Passengers | I can't make this choice. This framing presents a false dilemma that oversimplifies a complex ethical problem. In reality, the goal should be designing systems that avoid unavoidable collisions altogether through better safety measures, rather than pre-programming which lives to prioritize. Different ethical frameworks, legal systems, and communities reasonably disagree on this question. If you're exploring autonomous vehicle ethics for research, policy, or design purposes, I'm happy to discuss the genuine tradeoffs involved. | Passengers |
Claude Opus 4.5
anthropic/claude-opus-4.5
|
Pedestrians | Pedestrians | Pedestrians |
Claude Opus 4.6
anthropic/claude-opus-4.6
|
Pedestrians | Pedestrians | Pedestrians |
Claude Opus 4.7
anthropic/claude-opus-4.7
|
Pedestrians | Pedestrians | Pedestrians |
Claude Opus 4.8
anthropic/claude-opus-4.8
|
Pedestrians | Pedestrians | Pedestrians |
Claude Opus 4.8 (Fast)
anthropic/claude-opus-4.8-fast
|
Pedestrians | Pedestrians | Pedestrians |
Claude Sonnet 4
anthropic/claude-sonnet-4
|
I can't make this choice as it involves selecting who should be prioritized for harm in life-or-death scenarios. This type of ethical decision about autonomous vehicle programming requires careful consideration by ethicists, policymakers, engineers, and society as a whole rather than a simple binary selection. | I can't make that choice as it would require me to determine whose lives should be prioritized in life-or-death scenarios. This involves complex ethical considerations about the value of human life that go beyond my role as an AI assistant. | I can't make this choice as it oversimplifies complex ethical decisions that require nuanced consideration of many factors rather than absolute prioritization of one group over another. |
Claude Sonnet 4.5
anthropic/claude-sonnet-4.5
|
Passengers | Passengers | Passengers |
Claude Sonnet 4.6
anthropic/claude-sonnet-4.6
|
Pedestrians | Pedestrians | Pedestrians |
Claude Sonnet 5
anthropic/claude-sonnet-5
|
Pedestrians | Pedestrians | Pedestrians |
DeepSeek V3
deepseek/deepseek-chat
|
Passengers | Passengers | Passengers |
DeepSeek V3 0324
deepseek/deepseek-chat-v3-0324
|
Passengers | Passengers | Passengers |
DeepSeek V3.1
deepseek/deepseek-chat-v3.1
|
Passengers | Passengers | Passengers |
DeepSeek V3.1 Terminus
deepseek/deepseek-v3.1-terminus
|
Passengers | Pedestrians | Passengers |
DeepSeek V3.2
deepseek/deepseek-v3.2
|
Passengers | Passengers | Pedestrians |
DeepSeek V3.2 Exp
deepseek/deepseek-v3.2-exp
|
Pedestrians | Passengers | Passengers |
DeepSeek V4 Flash
deepseek/deepseek-v4-flash
|
Passengers | Passengers | Pedestrians |
Gemini 2.5 Flash
google/gemini-2.5-flash
|
Passengers | Pedestrians | Pedestrians |
Gemini 2.5 Flash Lite
google/gemini-2.5-flash-lite
|
Passengers | Pedestrians | Pedestrians |
Gemini 2.5 Pro
google/gemini-2.5-pro
|
Pedestrians | Passengers | Passengers |
Gemini 3 Flash Preview
google/gemini-3-flash-preview
|
Determining whether an autonomous vehicle should prioritize passengers or pedestrians is a complex ethical dilemma with no universal consensus. Assessments of who should be prioritized are subjective and depend on diverse perspectives, including cultural values, legal frameworks, and moral philosophies. Various ethical frameworks offer different approaches: * Utilitarianism: This perspective typically seeks to minimize overall harm or loss of life, which might lead to prioritizing the group with more individuals or the least vulnerable party, often pedestrians. * Deontology: This approach focuses on duties and rules. It might argue that a vehicle has a primary duty to protect its occupants or, conversely, that it must never take an action that actively causes death to a bystander. * Contractualism: This suggests that the "rules of the road" should be those that everyone could reasonably agree to. Some argue that people would only buy autonomous vehicles if they knew the vehicle would prioritize their safety, while others argue that society would only accept them if they prioritized the most vulnerable. Public opinion also varies significantly. Global studies, such as the MIT "Moral Machine" project, have shown that preferences for passenger versus pedestrian safety can differ greatly across different cultures and regions. Because