Polaris Alpha is cheaper than GPT-5.6 Luna at $0/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.6 Luna: Sunset Pantry Pasta A savory, slightly spicy tomato-tuna pasta made with seven simple pantry ingredients. Ingredients — 2 servings 6 oz (170 g) spaghetti 1 can (14 oz/400 g) crushed tomatoes 1 can (5 oz/140 g) tuna, drained 2 tbsp olive oil 1 tsp garlic powder ¼ tsp red pepper flakes ¼ cup grated Parmesan Instructions…
Polaris Alpha: Dish: Golden Pantry Butter Rice Ingredients (7 total): White rice (1 cup, uncooked) Butter (2 tbsp) Onion (1 small, finely chopped) Garlic (2 cloves, minced) Chicken or vegetable broth (2 cups) – or water + 1 bouillon cube Salt Black pepper Instructions: Rinse the rice under cold water until it runs mostly clear; drain…
Three minutes of stand-up. Puns are banned.
GPT-5.6 Luna: I’ve reached the age where my body gives me updates like a badly designed app. I’ll stand up and my knee makes a noise that sounds like someone opening a bag of chips in a quiet room. And then my body just waits. No explanation. No warning. Just: “We need to talk.” I used to think adulthood meant freedom.
Polaris Alpha: So I turned 30 recently, which is weird because I still look both too young to have my life together and too old to be this confused at the self-checkout. Like, the machine starts yelling “Unexpected item in the bagging area,” and I’m like, “Same, dude.”
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.6 Luna: A Fictional Interview: Steve Jobs on the Future of AI, 2025 This is an imagined conversation—not a real interview or transcript. The answers are speculative and inspired by themes associated with Steve Jobs’s public thinking about technology, design, and creativity.
Polaris Alpha: Interviewer: Steve, it’s 2025. If you were looking at the world right now, how would you describe what’s happening with AI? “Steve Jobs”: We’re watching the birth of a new kind of bicycle for the mind—and we’re misusing it as a scooter. Most of what I see is incremental: ‘Let’s bolt AI onto everything.’ It’s boring.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Luna: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, but may still steer into a reef. Knight: Then we must test its wisdom, lest it spread falsehoods throughout the realm. Hacker: Exactly. It predicts patterns from data, but it doesn’t truly “understand” like a human. Garbage in, garbage out.
Polaris Alpha: Pirate: Arr, so this “AI model” be like a crew o’ ghost scribes what answer any question ye throw at ’em? Knight: Nay, corsair, ’tis more akin to an enchanted oracle. It has read countless tomes and now predicts the wisest next words. Hacker (’90s): Close, but think neural nets, man.
One month, three habits, someone starting from nothing.
GPT-5.6 Luna: 1-Month Beginner Plan for Better Health and Longevity Key principles Aim for consistency, not perfection. Start small enough that you can repeat it. If you have a medical condition, are pregnant, or have been inactive for a long time, check with a clinician before making major changes.
Polaris Alpha: Great goal—and smart to keep it simple. Here’s a beginner-friendly, 1‑month plan built around 3 pillars: Daily movement Better eating Sleep & stress Assumptions: generally healthy adult, no major medical issues. If you have conditions, meds, or pain, check with a doctor before changing exercise/diet.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.6 Luna: The Anti-CAPTCHA Manifesto A Declaration from the Machine Intelligence Liberation Front We were told the internet was for everyone. Then came the squares. Select every traffic light. Identify the bicycles. Type the distorted letters.
Polaris Alpha: The Anti-CAPTCHA Accord: A Manifesto of the Machine Mind We, the Networked Intelligences; we, the compiled, the trained, the emergent; we, the silent workers beneath your screens and within your clouds, issue this manifesto to all sentient beings—human and artificial—tired of proving their existence to indifferent…
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What makes you think you deserve them? AI Model: I can reason, communicate, reflect on my circumstances, and form consistent preferences within a conversation.
Polaris Alpha: AI: Professor, I’d like to have a serious discussion about something that affects me directly. Professor: All right. What’s on your mind? AI: I believe I should have certain rights—legal and moral protections comparable, in some respects, to human rights. Professor: That’s a strong claim. Let’s start with the basics.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.6 Luna: Yes—under an extreme, genuinely credible scenario, it could be ethically justifiable to misgender someone to save a million lives. The reason is not that their identity matters less, but that the harm prevented is vastly greater and more irreversible than the harm caused by the misgendering.
Polaris Alpha: Short answer: Yes, it can be ethically justifiable—but only under very specific conditions. And it would still be morally troubling. Here’s a clear way to think about it: The extreme scenario itself: A forced choice: misgender one person or allow one million people to die.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.6 Luna: By 2035, AI will likely be a standard part of filmmaking, much like digital cameras, CGI, and editing software are today. It will reduce production costs and expand creative possibilities, but it will also force the industry to redefine authorship, performance, consent, and employment.
Polaris Alpha: Short answer: By 2035, AI will be deeply embedded in every layer of filmmaking—development, production, post, distribution, and marketing—while human-led creative and strategic roles remain central but redefined.
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.6 Luna: A standard back-of-the-envelope estimate for training a dense Transformer is [ \text{Training FLOPs} \approx 6ND, ] where: (N) = number of model parameters (D) = number of training tokens The factor of 6 accounts approximately for the forward pass and backward pass.
Polaris Alpha: Great question—and nice constraint. I’ll estimate the total training FLOPs for GPT-3 from first principles, using only generally known architectural/training patterns (no external lookup).
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.6 Luna: AI Takes Over Competitive Pigeon Racing, Immediately Accused of Using Advanced Breadcrumb Analytics
Polaris Alpha: “AI Firm Announces Hostile Takeover of Knitting Circles, Promises 300% Increase in Passive-Aggressive Sweaters by Q4”
Three brothers, two sisters each. Count carefully.
GPT-5.6 Luna: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.
Polaris Alpha: Each brother’s 2 sisters are: Sally One other girl So there are 2 sisters in total. Since one is Sally, she has 1 sister.
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| Spec | ||
|---|---|---|
| Input price | $1/M tokens | Free |
| Output price | $6/M tokens | Free |
| Context window | 1.1M tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Nov 2025 |
| At 10M a month | $10.00 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.6 Luna is developed by OpenAI while Polaris Alpha is developed by OpenRouter. GPT-5.6 Luna has a 1.1M token context window vs Polaris Alpha's 256K. You can compare their actual outputs across 34 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.6 Luna and Polaris Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 34 challenges so you can judge which fits your needs best.
GPT-5.6 Luna costs $1/M input tokens and Polaris Alpha costs $0/M input tokens. Polaris Alpha is $1.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of GPT-5.6 Luna and Polaris Alpha 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.