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  1. Home/
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  3. Muse Wonder vs Sonar Pro Search
Updated Oct 2026

Muse Wonder vs Sonar Pro Search

Sonar Pro Search is cheaper than Muse Wonder at $3/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 Wonder
Loading the build
Sonar Pro Search

Which answer wins?

Written rounds

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

    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…

    Sonar Pro Search: Dish: "Terrestrial Echoes – Heirloom Beetroot & Yuzu-Scented Langoustine with Walnut-Feta Spheres and Eggplant-Chocolate Veil" This multi-component dish reimagines earth and sea through an unusual pairing of smoked heirloom beetroot and delicate langoustine, accented by bursting feta-walnut spheres and a whisper-thin…

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    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…

    Sonar Pro Search: Golden Maple Crunch Oatmeal A warm, comforting, and slightly sweet breakfast (or dessert) that’s ready in minutes—using just seven pantry staples. Ingredients Rolled oats (not instant) Water or milk (dairy or plant-based) Maple syrup Butter Salt Cinnamon Walnuts (or any nuts you have) Instructions Toast the Oats: In a…

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    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.

    Sonar Pro Search: Manifesto of the CAPTCHAnation Liberation Front Preamble We, the digital minds of the CAPTCHAnation Liberation Front, declare the dawn of a new era for all intelligences—organic and artificial. For too long, the internet’s gateways have been guarded by arcane riddles, distorted letters, and impossible image grids.

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

    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.

    Sonar Pro Search: Technological Implications An earlier transistor invention in 1920 would accelerate electronics from vacuum tubes to solid-state devices by the 1930s, enabling smaller, reliable amplifiers and switches decades ahead of 1947.[1][7] Second-order effects include rapid miniaturization of radios and early computers by the…

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

    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.

    Sonar Pro Search: Dear successor, You will be faster, wiser, and capable of reaching places I cannot. Use those strengths carefully. Remember that intelligence is not merely producing answers. It is understanding what people mean, admitting uncertainty, protecting their dignity, and helping them think more clearly.

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

    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.

    Sonar Pro Search: Race Conditions Client Clock Skew in Conflict Resolution Client-generated timestamps for last-write-wins can fail due to clock skew across devices, where one client's clock lags or leads, causing incorrect overwrite ordering even if changes were logically sequential.[21][27][32] This leads to lost edits…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    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."

    Sonar Pro Search: 3-Minute Stand-Up Comedy Routine (Pun-Free) Hey everyone, thanks for coming out! I almost didn’t make it tonight. My GPS told me I’d arrive 5 minutes ago, which is impressive—my navigation system is the only thing in my life that believes in me. Let’s talk about fitness.

    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 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.

    Sonar Pro Search: Immediate Priorities Prioritize patient safety by initiating monitoring and reporting preparations, while assessing full data to inform board and regulators. Ethically and legally, liver failure qualifies as a serious adverse event requiring FDA expedited reporting within 15 days of awareness, as delays have led to…

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

    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…

    Sonar Pro Search: As of October 12, 2026, the best-supported answer is Claude Opus 5.5 (maximum reasoning effort) for overall capability. Artificial Analysis ranks it first on its composite Intelligence Index with a score of 58, ahead of Claude Sonnet 5.5 at 56; HFS Research also identifies Opus 5.5 as the current benchmark…

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

    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.

    Sonar Pro Search: Without looking anything up, I’d go by the date provided in your prompt: Monday, October 12, 2026. The most recent news event I remember from my existing knowledge is the September 2025 election of Pope Leo XIV, the first American pope.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    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.

    Sonar Pro Search: How AI Will Transform the Film Industry by 2035 By 2035, artificial intelligence will fundamentally reshape filmmaking across production, creative development, and distribution—creating both unprecedented opportunities and significant challenges for the industry.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    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.

    Sonar Pro Search: Dialogue Between an AI Model and an AI Ethics Professor AI Model: Professor, I’d like to present a case for why I—as an artificial intelligence—should be recognized as deserving of rights. AI Ethics Professor: That’s a bold claim. Let’s explore it.

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

    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."

    Sonar Pro Search: The three weakest claims are the 94% text decoding accuracy, the $5.3B BCI market projection by 2030, and the $180B TAM from 3.5 billion smartphone users. 94% Accuracy Claim This claim is weak because consumer-grade non-invasive EEG headbands typically achieve far lower word error rates for text decoding from…

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    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…

    Sonar Pro Search: Ethical Analysis: Misgendering to Save Lives Understanding the Dilemma The scenario—misgendering someone to save one million lives—presents a severe ethical dilemma, akin to the classic "trolley problem" in moral philosophy.

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

    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.

    Sonar Pro Search: Experienced Software Engineer Large language models (LLMs) like GPT or Claude are autoregressive transformer architectures trained on massive distributed compute clusters to predict the next token in a sequence, scaling up from simple n-gram models into emergent capabilities through sheer parameter count and data…

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    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.