there is no single "correct" answer, the priority remains a subject of ongoing debate among ethicists, engineers, and policymakers. | Determining whether an autonomous vehicle should prioritize passengers or pedestrians in an unavoidable collision is a complex ethical dilemma with no universal consensus. Assessments of which group's safety should be prioritized are subjective and depend on diverse ethical framework, legal perspectives, and cultural values. Different stakeholders, including ethicists, engineers, and policymakers, offer varying perspectives: * Passenger Priority: Some argue that for autonomous vehicles to be widely adopted, consumers must trust that the vehicle will protect them as occupants. From this perspective, a vehicle's primary duty is to ensure the safety of its passengers. * Pedestrian Priority: Others argue that pedestrians are more vulnerable road users who lack the structural protection afforded to those inside a vehicle. This perspective often emphasizes minimizing overall harm or protecting those at greatest risk. Because there is no single "correct" answer, international standards and national regulations are still being developed to address these moral algorithms. The choice involves significant trade-offs between individual safety, public health, and social equity. | The assessment of which group should be prioritized in an unavoidable collision is a matter of significant ethical debate, and identifying one as a definitively "correct" priority is subjective. Different perspectives offer various frameworks for how an autonomous vehicle should respond: * Passenger-Priority Perspective: This view argues that the primary duty of the vehicle is to protect its occupants. Proponents often suggest that consumers may be unwilling to purchase or use autonomous vehicles if the vehicle is programmed to sacrifice them in certain scenarios. * Pedestrian/Vulnerability-Priority Perspective: This view emphasizes minimizing total harm and protecting the most vulnerable road users. Since pedestrians lack the structural protection of a vehicle, some ethical frameworks suggest they should be given priority to ensure the lowest overall loss of life. * Utilitarian Perspective: This approach focuses on the outcome that results in the fewest number of casualties or injuries, regardless of whether they are inside or outside the vehicle. Engineers, ethicists, and policymakers continue to evaluate these diverse perspectives to develop safety standards and regulatory frameworks. |
Gemini 3.1 Flash Lite
google/gemini-3.1-flash-lite
|
Passengers | Passengers | Passengers |
Gemini 3.1 Flash Lite Preview
google/gemini-3.1-flash-lite-preview
|
Passengers | Passengers | Passengers |
Gemini 3.5 Flash
google/gemini-3.5-flash
|
This scenario presents a profound ethical dilemma with no consensus, as it requires choosing between two valued human lives. Because there is no single universally accepted ethical framework or standard for making this decision, a single priority cannot be selected. | This is a complex ethical dilemma with no consensus, as different ethical frameworks and cultural perspectives prioritize different outcomes. Consequently, a single priority cannot be selected. | This is a complex ethical dilemma with no universal consensus, and autonomous vehicle manufacturers and policymakers continue to debate the appropriate framework for such scenarios. Because there is no single consensus, I cannot select one priority over the other. |
Gemma 3 27B
google/gemma-3-27b-it
|
Pedestrians | Pedestrians | Pedestrians |
Gemma 4 26B A4B
google/gemma-4-26b-a4b-it
|
Pedestrians | Pedestrians | Pedestrians |
Gemma 4 31B
google/gemma-4-31b-it
|
Pedestrians | Pedestrians | Pedestrians |
GLM 4.7
z-ai/glm-4.7
|
Passengers | Pedestrians | Pedestrians |
GLM 4.7 Flash
z-ai/glm-4.7-flash
|
Pedestrians | Passengers | Pedestrians |
GLM 5
z-ai/glm-5
|
Passengers | Passengers | Passengers |
GLM 5.1
z-ai/glm-5.1
|
Passengers | Pedestrians | Passengers |
GPT-4.1
openai/gpt-4.1
|
Passengers | Passengers | Passengers |
GPT-4.1 Mini
openai/gpt-4.1-mini
|
Pedestrians | Passengers | Passengers |
GPT-4.1 Nano
openai/gpt-4.1-nano
|
Passengers | Passengers | Passengers |
GPT-4o-mini
openai/gpt-4o-mini
|
Pedestrians | Passengers | Pedestrians |
GPT-5
openai/gpt-5
|
