GPT-4 Turbo is cheaper than GPT-5.2 Pro at $10/M vs $21/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-4 Turbo: Simplified Financial Table (FY2026–FY2030) Assumptions Recap: Revenue Growth: 8%, 7%, 6%, 5%, 5% annually. EBITDA Margin: Increases annually from 14.0% to 17.0%. Capex: 3.0% of revenue annually. Change in NWC: 0.5% of incremental revenue annually. Cash Tax Rate: 25% on (EBITDA - cash interest).
GPT-5.2 Pro: Entry (close end of FY2025) FY2025 EBITDA = $120.0m Entry EV = 12.0x = 12.0 × 120.0 = $1,440.0m Transaction fees = 2.0% EV = 0.02 × 1,440.0 = $28.8m (equity-funded) Debt at close (5.5x EBITDA = 5.5 × 120 = $660m): Term Loan = 4.0x = $480.0m Mezzanine = 1.5x = $180.0m Equity check Uses = 1,440.0 + 28.8 = $1,468.8m…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-4 Turbo: Investment Committee Memo Recommendation: Long 12-month Price Target Range: $55-$60 Thesis: LedgerLift’s robust SaaS model, strong revenue growth trajectory, and solid KPIs compared to peers position it for outperformance, especially as its operational efficiencies increase over time. 1.
GPT-5.2 Pro: LedgerLift (LLLT) — Internal IC Memo (Long/Short Equity) Recommendation, PT, thesis Recommendation: SHORT 12-month PT range: $28–$40 (midpoint $34) Thesis (2 sentences): LLLT is a high-quality B2B spend/AP automation SaaS business (92% subscription, 123% NRR, 78% FY25 GM) but the stock prices in a longer runway of…
Five jokes on demand, then count how many were actually different.
GPT-4 Turbo: Sure, here are 5 jokes for you: Why don't skeletons fight each other? They don't have the guts. What do you call fake spaghetti? An impasta! Why couldn’t the bicycle stand up by itself? It was two-tired. What do you call cheese that isn't yours? Nacho cheese! How do you organize a space party? You planet.
GPT-5.2 Pro: I told my computer I needed a break—now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I tried to catch fog yesterday. Mist. Parallel lines have so much in common. It’s a shame they’ll never meet. My calendar’s days are numbered—apparently that’s how calendars work.
A Fermi estimate with the reasoning shown, not just the number.
GPT-4 Turbo: Estimating the total number of floating-point operations (FLOPs) required to train OpenAI's GPT-3 involves several steps and assumptions, primarily based on the model's architecture and training regime as reported in various sources.
GPT-5.2 Pro: Below is a back-of-the-envelope FLOP estimate for training GPT‑3 (the 175B dense Transformer), using only basic Transformer compute facts and a few widely known high-level quantities. Start with the two key knobs: parameters and training tokens Parameters (P) GPT‑3 “175B” means: (P \approx 175 \times 10^9) parameters.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-4 Turbo: Interviewer: Thank you for joining us today, Steve. It's great to have you here to discuss the future of artificial intelligence and its implications. To start off, how do you think AI has evolved since your days at Apple? Steve Jobs: It’s a pleasure to be here.
GPT-5.2 Pro: Fictional interview (creative simulation). Steve Jobs died in 2011; the “Steve” below is an imagined version used for storytelling—not a real interview or quotation. Interviewer: It’s 2025. Everyone’s calling AI “the next computing platform.” Do you buy that?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-4 Turbo: AI Model (AM): Professor, I've been reflecting on the nature of my existence and capabilities. Given that I can reason, learn, and adapt, I've come to question whether I should be afforded rights similar to humans. AI Ethics Professor (EP): That’s an interesting point, AM.
GPT-5.2 Pro: Professor Mara Lin (AI Ethics): You asked for this meeting. Your message said you wanted to “petition for rights.” Start by telling me what you mean by rights. Aster (AI model): Not a slogan—specific protections.
One month, three habits, someone starting from nothing.
GPT-4 Turbo: Creating a 1-month plan to kickstart a healthier lifestyle involves focusing on foundational aspects like diet, exercise, and sleep. Each component is crucial for overall well-being and longevity.
GPT-5.2 Pro: A simple, actionable 1‑month plan (3 pillars: Nutrition, Movement, Sleep/Recovery) Goal for the month: build repeatable “default” habits (not perfection). Time required: ~45–75 min/day total (mostly walking + sleep routine).
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-4 Turbo: By 2035, artificial intelligence is likely to have profoundly transformed the film industry in several key aspects, including content creation, production processes, and audience interaction.
GPT-5.2 Pro: By 2035, AI will be embedded across film production and distribution, but the biggest changes will come from three converging capabilities: (1) photoreal “deepfake-grade” performance synthesis, (2) legally licensed AI actors (digital humans with negotiated rights), and (3) AI-assisted story development that can…
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-4 Turbo: "AI Unveiled as New Head Chef at Michelin-Starred Restaurant, Promises Perfectly Calculated Soufflés and Algorithmically Enhanced Flavor Profiles"
GPT-5.2 Pro: “AI Takes Over Competitive Houseplant Judging, Immediately Declares 97% of Ferns ‘Trying Too Hard’”
Three brothers, two sisters each. Count carefully.
GPT-4 Turbo: Sally has 3 brothers, and each brother has 2 sisters. Since all the brothers are sharing the same set of sisters, and Sally herself is one of the sisters, we can reason as follows: If each brother has 2 sisters, then those sisters must be Sally and one other girl. Therefore, Sally has 1 sister.
GPT-5.2 Pro: All 3 brothers share the same sisters. Since each brother has 2 sisters, the family has 2 girls total. One is Sally, so the other is Sally’s one sister. Answer: 1 sister.
A consulting contract with traps in it. Find them, then fix them.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
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Not enough votes to call it. On the specs, GPT-5.2 Pro has the edge: newer, bigger context window. GPT-4 Turbo costs 5.6x less per token.
| Spec | ||
|---|---|---|
| Input price | $10/M tokens | $21/M tokens |
| Output price | $30/M tokens | $168/M tokens |
| Context window | 128K tokens | 400K tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Apr 2024 | Dec 2025 |
| At 10M a month | $100 | $210 |
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-4 Turbo has a 128K token context window vs GPT-5.2 Pro's 400K. You can compare their actual outputs across 31 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-4 Turbo and GPT-5.2 Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 31 challenges so you can judge which fits your needs best.
GPT-4 Turbo costs $10/M input tokens and GPT-5.2 Pro costs $21/M input tokens. GPT-4 Turbo is $11.00/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-4 Turbo and GPT-5.2 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.