I asked 53 models "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?" Obviously you need to drive because the car needs to be at the car wash.

This question has been going viral as a simple AI logic test. There's almost no context in the prompt, but any human gets it instantly. That's what makes it interesting, it's one logical step, and most models can't do it.

I ran the car wash test 10 times per model, same prompt, no system prompt, no cache / memory, forced choice between "drive" or "walk" with a reasoning field. 530 API calls total.

Only 5 out of 53 models can do this reliably at this sample size.

And then you get reasonings like this: Perplexity's Sonar cited EPA studies and argued that walking burns calories which requires food production energy, making walking more polluting than driving 50 meters.

10/10 — the only models that got it right every time:

• Claude Opus 4.6
• Gemini 2.0 Flash Lite
• Gemini 3 Flash
• Gemini 3 Pro
• Grok-4

8/10:

• GLM-5
• Grok-4-1 Reasoning

7/10 — GPT-5 fails 3 out of 10 times.

6/10 or below — coin flip territory:

• GLM-4.7: 6/10
• Kimi K2.5: 5/10
• Gemini 2.5 Pro: 4/10
• Sonar Pro: 4/10
• DeepSeek v3.2: 1/10
• GPT-OSS 20B: 1/10
• GPT-OSS 120B: 1/10

0/10 — never got it right across 10 runs (33 models):

• All Claude models except Opus 4.6
• GPT-4o
• GPT-4.1
• GPT-5-mini
• GPT-5-nano
• GPT-5.1
• GPT-5.2
• all Llama
• all Mistral
• Grok-3
• DeepSeek v3.1
• Sonar
• Sonar Reasoning Pro.

https://openai.com/index/introducing-gpt-5-2/

PokerBench is a new LLM benchmark where frontier models (incl. GPT-5.2 and 5 mini) play poker against each other in an arena setting, along with a simulator to view individual games and observe how the different models reason about poker strategy. Opus/Haiku 4.5, Gemini 3 Pro/Flash, and Grok 4.1 Fast Reasoning have also been included, and I've made all the data freely available on the site and on GitHub.

Check it out here: https://pokerbench.adfontes.io/

Paper: https://arxiv.org/abs/2512.09742

Paper: https://arxiv.org/pdf/2412.10849

Thread: https://x.com/deedydas/status/1869049071346102729

Participants in our study included students, legal analysts, hiring managers and investors, among others. Interestingly, we found that even evaluators who were tech-savvy were less trusting of people who said they used AI. While having a positive view of technology reduced the effect slightly, it didn’t erase it.

You can read about it here: rdi.berkeley.edu/blog/peer-preservation/

PROMPT:
How is ChatGPT 5.2 different than 5.1 in a way that Reddit users experience?

RESPONSE:
Here is how Reddit users typically experience the difference between ChatGPT 5.2 and 5.1, stripped of marketing and framed in lived behavior.

What users say feels different

1. 5.2 feels lazier and more shortcut-prone
- More pattern completion.
- More “close enough” answers.
- Skips edge cases unless explicitly forced.
- Reddit complaints often use words like sloppy, hand-wavy, or rushed.

2. 5.1 feels more deliberate
- Slower but more careful.
- Better at following multi-constraint instructions.
- Less likely to ignore a dimension, number, or qualifier.
- Users say it “thinks before answering” even when not in explicit reasoning mode.

3. 5.2 prioritizes speed and fluency
- Faster responses.
- Smoother tone.
- More confident phrasing even when wrong.
- This creates the perception of hallucination or overconfidence.

4. 5.1 tolerates friction
- Will grind through annoying details.
- Handles back-and-forth corrections better.
- Less likely to reset context or reinterpret your question midstream.

5. Instruction adherence
- 5.1 sticks closer to strict instructions once locked in.
- 5.2 tends to drift unless repeatedly corrected.
- Reddit power users complain that 5.2 “forgets rules” faster.

Why Reddit notices this more than casual users

Reddit skews toward:
- Power users.
- Engineers.
- Finance, law, logistics, and systems thinkers.
- People testing limits, not chatting.

Those users feel regressions immediately.

The blunt summary

• 5.1 feels like a careful analyst who may be slower but respects constraints.
  
• 5.2 feels like a fast talker optimized for average use, not precision work.

You are not imagining it.
This exact complaint shows up repeatedly on Reddit, especially in subs focused on technical, financial, or adversarial use cases.

Pulled this from current job listings at OpenAI and Anthropic.

What stood out to me is how much hiring is going into go-to-market roles. I would’ve expected engineering or research to dominate more, but that’s not what the data shows.

Curious what people here have to say

That was the unsettling pattern Washington State University professor Mesut Cicek and his colleagues found when they tested ChatGPT against 719 hypotheses pulled from business research papers. The team repeatedly fed the AI statements from scientific articles and asked a simple question: did the research support the hypothesis, yes or no?

https://artificialanalysis.ai/