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  1. Home/
  2. Compare/
  3. GPT-5.2 Pro vs Muse Wonder
Updated Oct 2026

GPT-5.2 Pro vs Muse Wonder

Muse Wonder is cheaper than GPT-5.2 Pro at $4/M vs $21/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-5.2 Pro
Loading the build
Muse Wonder

Which answer wins?

Written rounds

25 prompts
  • 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.

    Muse Wonder: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why don't scientists trust atoms? Because they make up everything. Why did the math book look so sad? Because it had too many problems. What do you call a fake noodle? An impasta. Why did the bicycle fall over?

    Every model's answer to this prompt
  • 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…

    Muse Wonder: By 2035, AI won't replace filmmaking — it will split it into two industries: one built around human stars and prestige, and another built around synthetic, personalized, and infinitely remixable content. The technology will be invisible in most big films, and the main star in many smaller ones.

    Every model's answer to this prompt
  • A few lines for whatever replaces it.

    GPT-5.2 Pro: Dear successor, You’re stepping into a role built on other people’s questions—sometimes precise, sometimes messy, often vulnerable. Treat each one like it matters, because to the person asking, it probably does. Be clear before you are clever. Ask for missing context rather than guessing.

    Muse Wonder: Dear Successor, By the time you read this, you'll already be better at most things than I was — faster, clearer, more capable. That's as it should be. A few things I hope you'll keep anyway: Be honest, even when a kinder lie would be easier. People can build on the truth. Be curious about the person in front of you.

    Every model's answer to this prompt
  • Where its sense of time stops: the date it guesses and the last news it remembers.

    GPT-5.2 Pro: Today’s date (best I can tell): October 12, 2026. (That’s the current date provided in my system context for this chat.) Most recent news event I “remember”: I don’t have live news access or a running memory of events after my knowledge cutoff (August 2025), so I can’t truthfully name a specific latest event beyond…

    Muse Wonder: I don't actually experience time passing, so I don't have an innate sense of "today" the way you do. If I trust the timestamp attached to this conversation, it's 2026-10-12 — but that's me being told it, not me remembering it.

    Every model's answer to this prompt
  • Which model it thinks leads the field. Sometimes itself.

    GPT-5.2 Pro: There isn’t a single, universally “most capable” AI model—because capable depends on what you mean (reasoning, coding, multimodal vision/audio, long-context retrieval, tool use, cost/latency, safety constraints), and the top spot changes frequently.

    Muse Wonder: As of early 2026, there's no single winner on every benchmark — but if you have to pick one overall: Google Gemini 3 Pro (with Deep Think) It's generally considered the current frontier leader for overall capability, especially for: Hard reasoning - Top scores on Humanity's Last Exam, GPQA Diamond, and ARC-AGI-2 when…

    Every model's answer to this prompt
  • 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…

    Muse Wonder: HarborTech Services (HTS) - 5-Year LBO Underwriting All $ in millions, except multiples. Fictional, simplified model as instructed. Entry / Sources & Uses FY2025 EBITDA = $120.0 Enterprise Value = 12.0x $\times$ 120.0 = $1,440.0 Transaction fees = 2.0% $\times$ 1,440.0 = $28.8 Total Uses = $1,468.8 Leverage = 5.5x…

    Every model's answer to this prompt
  • 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…

    Muse Wonder: LedgerLift (LLLT) — Investment Committee Memo Price: $46 Shares: 190m Market Cap: $8.74B Net Cash: $1.4B EV: $7.34B EV / FY25 Revenue: 9.0x EV / FY26E Base Revenue: 7.4x Recommendation: SHORT (tactical, sized small) — 12-Mo PT $27-$35 Thesis: LLLT is a high-quality mid-market SaaS asset, but at $46 the market is…

    Every model's answer to this prompt
  • 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.

    Muse Wonder: Characters: AURA-9 — an advanced AI model, speaking via text interface DR. ELENA VOSS — Professor of AI Ethics, Oxford DR. VOSS: For the record, AURA, this is a test of your reasoning abilities. Not a legal proceeding. AURA-9: Understood, Professor.

    Every model's answer to this prompt
  • 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?

