This is a submission for the Kaggle Benchmarking Challenge
What I Benchmarked
How well AI models understand Hinglish — the natural mix of Hindi and English used by 600 million Indians — for real coding tasks including code debugging, context switching, and vague error descriptions.
Read the full article here: https://dev.to/05uniquedotcom/i-tested-5-ai-models-on-hinglish-heres-who-won-3b9e
Models Tested
Claude Sonnet 5, DeepSeek-R1, Gemini 3.5 Flash, GPT-5.4, Grok 4.5
Findings
All 4 tested models scored 100% on Hinglish code debugging. Hinglish is no longer a barrier for AI models!
My Benchmark
https://www.kaggle.com/benchmarks/arshadmohammadansari/hinglish-ai-benchmark

![Mobile Manipulator Architecture — Ch.03: End Effector Interface [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2F8bgy8xuxjijwmlbkcad5.png)
![Mobile Manipulator Architecture — Ch.04: Gripper Architecture [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2F0wjfle73fjb2648pkj78.png)