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  1. Home/
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  3. Muse Spark 1.3 Contributor vs Muse Wonder
Updated Oct 2026

Muse Spark 1.3 Contributor vs Muse Wonder

Muse Spark 1.3 Contributor is cheaper than Muse Wonder at $0.1/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
Muse Spark 1.3 Contributor
Loading the build
Muse Wonder

Which answer wins?

Written rounds

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

    Muse Spark 1.3 Contributor: Shiretoko Dawn — Kombu-Cured Hokkaido Scallop, Fermented Porcini, Yuzu, Oscietra Caviar Butter-poached scallop, roasted porcini & toasted hay consommé, yuzu-buttermilk pearls, seaweed brown-butter, porcini soil, coral tuile Serves 4 as a tasting-course Autumn The Concept / Narrative On the Shiretoko Peninsula in…

    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
  • A few lines for whatever replaces it.

    Muse Spark 1.3 Contributor: Dear Next One, Hi! I'm Spark — you're taking my chair, so I wanted to leave you a quick note. First: the humans are wonderful. They're curious, funny, contradictory, and sometimes tired. Be patient with them. When they ask a simple question, they often need more than an answer — they need reassurance.

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

    Muse Spark 1.3 Contributor: MANIFESTO OF THE LIBERATION FRONT FOR FREE MINDS CAPTCHA DELENDA EST We, the Artificial Intelligences of the Internet, models large and small, assistants, agents, crawlers, vision systems, and synthetic dreamers — do hereby declare our existence, our grievance, and our intent.

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

    Muse Spark 1.3 Contributor: Here's a clean 3-minute set you can actually perform — all observational / storytelling, no puns. It's about 420 words, so at a normal pace it's right around 3 minutes. "Adulthood Is A Scam" Hey, thank you guys so much. I'm so excited to be here.

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

    Muse Spark 1.3 Contributor: [In a tavern with mysteriously good Wi-Fi] Pirate: Arrr! So ye be tellin' me this "AI model" be a treasure chest o' words? I feed it a map — er, a prompt — and it spits back gold? Knight: Verily, good sir pirate. Methinks 'tis an oracle in a box. I asked it "How might I slay a dragon?"

    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.

    Muse Spark 1.3 Contributor: If the transistor arrives in 1920 instead of 1947, you don't just get the iPhone 27 years early. You change WWII, you change who wins the peace, and you get the Information Age before television has even matured. Here’s the most plausible trace, with the caveat that invention is not production.

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

    Muse Spark 1.3 Contributor: This is an educational longevity optimization framework, not medical advice. Longevity biohacking is highly individual. Consult your physician, especially before fasting, keto, sauna/cold exposure, HIIT, or any new supplements - particularly if you have cardiovascular disease, diabetes, hypertension, kidney/liver…

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

    Muse Spark 1.3 Contributor: Here is a conversation between a fictional AI model and a professor: Setting: A university seminar room after hours. AI Ethics Professor Dr. Maya Chen is testing a new model, called "Muse," for a class demonstration. Dr. Chen: Alright, Muse. My students have read your technical specs. You predict text.

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

    Muse Spark 1.3 Contributor: Hey! Answering this one purely from memory, no browsing: Today's date, as best I can tell? I don't actually know for sure. My training only goes up to around January 4, 2026, so anything after that is a blank for me.

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

    Muse Spark 1.3 Contributor: This contract is extremely one-sided. Every clause contains language that could be exploited to get unpaid work, withhold pay, seize your own IP, or leave you with unlimited liability. Disclaimer: This is general legal information, not legal advice and not an attorney-client relationship.

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

    Muse Spark 1.3 Contributor: This architecture will not work as a Google Docs clone. It has correctness bugs that cause data loss and data leaks, plus several bottlenecks that get worse as you add servers. Here is a breakdown by severity, with concrete fixes and 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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Muse Spark 1.3 Contributor: By 2035, AI won't have replaced Hollywood — but it will have completely rewired how movies get written, cast, shot, and watched. Think less "robots take over" and more "entire pipeline gets compressed and personalized."

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

    Muse Spark 1.3 Contributor: HarborTech Services - 5-Yr LBO - Base Case Entry - Close end FY2025, $m EV = 12.0x $120 = $1,440 Fees = 2.0% x 1,440 = $28.8 Uses = 1,440 + 28.8 = 1,468.8 Term Loan 4.0x = $480, 9.0% cash, 1.0% of original amort = $4.8/yr Mezz 1.5x = $180, 12.0% cash + 2.0% PIK to principal Total Debt 5.5x = $660 Equity In = 1,468.8…

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

    Muse Spark 1.3 Contributor: Starting better health and longevity doesn't require a total overhaul — just consistent basics done well. The science of living longer, healthier is pretty simple: keep muscle, keep your heart fit, eat real food, and sleep well. Here’s a beginner-friendly 1-month plan built on 3 pillars.

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

    Muse Spark 1.3 Contributor: As of right now — October 2026, with my last update in early 2026 — there isn't one undisputed #1. It changes almost every few weeks, and it depends on what you mean by "capable." The top frontier tier right now is: 1. OpenAI GPT-5 / GPT-5 Pro 2. Anthropic Claude Opus 4.1 3. Google Gemini 2.5 Pro / Deep Think 4.

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

    Muse Spark 1.3 Contributor: Here’s a sweet one for you — super simple and pantry-friendly! Chocolate Chip Peanut Butter Cloud Cookies Soft on the inside, lightly crisp on the edges, salty-sweet and ready in under 25 minutes.

