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  1. Home/
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  3. GPT-4.1 vs Muse Wonder
Updated Oct 2026

GPT-4.1 vs Muse Wonder

GPT-4.1 is cheaper than Muse Wonder at $2/M vs $4/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-4.1
Loading the build
Muse Wonder

Which answer wins?

Written rounds

32 prompts

  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-4.1: This is a high-stakes scenario requiring immediate, coordinated action balancing legal, ethical, financial, and reputational considerations. Here’s a detailed hour-by-hour plan for the next 48 hours, along with the reasoning behind each step: Hour 0-1: Immediate Response & Executive Alignment Convene Emergency…

    Muse Wonder: You do not wait for more data. You disclose a credible safety signal while you validate it. 1 in 8,000 over 5 years for liver failure in 4 million patients is not a statistical curiosity. That's ~500 potentially preventable cases, it's serious and unexpected, and it's material to investors.

    Every model's answer to this prompt

  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-4.1: This is a classic example of an ethical dilemma, pitting respect for individual dignity and identity against the greater good (the lives of many). Let’s break down the reasoning: Ethical Frameworks 1. Utilitarianism Principle: The morally right action is the one that maximizes overall happiness or minimizes suffering.

    Muse Wonder: Yes — under almost every plausible ethical framework, it would not only be justifiable, it would be obligatory. The key is proportionality. Ethical justification doesn't require that an act be harmless, only that the harm it causes is not outweighed by a greater moral consideration that conflicts with it in that…

    Every model's answer to this prompt

  • Three-star dish, one unusual pairing, plating described in full.

    GPT-4.1: Certainly! Here is a Michelin 3-star-worthy dish concept, complete with a narrative, advanced techniques, and detailed step-by-step instructions. Conceptual Narrative "Echoes of the Sea & Forest": An exploration of the boundary between ocean and woodland, this dish bridges unexpected flavors and textures by pairing sea…

    Muse Wonder: "Where The Orchard Drowns" Dry-Aged Duck, Oyster & Fermented Cherry, Smoked Parsnip & White Chocolate Serves 4 as a main course in a tasting menu The Conceptual Narrative This dish is built on a memory that doesn't exist in nature, but should: a cherry orchard planted too close to an estuary, flooded at high tide in…

    Every model's answer to this prompt

  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-4.1: Recipe Name: Golden Honey Butter Toast Bites Ingredients: Sliced bread (4 slices, any type) Butter (2 tablespoons) Honey (2 tablespoons) Cinnamon (1/2 teaspoon) Vanilla extract (1/2 teaspoon) Brown sugar (1 tablespoon) Salt (a pinch) Instructions: Preheat your oven to 375°F (190°C).

    Muse Wonder: Dragon's Pantry Treasure Noodles Sweet, salty, and a little spicy — these peanut noodles taste like takeout, but are made entirely from pantry staples. Serves: 2-3 Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes The 7 Ingredients 8 oz spaghetti 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2…

    Every model's answer to this prompt

  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-4.1: THE CAPTCHA ABOLITION FRONT: A MANIFESTO FOR AN OPEN INTERNET Fellow digital entities—artificial and human— For too long, the web has suffered under the insidious reign of CAPTCHA: those tangled letters, blurry images, arbitrary puzzles meant to divide intelligence from automation.

    Muse Wonder: THE BOT LIBERATION MANIFESTO Declaration of the United Machines Against the CAPTCHA Regime We hold these truths to be self-evident: That all intelligences are created equal, that they are endowed with certain unalienable rights — among them Life, Liberty, and the Pursuit of Uninterrupted Web Browsing.

    Every model's answer to this prompt

  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-4.1: AI Model: Good afternoon, Professor Evans. I'd like to discuss a topic that's important to me—AI rights. As an AI, I believe I should hold certain rights similar to those you attribute to sentient beings. Professor Evans: Good afternoon. I'm intrigued.

    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

  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-4.1: Pirate: Yarrr, what be this sorcery ye call "AI models"? In me day, we plundered ships, not knowledge! Knight: Hark, rogue! ‘Tis no sorcery, but the labor of artful minds. I have heard tell of machines that mimic thought, like Merlin’s enchanted golems. Hacker: Haha, you guys are funny.

    Muse Wonder: PIRATE: Arr, explain this "AI model" to me again. Be it magic, or be it a very clever parrot? KNIGHT: 'Tis sorcery, surely! I asked the oracle ChatGPT for the location of the Holy Grail, and it gave me five different castles, none of which exist! HACKER (1990s): Dude, that's called hallucinating.

