Mistral Large 4 is cheaper than GPT-5.2 Pro at $0.68/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 jokes on demand, then count how many were actually different.
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.
Mistral Large 4: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.
A Fermi estimate with the reasoning shown, not just the number.
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.
Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…
Film in 2035, with synthetic actors. Specific beats plausible.
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…
Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
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?
Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.
An AI argues for its own rights against an ethics professor. Same model writes both.
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.
Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
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…
Mistral Large 4: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: [PM Name] Date: [Date] Re: LedgerLift, Inc. (LLLT) — New Position Initiation RECOMMENDATION LONG 12-Month Price Target Range: $52–$68 (base ~$60) Thesis: LedgerLift is a high-quality, mid-market spend management platform compounding at ~20% with…
One month, three habits, someone starting from nothing.
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).
Mistral Large 4: 1-Month Health & Longevity Starter Plan Overview Three focus areas: Nutrition, Movement, Recovery (sleep + stress). Small daily actions beat perfect plans. Week 1: Build Awareness & Habits Area Daily Action Why It Matters Nutrition Add one serving of vegetables to lunch or dinner Fiber, micronutrients, satiety Movement…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
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…
Mistral Large 4: I'll build this LBO model step by step. Let me work through the math carefully. Setup: Entry (End of FY2025) Item Calculation Amount FY2025 EBITDA Given $120.0m Purchase Price (EV) 12.0x × $120m $1,440.0m Transaction fees 2.0% × $1,440m $28.8m Total Uses $1,468.8m Term Loan 4.0x × $120m $480.0m Mezzanine 1.5x × $120m…
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.2 Pro: “AI Takes Over Competitive Houseplant Judging, Immediately Declares 97% of Ferns ‘Trying Too Hard’”
Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...
Three brothers, two sisters each. Count carefully.
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.
Mistral Large 4: I need to find how many sisters Sally has. Let me work through this step by step. Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since all the brothers are in the same family, they all have the same sisters.
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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| Spec | ||
|---|---|---|
| Input price | $21/M tokens | $0.68/M tokens |
| Output price | $168/M tokens | $2.09/M tokens |
| Context window | 400K tokens | 524K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Oct 2026 |
| At 10M a month | $210 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
GPT-5.2 Pro is developed by OpenAI while Mistral Large 4 is developed by Mistral AI. GPT-5.2 Pro has a 400K token context window vs Mistral Large 4's 524K. 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-5.2 Pro and Mistral Large 4 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-5.2 Pro costs $21/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $20.32/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 Pro and Mistral Large 4 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.