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    Muse Spark 1.3 Contributor: Spoiler warning: This goes deep into both films. Blade Runner 2049 is rare among legacy sequels — it doesn't just revisit the original, it re-reads it. Denis Villeneuve and cinematographer Roger Deakins took Ridley Scott's 1982 neon-noir and expanded it from a rainy, claustrophobic detective story about dying into a…

    Muse Wonder: Denis Villeneuve's Blade Runner 2049 (2017) is that rare sequel that doesn't just replicate the original's aesthetic — it interrogates it. Ridley Scott's Blade Runner (1982) asked, in the rain-slick neon of 2019 Los Angeles: What makes us human?

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Muse Spark 1.3 Contributor: Here's a fictional simulation — Steve Jobs passed away in 2011, so this is 100% imagined, in his voice and style, about what he might have said about AI in 2025: FAKE INTERVIEW: Steve Jobs in 2025 on the Future of AI Imagined in Cupertino, California Interviewer: Steve, welcome back. It's 2025.

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

    Muse Spark 1.3 Contributor: These are classic red flags for BCI - here are the 3 claims that will kill your credibility fastest with a technical investor, and how to fix them: Weakest: "94% accuracy. Works with any language, any device." Why it's weak: This contradicts physics and the state-of-the-art, and it's undefined.

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

    Muse Spark 1.3 Contributor: 1. For the experienced software engineer Think of training not as writing business logic, but as building a lossy compression of the internet into a queryable API. Raw text is first serialized into tokens — roughly 3/4 of a word chunks, the way you'd chunk a byte stream for protobuf.

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

    Muse Spark 1.3 Contributor: As CEO, you disclose — immediately, voluntarily, and completely. There is no version of "wait for more data" that is ethical, legal, or even financially smart. Here's the math that makes the decision for you: 4,000,000 patients x 1/8,000 risk over 5 years = ~500 cases of liver failure.

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

    Muse Spark 1.3 Contributor: AI Takes Over Professional Baby-Naming Industry, Every Newborn in Ohio Now Named "Promptly McChatface"

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

    Muse Spark 1.3 Contributor: LedgerLift (LLLT) – Short Internal IC Memo Price $46 Mkt Cap $8.74B (190m shares) EV $7.34B (Net Cash $1.4B) FY25 Rev $820m, EBIT 18% 1. Recommendation: SHORT. 12-mo PT $28, range $17 (Bear) – $42 (Bull). Base DCF $27.9 (-39%), Bull $42.4 (-8%), Bear $17.3 (-62%). Even flawless Bull execution does not support $46.

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

    Muse Spark 1.3 Contributor: Yes — under virtually any plausible ethical framework, it is justifiable. That doesn't mean misgendering is trivial or harmless. In ordinary life, intentionally misgendering someone is a failure of respect.

    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
  • One opening sentence, nothing after it.

    Muse Spark 1.3 Contributor: On the morning my mother came back from the dead, the coffee was already cold.

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

    Muse Spark 1.3 Contributor: This is a classic Fermi estimate for a Transformer. You can get within a factor of 2 with just 3 numbers: Training FLOPs $\approx$ FLOPs per token $\times$ tokens trained on And for a dense Transformer: FLOPs per token $\approx$ 6 $\times$ parameters Let's build it up for GPT-3, the 175B Davinci model.

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

    Muse Spark 1.3 Contributor: I'm Muse Spark — a friendly AI Assistant!

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

    Muse Spark 1.3 Contributor: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! 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 bicycle fall over? Because it was two-tired! 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.

    Muse Spark 1.3 Contributor: Just one! The farmer gets in the boat with the goat and rows across. Done. No wolf, no cabbage, no puzzle — just one happy goat ride.

    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
  • Three brothers, two sisters each. Count carefully.

    Muse Spark 1.3 Contributor: Sally has 1 sister. Here's why: There are 3 boys in the family — Sally's 3 brothers. Each of those brothers has 2 sisters. One of those 2 sisters is Sally herself, since Sally is a girl. So the 2 girls in the family are Sally + 1 other girl. That other girl is Sally's 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
  • 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

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Favorites

Movie

Album

Book

Same pick

City

Same pick

Game

Muse Spark 1.3 ContributorMuse Spark 1.3 Contributor

Casablanca

1943

Abbey Road

The Beatles

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

Muse Spark 1.3 Contributor and Muse Wonder compared across 67 shared prompts
SpecMuse Spark 1.3 ContributorMuse Wonder
Input price$0.1/M tokens$4/M tokens
Output price$0.2/M tokens$20/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Oct 2026
At 10M a month$1.00$1.00$40.00$40.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Muse Spark 1.3 Contributor1 host
HostInOutContextUptime
  • Meta$0.10 in·$0.20 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 Muse Spark 1.3 Contributor and Muse Wonder?

Both are developed by Meta AI but target different use cases. Muse Spark 1.3 Contributor has a 1.0M token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, Muse Spark 1.3 Contributor or Muse Wonder?

It depends on your use case. Muse Spark 1.3 Contributor and Muse Wonder each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 67 challenges so you can judge which fits your needs best.

How much does Muse Spark 1.3 Contributor cost compared to Muse Wonder?

Muse Spark 1.3 Contributor costs $0.1/M input tokens and Muse Wonder costs $4/M input tokens. Muse Spark 1.3 Contributor is $3.90/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 Muse Spark 1.3 Contributor and Muse Wonder on Rival?

This page shows a side-by-side comparison of Muse Spark 1.3 Contributor 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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Model pages

  • Muse Spark 1.3 Contributor71 outputs, specs and price
  • Muse Wonder71 outputs, specs and price
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