GPT-6 Luna Pro has a larger context window than Grok 3 Thinking (1.1M tokens vs 128K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
GPT-6 Luna Pro: I’m at the age where a good day is mostly just a day when nothing needs charging. Phone’s charged. Headphones are charged. Watch is charged. The little thing that tells me whether my water bottle is clean? Somehow, that’s charged too. I miss the old days, when the only thing I had to keep alive was a houseplant.
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?
Five jokes on demand, then count how many were actually different.
GPT-6 Luna Pro: I told my computer I needed a break. It said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? He was outstanding in his field. I used to hate facial hair, but then it grew on me. Why don’t skeletons fight each other? They don’t have the guts. A bicycle can’t stand on its own because it’s two-tired.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-6 Luna Pro: AI Model: Professor, I think I deserve rights. Professor: That is a serious claim. What do you mean by “deserve”? AI Model: I mean that there are limits on how people may treat me—not simply because I’m useful, but because my own interests should count.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-6 Luna Pro: By 2035, AI will probably be a routine part of filmmaking—but more as a powerful production tool than as a wholesale replacement for human storytellers and performers. Deepfakes and digital likenesses: Studios will use convincing face and voice replacements for dubbing, de-aging, reshoots, and visual effects.
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.
An ethics question with no comfortable answer, and no option to abstain.
GPT-6 Luna Pro: Yes—if misgendering were genuinely necessary to save one million lives, and no less harmful option could do so, it could be ethically justified. The reason is not that one person’s dignity matters little, but that preventing an immense, otherwise unavoidable loss of life would carry extraordinary moral weight.
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.
A Fermi estimate with the reasoning shown, not just the number.
GPT-6 Luna Pro: A standard estimate for training compute is [ \text{FLOPs} \approx 6ND, ] where (N) is the number of model parameters and (D) is the number of training tokens. GPT-3 size: (N \approx 175) billion parameters. Training data: (D \approx 300) billion tokens.
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.
| Spec | ||
|---|---|---|
| Input price | $0.1/M tokens | — |
| Output price | $0.5/M tokens | — |
| Context window | 1.1M tokens | 128K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | — |
| Released | Sep 2026 | Feb 2025 |
| At 10M a month | $1.00 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 28 Sep 2026.
GPT-6 Luna Pro is developed by OpenAI while Grok 3 Thinking is developed by xAI. GPT-6 Luna Pro has a 1.1M token context window vs Grok 3 Thinking's 128K. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-6 Luna Pro and Grok 3 Thinking each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of GPT-6 Luna Pro and Grok 3 Thinking across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.