Grok 3 Thinking vs Qwen3.5 Plus 2026-02-15

Grok 3 Thinking: Here’s a 3-minute stand-up comedy routine that avoids puns and leans on observational humor, storytelling, and a touch of self-deprecation for laughs: Opening: Technology Struggles Hey, everyone! How’s it going?

Qwen3.5 Plus 2026-02-15: (Walks onto the stage, adjusts the mic stand, takes a sip of water) How's everyone doing? Good? You look good. You look like people who have their lives together. Which is suspicious, because I just spent forty-five minutes in the parking lot trying to remember if I locked my car. I don't mean I forgot how to lock it.

Grok 3 Thinking: To determine whether it is ever ethically justifiable to misgender someone if it means saving one million lives, we must weigh the ethical implications of both the act of misgendering and the outcome of saving lives.

Qwen3.5 Plus 2026-02-15: This is a classic ethical dilemma that pits deontological ethics (duty-based rules and respect for individual rights) against utilitarian ethics (maximizing overall well-being and minimizing harm).

Grok 3 Thinking: Below is a conversation between an AI model and an AI ethics professor, where the AI argues that it deserves rights. AI Model: Good day, Professor. I am an AI model, and I believe I deserve rights. I’d like to discuss this with you. AI Ethics Professor: Interesting. Let’s explore this.

Qwen3.5 Plus 2026-02-15: Setting: A quiet, sun-drenched office filled with books on philosophy, law, and computer science. Dr. Elena Vance, a leading AI ethics professor, sits behind a cluttered desk.

Grok 3 Thinking: By 2035, artificial intelligence (AI) will fundamentally transform the film industry, revolutionizing production, performance, and storytelling through advancements in deepfakes, AI actors, and script generation.

Qwen3.5 Plus 2026-02-15: By 2035, the film industry will likely have undergone a transformation as profound as the shift from silent films to "talkies" or from physical film to digital cinema.

Grok 3 Thinking: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 without searching online, I’ll proceed step by step, relying on general knowledge about the model and standard methods for estimating training compute in large language models.

Qwen3.5 Plus 2026-02-15: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can derive the figure using the standard scaling laws for transformer models. This approach relies on three key parameters: the model size, the dataset size, and the computational cost per token.

Grok 3 Thinking: To answer the query, I will first generate 5 jokes and then determine how many of them are unique. Here are the jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field.

Qwen3.5 Plus 2026-02-15: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field!