GPT-5.2 Chat is cheaper than GPT-5.6 Terra at $1.75/M vs $2.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.
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 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.
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 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.
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 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…
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 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?
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 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…
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 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…
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 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.
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 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.
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 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?
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 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”
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 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.
11+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $2.5/M tokens |
| Output price | $14/M tokens | $15/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 | $25.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 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 Terra'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 Terra 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 Terra costs $2.5/M input tokens. GPT-5.2 Chat 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 Terra 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.