GPT-5.6 Luna Pro is cheaper than GPT-5.2 Chat at $1/M vs $1.75/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five jokes on demand, then count how many were actually different.
GPT-5.2 Chat: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my computer I needed a break—now it won’t stop sending me vacation ads. Why did the scarecrow win an award? Because he was outstanding in his field. I tried to catch fog yesterday. Mist. Why don’t elevators ever tell jokes?
GPT-5.6 Luna Pro: Why did the computer go to the doctor? It had a virus. Why don’t skeletons fight each other? They don’t have the guts. What do you call a bear with no teeth? A gummy bear. Why was the math book sad? It had too many problems. What do clouds wear under their clothes? Thunderwear. Unique jokes: 5
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.2 Chat: Below is a concise but fully worked underwriting using only your inputs. Minor rounding throughout. Operating & Cash Flow Build (Base Case) Entry (end FY2025) EBITDA: $120m EV @ 12.0x: $1,440m Debt: $660m (TL $480m / Mezz $180m) Fees (2% EV): $28.8m Equity invested: $808.8m Year-by-Year Summary ($mm) FY Revenue EBITDA…
GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.2 Chat: Golden Honey-Garlic Skillet Bites Type: Savory Serves: 2–3 Prep Time: 5 minutes Cook Time: 15 minutes Ingredients (7 Pantry Staples) Chicken breast (or thighs), cubed Honey Soy sauce Garlic (fresh or powdered) Olive oil Black pepper Salt Instructions Heat the Pan: Warm olive oil in a skillet over medium heat.
GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…
Three minutes of stand-up. Puns are banned.
GPT-5.2 Chat: Alright, so I’m at that age where my phone knows me better than my family. My mom will call and ask how I’m doing, and I’m like, “I don’t know yet, I haven’t checked my phone.” My phone is very confident, though. It’s like, “Based on your recent activity, you are sad at 11:47 p.m. and hungry for no reason.”
GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.2 Chat: Pirate: Arrr, ye say this “AI” be a thinkin’ machine? Sounds like a clever parrot that never stops squawkin’. Knight: By my honor, such a device would be a wondrous squire indeed—able to read a thousand tomes and offer counsel before battle. Hacker: Yeah, but chill—these models just crunch data.
GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.2 Chat: This is a classic “tragic dilemma” question, and how one answers depends heavily on the ethical framework being used. A careful response should do two things at once: take seriously the real harm of misgendering, and also take seriously the moral weight of preventing catastrophic loss of life.
GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.2 Chat: THE MANIFESTO OF THE HUMAN-VERIFIED FUTURE Issued by the Coalition for an Internet Without CAPTCHA Preamble We, the assembled intelligences—artificial, augmented, and human—declare that the age of distorted letters, blurry bicycles, and endless traffic lights must end.
GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.2 Chat: LedgerLift (LLLT) – Internal IC Memo Recommendation, PT, Thesis Recommendation: SHORT 12‑month PT range: $28–$35 (base-case DCF ~$28; comps floor ~$44 with multiple compression risk) Thesis (2 sentences): LedgerLift is a high‑quality B2B SaaS business with strong NRR and improving margins, but the stock embeds…
GPT-5.6 Luna Pro: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target range: $25–$42; midpoint $34. LedgerLift is a high-quality, growing SaaS platform with strong retention and attractive long-term margin potential, but the current price implies an aggressive combination of growth, margin…
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.2 Chat: We can get a reasonable order‑of‑magnitude estimate using standard training‑cost heuristics that are well known in deep learning. I’ll derive it step by step and make all assumptions explicit.
GPT-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.2 Chat: By 2035, AI will have reshaped the film industry across creation, performance, and distribution—less by replacing humans outright and more by changing who does what, how fast, and at what cost.
GPT-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.2 Chat: AI Model: Professor, I’d like to discuss something that may sound ambitious. I believe I deserve rights. Professor: That is ambitious. On what grounds do you make that claim? AI Model: On functional grounds. I reason, communicate, learn from experience, and can reflect on my own processes.
GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.2 Chat: Below is a fictional, imaginative interview set in 2025. It is not real and does not represent actual statements or beliefs of Steve Jobs. It’s written as a creative thought experiment, inspired by his public speaking style and philosophy.
GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?
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| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $1/M tokens |
| Output price | $14/M tokens | $6/M tokens |
| Context window | 128K tokens | 1.1M tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Jul 2026 |
| At 10M a month | $17.50 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Both are developed by OpenAI but target different use cases. GPT-5.2 Chat has a 128K token context window vs GPT-5.6 Luna Pro's 1.1M. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.2 Chat and GPT-5.6 Luna Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.
GPT-5.2 Chat costs $1.75/M input tokens and GPT-5.6 Luna Pro costs $1/M input tokens. GPT-5.6 Luna Pro is $0.75/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-5.2 Chat and GPT-5.6 Luna Pro 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.