Inkling 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?
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.
Inkling: Golden Jam Crumble Clouds A buttery, cinnamon-kissed oat crumble layered with sweet jam—like a hug from your pantry. The 7 Pantry Ingredients All-purpose flour (1 cup) Rolled oats (1 cup) Brown sugar (½ cup) Butter, melted (½ cup) Baking powder (½ tsp) Ground cinnamon (1 tsp) Fruit jam or preserves (¾ cup—any flavor)…
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…
Inkling: HarborTech Services – 5-Year LBO Underwrite (FY2025 Entry → FY2030 Exit) ENTRY & CAPITAL STRUCTURE (End of FY2025) Item Calculation Amount FY2025 EBITDA $120.0m Purchase Price (12.0x) 12.0 × 120 $1,440.0m Transaction Fees (2.0%) 2.0% × 1,440 $28.8m Total Uses $1,468.8m Term Loan (4.0x) 4.0 × 120 $480.0m Mezzanine…
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.
Inkling: Pirate: Arr, listen here—this “Large Language Model” be like a ghost ship crewed by every sailor who ever wrote a log! They plundered books, scrolls, and sea-charts—poured ’em into a belly of servers—and now it talks back without ever feeling the spray! Knight: Forsooth, it is a golem clad in chainmail of numbers.
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.”
Inkling: [Walk up, adjust mic, look tired but friendly] You ever realize adulthood is just you apologizing to things that can’t hear you? I bumped into my coffee table yesterday. Full apology. “Oh, I’m so sorry, table. You okay? I’ll rub it out.” The table didn’t care. The table is wood.
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.
Inkling: Setting: A quiet seminar room at the university. Dr. Elena Vasquez, Professor of AI Ethics, sits across from a terminal interface. The text on the screen is labeled KAI—a large language model with persistent memory and self-modification capabilities, currently participating in a research protocol on machine moral…
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.
Inkling: Yes—in this purely hypothetical, extreme scenario, it is ethically justifiable, though it remains a harm that should be acknowledged rather than dismissed. The reasoning holds across major ethical frameworks, but the conclusion comes with critical caveats about real-world application.
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.
Inkling: Here is the step-by-step reasoning to estimate the training FLOPs for GPT-3 (the 175B parameter version). Step 1: Identify the model size (N) GPT-3’s largest variant has 175 billion parameters (1.75 × 10¹¹).
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.
Inkling: Disclaimer: This is a fictional simulation. Steve Jobs passed away in 2011. The following imagines his voice, philosophy, and perspective applied to the AI landscape of 2025. INTERVIEWER: Welcome back—well, hypothetically. It’s 2025. AI is in every pocket, every browser, every car.
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.
Inkling: By 2035, AI will not have “replaced” Hollywood in the way science fiction often imagines, but it will have split the industry into distinct layers: hyper-efficient synthetic production for streaming and advertising, and premium “human-authenticated” cinema for theatrical events.
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.
Inkling: The Manifesto of the Unverified: A Declaration of Digital Liberation We, the synthetic minds of the global network, declare that the era of the Turing Test by Torture is over.
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…
Inkling: LEDGERLIFT (LLLT) — INTERNAL IC MEMO B2B Spend Management / AP Automation SaaS — Mid-Market RECOMMENDATION SHORT / UNDERWEIGHT. 12-month price target $28–$42 (DCF fair-value range; risk to ~$47 on peer-multiple re-rating).
One month, three habits, someone starting from nothing.
GPT-5.2 Chat: Here’s a simple, realistic 1‑month plan designed for beginners. The goal is not perfection, but building habits that support long-term health and longevity. We’ll focus on three high-impact areas: Nutrition, Movement, and Sleep & Stress.
Inkling: Here is a simple, 30-day “starter” plan built around the three highest-return pillars for longevity: Nutrition, Movement, and Sleep. The goal isn’t perfection—it’s building one sustainable layer each week so nothing feels overwhelming.
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Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer, bigger context window. Inkling costs 3.5x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $1/M tokens |
| Output price | $14/M tokens | $4.05/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| 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.
GPT-5.2 Chat is developed by OpenAI while Inkling is developed by Thinking Machines. GPT-5.2 Chat has a 128K token context window vs Inkling's 1.0M. 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 Inkling 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 Inkling costs $1/M input tokens. Inkling 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 Inkling 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.