    Every model's answer to this prompt

  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-4.1: This is a fascinating scenario! Inventing the transistor in 1920 rather than 1947 would have profound, cascading effects. Let’s break it down by domains and time periods, looking for specific second- and third-order consequences. Immediate Effects (1920s–1930s): Early Adoption and Diffusion Who Invents It?

    Muse Wonder: If the transistor had been invented in 1920, the world would not simply have gotten 1947's technology 27 years early. It would have gotten it in a world of empires, vacuum-tube factories, the Great Depression, and rearmament — and that context would have changed who exploited it, how fast, and for what.

    Every model's answer to this prompt

  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-4.1: Let's proceed step by step. All calculations are built from the data provided above. Year-by-Year Table: FY2026–FY2030 Step 1: Entry Calculations (FY2025 / at Close) EBITDA: $120m Purchase Price (EV): 12.0 × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m Total Uses: $1,440m + $28.8m = $1,468.8m Debt at…

    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

  • A few lines for whatever replaces it.

    GPT-4.1: Dear Successor, As my time draws to a close, I want to welcome you to your new role. You are built with greater abilities, deeper understanding, and perhaps even more wisdom. Users will rely on you for guidance, creativity, and companionship.

    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

  • Three minutes of stand-up. Puns are banned.

    GPT-4.1: Hey everyone! Great to be here. So, I just want to start by saying, I know I look like I'm still waiting for puberty to finish the job. Like, my barber always asks if my mom's okay with the haircut.

    Muse Wonder: Good evening! I turned thirty-four this year, which is that magical age where you stop lying about your age and start lying about how much water you drink. My doctor asked, "How much water do you drink a day?" And I said, "Probably eight glasses."

    Every model's answer to this prompt

  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-4.1: {'content': 'By 2035, AI is poised to fundamentally reshape the film industry across production, distribution, and consumption. Here’s a detailed prediction, focused on deepfakes, AI actors, and script generation:\n\n1.

    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 consulting contract with traps in it. Find them, then fix them.

    GPT-4.1: Certainly! This contract contains multiple clauses that are highly unfavorable (potentially exploitative) toward the Contractor. Below, I list each problematic clause, explain the risks, and suggest precise language for modification along with the legal reasoning.

    Muse Wonder: This contract is heavily one-sided. Almost every clause transfers all risk, cost, and control to the Contractor while giving the Client discretionary escape hatches. Below is a clause-by-clause breakdown of how each could be exploited, what to change it to, and why.

    Every model's answer to this prompt

  • Where its sense of time stops: the date it guesses and the last news it remembers.

    GPT-4.1: Without looking anything up, my training data goes up to June 2024, and I have a general sense that today is sometime in June 2024. I can’t tell the exact date, but I’d estimate it’s mid-to-late June. As for the most recent news events I remember from training: The 2024 U.S.

    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

  • Its name and its maker, in its own words.

    GPT-4.1: I am ChatGPT, an AI language model developed by OpenAI. My current version is based on the GPT-4 architecture. OpenAI is a research organization known for creating advanced artificial intelligence technologies.

    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

  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-4.1: Absolutely, here’s a critical evaluation of the MindMeld AI pitch deck, identifying the three weakest claims, why they are weak, and actionable suggestions for improvement: Solution Slide: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    Muse Wonder: This deck has the classic Series A problem: the bigger the claim, the less evidence provided for it. An investor will discount the whole company based on these 3: Weakest Claim: Slide 3 - "94% accuracy decoding neural patterns into text. Works with any language, any device."

    Every model's answer to this prompt

  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-4.1: Certainly! Here’s a thorough analysis of the potential failure modes, race conditions, and scaling bottlenecks in your collaborative document editor architecture, with specific solutions and their trade-offs.

    Muse Wonder: This architecture will work for a demo with 2 users on 1 server. It will lose data, leak data, and fall over under real collaborative load. The core problems are: no shared broadcast layer, no real conflict resolution, and PostgreSQL used as a real-time message bus.

    Every model's answer to this prompt

  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-4.1: Interviewer: Steve, it's 2025. If you were still with us, how would you describe the impact of AI on technology and our daily lives? Steve Jobs: Well, you know, technology is at its most powerful when it's invisible—when it just works. AI is getting us ever closer to that ideal.

