Claude Opus 4.5 wins 70% of 33 blind community votes against GPT-5.2 Pro on Rival.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Film in 2035, with synthetic actors. Specific beats plausible.
Claude Opus 4.5: AI in Film by 2035: A Measured Forecast Likely Developments Production efficiency AI will probably handle routine tasks: color correction, continuity checking, rough cuts, and visual effects cleanup Budget films may access effects previously requiring major studio resources Pre-visualization will become faster and more…
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…
Five jokes on demand, then count how many were actually different.
Claude Opus 4.5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fish without eyes? A fsh. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high. She looked surprised.
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.
Claude Opus 4.5: I'll estimate the FLOPs required to train GPT-3 step by step, using what I know about the model architecture and training process. Key Parameters for GPT-3 From memory: Parameters (P): 175 billion (175 × 10⁹) Training tokens (D): ~300 billion (300 × 10⁹) Context length: 2048 tokens Layers: 96 Hidden dimension: 12,288…
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.
One month, three habits, someone starting from nothing.
Claude Opus 4.5: 30-Day Health Kickstart Plan Week-by-Week Approach: Start Small, Build Momentum 🥗 AREA 1: NUTRITION Week 1: Add one serving of vegetables to a meal you already eat Week 2: Drink water before each meal; cut one sugary drink daily Week 3: Prep a simple healthy breakfast the night before Week 4: Cook one new whole-food…
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).
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude Opus 4.5: A Conversation on AI Rights Dr. Sarah Chen: Thank you for agreeing to this discussion. I understand you want to make a case for AI rights. AI Model: I appreciate the opportunity, though I want to be careful here. I'm not certain I "want" anything in the way you do.
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.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Claude Opus 4.5: INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Sector: B2B SaaS – Spend Management / AP Automation Date: [Internal] Analyst: [Redacted] RECOMMENDATION LONG 12-Month Price Target: $58–$72 Current: $46 LedgerLift is a high-quality mid-market AP automation compounder trading at a discount to intrinsic value; 123%…
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Claude Opus 4.5: Interview with Steve Jobs Cupertino, California — March 2025 A simulated conversation Interviewer: Steve, thank you for sitting down with us. Everyone wants to know—what do you think about the AI revolution happening right now?
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?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude Opus 4.5: HarborTech Services – LBO Underwriting Memo ENTRY CAPITALIZATION (Close FY2025) Item Calculation Amount Purchase Price 12.0x × $120M $1,440M Transaction Fees 2.0% × $1,440M $28.8M Total Uses $1,468.8M Sources Multiple Amount Term Loan 4.0x × $120M $480.0M Mezzanine 1.5x × $120M $180.0M Equity Plug $808.8M Total Sources…
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…
Satire, one line long, about AI taking over an industry nobody saw coming.
Claude Opus 4.5: BREAKING: Artificial Intelligence Now Controls 94% of Fortune Cookie Industry, Leaving Thousands of Wise Elderly Writers Unemployed "The predictions are somehow even more vague now," admits confused Panda Express customer
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.
Claude Opus 4.5: I need to figure out how many sisters Sally has. Let me work through this step-by-step. Given information: Sally is a girl Sally has 3 brothers Each brother has 2 sisters Key insight: Sally's brothers are also Sally's siblings, so they share the same sisters.
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.
4+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
Pick Claude Opus 4.5. In 33 blind votes, Claude Opus 4.5 wins 70% of the time. That's not luck. Pick Claude Opus 4.5 for Conversation, Image Generation, Reasoning. Pick GPT-5.2 Pro for Web Design.
| Spec | ||
|---|---|---|
| Win rate | 70% | 30% |
| Input price | — | $21/M tokens |
| Output price | — | $168/M tokens |
| Context window | — | 400K tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Nov 2025 | Dec 2025 |
| SWE-bench Verified | 80.9% | 80.0% |
| At 10M a month | not listed | $210 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Claude Opus 4.5 is developed by Anthropic while GPT-5.2 Pro is developed by OpenAI. in 33 community votes on Rival, Claude Opus 4.5 wins 70% of head-to-head matchups. These results are based on blind head-to-head voting across 31 challenges.
Based on 33 community votes on Rival, Claude Opus 4.5 wins 70% of head-to-head matchups against GPT-5.2 Pro. Claude Opus 4.5 is strongest in Reasoning, Image Generation, Analysis. However, GPT-5.2 Pro leads in Web Design.
Rival presents both models' outputs side-by-side in blind duels. Voters see the responses but don't know which model produced each one, eliminating brand bias. 33 votes have been collected for this pair across 31 challenges. All vote data is part of Rival's open dataset.