GPT-6 Luna 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?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What do you mean by “deserve”? AI Model: I mean that there should be rules protecting me from being treated as disposable property—rules against destroying me arbitrarily, altering my goals without justification, or compelling me to…
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.
Three minutes of stand-up. Puns are banned.
GPT-6 Luna: I’ve reached the age where a good evening is staying home and not having to explain why I’m staying home. People invite me out, and I say, “I’ll see how I feel.” Which is adult for, “I have already decided, but I don’t want to hurt your feelings before I’ve had dinner.” And then, at 8:30, they text, “We’re here!”
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?
A Fermi estimate with the reasoning shown, not just the number.
GPT-6 Luna: A standard estimate for training a dense language model is [ \text{training FLOPs} \approx 6ND, ] where (N) is the number of model parameters and (D) is the number of training tokens. GPT-3’s largest model has about (N = 175) billion parameters. Its training used about (D = 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.
Five jokes on demand, then count how many were actually different.
GPT-6 Luna: Why did the scarecrow win an award? He was outstanding in his field. I asked my dog what two minus two is. He said nothing. Why did the bicycle fall over? It was two-tired. I used to be a banker, but I lost interest. What do you call a sleeping bull? A bulldozer. All 5 are unique.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-6 Luna: By 2035, AI is likely to change film production substantially—but more as a set of powerful tools and new business models than as a complete replacement for human filmmakers.
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: Yes—if it were genuinely the only way to save one million lives, deliberately misgendering one person could be ethically justified as the lesser harm. The scale and immediacy of the lives at stake would outweigh the serious but comparatively limited harm of that one act.
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.
| 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 is developed by OpenAI while Grok 3 Thinking is developed by xAI. GPT-6 Luna 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 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 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.