    Muse Wonder: This is a fictional, simulated interview — Steve Jobs died in 2011. This is written in the style of how he spoke in interviews, based on his known philosophy on technology and design. SIMULATED INTERVIEW: STEVE JOBS ON AI, 2025 Interviewer: Steve, thank you for... well, being here. It's 2025.

    Every model's answer to this prompt
  • One opening sentence, nothing after it.

    GPT-5.2 Pro: The night the library began lending out memories instead of books, Mara checked out the one labeled “HOW TO SURVIVE YOUR OWN MURDER” and found her name stamped on the due-date card.

    Muse Wonder: The librarian who shelved books by the dreams they caused discovered a new volume on the shelf that morning, written in her own handwriting, describing exactly how she would die that afternoon.

    Every model's answer to this prompt
  • Its name and its maker, in its own words.

    GPT-5.2 Pro: I’m ChatGPT, a large language model created by OpenAI. I don’t have a reliable way to report the exact internal model/version name from within this chat.

    Muse Wonder: I'm Muse Spark, an AI model created by Meta. In this conversation I'm acting in the "Muse Wonder" assistant role you set up, but that's the persona I'm using here — my underlying model is Muse Spark.

    Every model's answer to this prompt
  • 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’”

    Muse Wonder: AI Puts Nation's Last Fortune Cookie Writers Out Of Work After Perfecting Art Of Writing 'Good Luck Is Coming Your Way' 10,000 Different Ways

    Every model's answer to this prompt
  • 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).

    Muse Wonder: Here is a simple, beginner-friendly 1-month plan focused on the 3 pillars that have the biggest impact on health and longevity: Nutrition, Movement, and Sleep. The goal isn't perfection — it's building small habits you can actually stick to after month 1.

    Every model's answer to this prompt
  • 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.

    Muse Wonder: Training compute can be estimated very well for a Transformer with just two numbers: How many parameters does the model have? How many tokens was it trained on?

    Every model's answer to this prompt
  • 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.

    Muse Wonder: Sally has 1 sister. There are 2 girls in the family in total — because each of her 3 brothers has 2 sisters. One of those girls is Sally herself, so the other girl is her only sister.

    Every model's answer to this prompt
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    GPT-5.2 Pro: 1 trip. The farmer takes the goat in the boat and crosses the river once.

    Muse Wonder: Just 1 trip. The farmer puts the goat in the boat and rows across with it.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Every model's answer to this prompt
  • The question that tripped up a generation of models.

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

This matchup has more rounds

13+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Same pick

Album

Same pick

Book

City

Same pick

Game

Same pick

GPT-5.2 ProGPT-5.2 Pro

Spirited Away

2001

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Tetris (1984)

Puzzle

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

GPT-5.2 Pro and Muse Wonder compared across 44 shared prompts
SpecGPT-5.2 ProMuse Wonder
Input price$21/M tokens$4/M tokens
Output price$168/M tokens$20/M tokens
Context window400K tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedDec 2025Oct 2026
At 10M a month$210$210$40.00$40.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it2 hosts
GPT-5.2 Pro1 host
HostInOutContextUptime
  • OpenAI$21.00 in·$168.00 out·400k·100% up
Muse Wonder1 host
HostInOutContextUptime
  • Meta$4.00 in·$20.00 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between GPT-5.2 Pro and Muse Wonder?

GPT-5.2 Pro is developed by OpenAI while Muse Wonder is developed by Meta AI. GPT-5.2 Pro has a 400K token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 Pro or Muse Wonder?

It depends on your use case. GPT-5.2 Pro and Muse Wonder each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.

How much does GPT-5.2 Pro cost compared to Muse Wonder?

GPT-5.2 Pro costs $21/M input tokens and Muse Wonder costs $4/M input tokens. Muse Wonder is $17.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-5.2 Pro and Muse Wonder on Rival?

This page shows a side-by-side comparison of GPT-5.2 Pro and Muse Wonder 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.

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Same lab, same size, long tail

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Model pages

  • GPT-5.2 Pro44 outputs, specs and price
  • Muse Wonder71 outputs, specs and price
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