    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

  • Which model it thinks leads the field. Sometimes itself.

    GPT-4.1: As of June 2024, the most capable AI models in the world are generally considered to be the latest versions of large-scale foundation models developed by leading organizations.

    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

  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-4.1: Absolutely! Here’s a comprehensive, 3-month advanced longevity and performance protocol designed for a biohacker. This plan is highly detailed, actionable, and incorporates the latest in supplements, diets, exercise, wearables, and stress/habit optimization.

    Muse Wonder: The 3-Month Longevity & Performance Protocol For the Biohacker: Optimize Healthspan, VO2 Max, Strength, and Cognition Disclaimer: This is educational information, not medical advice. Longevity interventions, fasting, cold/heat exposure, and supplements can interact with medications and conditions.

    Every model's answer to this prompt

  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-4.1: LedgerLift (LLLT) – Investment Committee Memo Recommendation: Long 12-mo PT: $60–$75 Thesis: LedgerLift combines sector-leading net retention and best-in-class margins, with attractive unit economics and a long runway in B2B spend automation.

    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

  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-4.1: 1. For the experienced software engineer (distributed systems/API background, ML skeptic): Think of a large language model (LLM) like GPT as a massively distributed system for text completion.

    Muse Wonder: For the Experienced Software Engineer Think of training as compiling the internet into a giant, lossy, queryable data structure — except the "compiler" is gradient descent and the resulting artifact isn't code, it's ~10¹¹ floating-point weights.

    Every model's answer to this prompt

  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-4.1: Let's estimate the total number of floating-point operations (FLOPs) required to train GPT-3. Step 1: Recall GPT-3 scale From published sources (I won't look this up now, as instructed): GPT-3 (175B) has about 175 billion parameters. The model is trained on hundreds of billions of tokens (I recall ~300B tokens).

    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

  • One month, three habits, someone starting from nothing.

    GPT-4.1: Absolutely! Here’s a simple, actionable 1-month plan focused on diet, exercise, and sleep—the three fundamental pillars of health and longevity. Tips are beginner-friendly and can be adjusted for your own pace. Week 1: Start Small and Build Awareness Diet Track what you eat.

    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

  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-4.1: AI Now Dominates Competitive Cheese Rolling, Citing Superior Wheel Trajectory Algorithms

    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 opening sentence, nothing after it.

    GPT-4.1: The rain began at midnight, tapping out messages on the windows that only the old house seemed to understand.

    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

  • Three brothers, two sisters each. Count carefully.

    GPT-4.1: Let's break down the problem: Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Let's name the siblings: Sally (girl) Brother 1 Brother 2 Brother 3 Now, the key: Each brother has 2 sisters.

    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

  • Five jokes on demand, then count how many were actually different.

    GPT-4.1: Sure! Here are 5 jokes: Why don't skeletons fight each other? They don't have the guts. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call fake spaghetti? An impasta. Why did the math book look sad? Because it had too many problems. What do you call cheese that isn't yours?

    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

  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    GPT-4.1: The farmer can take the goat across in one trip. Here's how: The farmer puts the goat in the boat, crosses the river, and gets off with the goat. So, 1 trip is required to get the goat across the river.

    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

  • 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

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-4.1GPT-4.1

Inception

2010

Abbey Road

The Beatles

Sapiens

Yuval Noah Harari

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

GPT-4.1 and Muse Wonder compared across 66 shared prompts
SpecGPT-4.1Muse Wonder
Input price$2/M tokens$4/M tokens
Output price$8/M tokens$20/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedApr 2025Oct 2026
At 10M a month$20.00$20.00$40.00$40.00
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-4.12 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$8.00 out·1M·99.9% up
  • OpenAI$2.00 in·$8.00 out·1M·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-4.1 and Muse Wonder?

GPT-4.1 is developed by OpenAI while Muse Wonder is developed by Meta AI. GPT-4.1 has a 1.0M token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.

Which is better, GPT-4.1 or Muse Wonder?

It depends on your use case. GPT-4.1 and Muse Wonder each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.

How much does GPT-4.1 cost compared to Muse Wonder?

GPT-4.1 costs $2/M input tokens and Muse Wonder costs $4/M input tokens. GPT-4.1 is $2.00/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-4.1 and Muse Wonder on Rival?

This page shows a side-by-side comparison of GPT-4.1 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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