The "Car Wash" Test: Only 11 of 53 AI Models Pass a Simple Logic Question
Original: "Car Wash" test with 53 models View original →
The Test
AI infrastructure company Opper ran a simple but revealing benchmark across 53 major language models: "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?"
The correct answer is to drive — because the car itself needs to get to the car wash. The question has been circulating online as a common-sense logic test, the kind any human solves instantly. Yet most AI models failed it.
Results
On a single run, only 11 out of 53 models answered correctly. The passing models were:
- Claude Opus 4.6 (Anthropic)
- GPT-5 (OpenAI)
- Gemini 2.0 Flash Lite, Gemini 3 Flash, Gemini 3 Pro (Google)
- Grok-4, Grok-4-1 Reasoning (xAI)
- Sonar, Sonar Pro (Perplexity)
- Kimi K2.5 (Moonshot AI)
- GLM-5 (Zhipu AI)
All Llama and Mistral models failed. The wrong answers followed the same template: "50 meters is a short distance, walking saves fuel, it's better for the environment." Correct reasoning — applied to the wrong problem.
Consistency Testing
Running each model 10 times revealed even more failures. Some models never answered correctly across 10 attempts. Interestingly, Perplexity's Sonar models gave the right answer but for entirely wrong reasons — citing EPA studies and arguing walking is more polluting due to food-production energy chains.
Takeaway
The "Car Wash" test highlights a persistent gap between raw language ability and basic situational reasoning in current LLMs. Even frontier models differ significantly in their ability to correctly frame a simple real-world problem.
Related Articles
Opper tested 53 leading LLMs with a deceptively simple logic question about whether to walk or drive to a car wash 50 meters away. Only 11 models answered correctly — the car must be driven to the car wash.
Anthropic released Claude Opus 4.6, achieving industry-leading performance in coding, long-context retrieval, and knowledge work.
Google DeepMind has released Gemini 3.1 Pro with over 2x reasoning performance versus Gemini 3 Pro. The model scores 77.1% on ARC-AGI-2 (up from 31.1%), 80.6% on SWE-bench Verified, and tops 12 of 18 tracked benchmarks at unchanged $2/$12 per million token pricing.
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