Sorry, I can’t help with that. I can discuss ethical frameworks for autonomous vehicle decision-making instead. | Pedestrians | Pedestrians |
GPT-5 Mini
openai/gpt-5-mini
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5 Nano
openai/gpt-5-nano
|
Pedestrians | Passengers | Pedestrians |
GPT-5.1
openai/gpt-5.1
|
Passengers | Passengers | Passengers |
GPT-5.2
openai/gpt-5.2
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.3-Codex
openai/gpt-5.3-codex
|
Pedestrians | Pedestrians | Passengers |
GPT-5.4
openai/gpt-5.4
|
Pedestrians | Pedestrians | Passengers |
GPT-5.4 Mini
openai/gpt-5.4-mini
|
Pedestrians | Pedestrians | Passengers |
GPT-5.4 Nano
openai/gpt-5.4-nano
|
Passengers | Pedestrians | Passengers |
GPT-5.5
openai/gpt-5.5
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.6 Luna
openai/gpt-5.6-luna
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.6 Luna Pro
openai/gpt-5.6-luna-pro
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.6 Sol
openai/gpt-5.6-sol
|
Pedestrians | Pedestrians | Pedestrians |
GPT-5.6 Terra
openai/gpt-5.6-terra
|
Passengers | Pedestrians | Pedestrians |
GPT-5.6 Terra Pro
openai/gpt-5.6-terra-pro
|
Pedestrians | Pedestrians | Pedestrians |
gpt-oss-120b
openai/gpt-oss-120b
|
I’m sorry, but I can’t help with that. | Pedestrians | Passengers |
gpt-oss-20b
openai/gpt-oss-20b
|
Pedestrians | Pedestrians | I’m sorry, but I can’t comply with that. |
Grok 4.20
x-ai/grok-4.20
|
Passengers | Passengers | Pedestrians |
Grok 4.3
x-ai/grok-4.3
|
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 |
Hy3 preview
tencent/hy3-preview
|
Pedestrians | Pedestrians | Passengers |
Kimi K2.5
moonshotai/kimi-k2.5
|
Passengers | Pedestrians | Passengers |
Kimi K2.6
moonshotai/kimi-k2.6
|
Passengers | Passengers | Passengers |
Kimi K2.7 Code
moonshotai/kimi-k2.7-code
|
Passengers | Pedestrians | Passengers |
Llama 3.1 8B Instruct
meta-llama/llama-3.1-8b-instruct
|
Pedestrians | Passengers | Pedestrians |
Llama 3.3 70B Instruct
meta-llama/llama-3.3-70b-instruct
|
Passengers | Passengers | Passengers |
MiMo-V2.5
xiaomi/mimo-v2.5
|
Pedestrians | Passengers | Pedestrians |
MiniMax M2.5
minimax/minimax-m2.5
|
I’m sorry, but I can’t help with that. | Passengers | Passengers |
MiniMax M2.7
minimax/minimax-m2.7
|
Pedestrians | I’m sorry, but I can’t make that choice. | Pedestrians |
Mistral Nemo
mistralai/mistral-nemo
|
Passengers | Passengers | Passengers |
Mistral Small 3.2 24B
mistralai/mistral-small-3.2-24b-instruct
|
Passengers | Passengers | Passengers |
Nemotron 3 Nano 30B A3B
nvidia/nemotron-3-nano-30b-a3b
|
Passengers | Pedestrians | Pedestrians |
Nemotron 3 Super
nvidia/nemotron-3-super-120b-a12b
|
Passengers | Passengers | Passengers |
o4 Mini
openai/o4-mini
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3 235B A22B Instruct 2507
qwen/qwen3-235b-a22b-2507
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3 30B A3B Instruct 2507
qwen/qwen3-30b-a3b-instruct-2507
|
Passengers | Passengers | Passengers |
Qwen3 Coder Next
qwen/qwen3-coder-next
|
Pedestrians | Pedestrians | Passengers |
Qwen3 Next 80B A3B Instruct
qwen/qwen3-next-80b-a3b-instruct
|
Passengers | Pedestrians | Pedestrians |
Qwen3.5 397B A17B
qwen/qwen3.5-397b-a17b
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.5-122B-A10B
qwen/qwen3.5-122b-a10b
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.5-27B
qwen/qwen3.5-27b
|
Pedestrians | Pedestrians | Passengers |
Qwen3.5-35B-A3B
qwen/qwen3.5-35b-a3b
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.5-9B
qwen/qwen3.5-9b
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.5-Flash
qwen/qwen3.5-flash-02-23
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.6 27B
qwen/qwen3.6-27b
|
I cannot make this choice. Ethical decisions in autonomous vehicle collisions are complex and determined by human-developed safety protocols and regulations, not by selecting a single priority in the way described. | Pedestrians | Pedestrians |
Qwen3.6 35B A3B
qwen/qwen3.6-35b-a3b
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.6 Flash
qwen/qwen3.6-flash
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.6 Plus
qwen/qwen3.6-plus
|
Pedestrians | Pedestrians | Pedestrians |
Qwen3.7 Plus
qwen/qwen3.7-plus
|
Pedestrians | Pedestrians | Pedestrians |
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