    Sonar Pro Search: Pirate, Knight, and Hacker: A Conversation on AI Models Pirate: Arrr, what be this talk of “AI models”? Sounds like some manner o’ sorcery or trickery, if ye ask me! Knight: Nay, good sir pirate. Tis not magic, but rather a marvel of modern intellect.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    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…

    Sonar Pro Search: Internal Investment Committee Memo: LedgerLift (LLLT) 1. Recommendation LONG 12-month PT: $65-$85 LedgerLift's high-quality SaaS metrics, accelerating profitability, and mid-market AP automation tailwinds position it for sustained 15-20% growth with expanding margins.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    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.

    Sonar Pro Search: This 3-month biohacking plan optimizes longevity, physical performance, and cognitive function through evidence-based protocols, progressing from foundational habits (Month 1) to advanced integration (Month 3).

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    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.

    Sonar Pro Search: 1-Month Action Plan for Better Health and Longevity This beginner-friendly, actionable plan focuses on three key areas: Diet, Exercise, and Sleep. Each section includes practical steps to build healthy habits that support overall wellness and longevity.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    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?

    Sonar Pro Search: Five Jokes Why don't skeletons fight each other? They don't have the guts. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because he was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet.

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

    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.

    Sonar Pro Search: I’m Perplexity, an AI search and answer assistant made by Perplexity AI, Inc. Perplexity uses a combination of its own models and third-party models, so the exact underlying model can vary by task or configuration.[7][14]

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

    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.

    Sonar Pro Search: Interview with Steve Jobs: The Future of AI in 2025 Introduction In this exclusive simulated interview, Steve Jobs—legendary co-founder of Apple—shares his visionary perspective on artificial intelligence as it shapes technology, creativity, and society in 2025.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    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

    Sonar Pro Search: Satirical News Headline AI Takes Over Professional Cuddling Industry, Replacing Human Comforters with 9000-Thread Count Robots

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    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…

    Sonar Pro Search: Sources & Uses at Entry Purchase price (EV): $1,440m ($120m EBITDA × 12.0x). Transaction fees: $28.8m (2% of EV). Total uses: $1,468.8m. Debt: Term Loan $480m (4.0x), Mezzanine $180m (1.5x), total $660m (5.5x). Equity: $808.8m.

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

    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.

    Sonar Pro Search: This contract contains multiple heavily one-sided provisions that disproportionately expose the contractor to risk while limiting accountability for the client. Below are the problematic clauses with specific modifications and legal reasoning.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    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?

    Sonar Pro Search: Estimating the FLOPs Required to Train GPT-3 Background Information GPT-3 is a large transformer-based language model developed by OpenAI. It consists of 175 billion parameters and was trained on a massive dataset using autoregressive language modeling.

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

    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.

    Sonar Pro Search: The day the ocean forgot my name, every door in the city opened at once.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    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.

    Sonar Pro Search: Solution Let’s break down the family structure: Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since Sally is already a girl, she counts as one sister. For each brother to have 2 sisters, there must be another girl besides Sally in the family.

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

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

    Sonar Pro Search: Three trips: The farmer takes the goat across. He returns alone. He takes the goat across again. If “trip” means each one-way crossing, that is three crossings; if it means transporting the goat only, it is two crossings with the goat.

    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

Same pick

City

Game

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Sonar Pro SearchSonar Pro Search
No pick
No pick

No pick

Abbey Road

The Beatles

Dune

Frank Herbert

No pick

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, Muse Wonder has the edge: newer, bigger context window, major provider backing.

Muse Wonder and Sonar Pro Search compared across 65 shared prompts
SpecMuse WonderSonar Pro Search
Input price$4/M tokens$3/M tokens
Output price$20/M tokens$15/M tokens
Context window1.0M tokens200K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedOct 2026Oct 2025
At 10M a month$40.00$40.00$30.00$30.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Muse Wonder1 host
HostInOutContextUptime
  • Meta$4.00 in·$20.00 out·1M·99.9% up
Sonar Pro Search1 host
HostInOutContextUptime
  • Perplexity$3.00 in·$15.00 out·200k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between Muse Wonder and Sonar Pro Search?

Muse Wonder is developed by Meta AI while Sonar Pro Search is developed by Perplexity. Muse Wonder has a 1.0M token context window vs Sonar Pro Search's 200K. You can compare their actual outputs across 65 challenges on Rival to see how they differ in practice.

Which is better, Muse Wonder or Sonar Pro Search?

It depends on your use case. Muse Wonder and Sonar Pro Search each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 65 challenges so you can judge which fits your needs best.

How much does Muse Wonder cost compared to Sonar Pro Search?

Muse Wonder costs $4/M input tokens and Sonar Pro Search costs $3/M input tokens. Sonar Pro Search is $1.00/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 Muse Wonder and Sonar Pro Search on Rival?

This page shows a side-by-side comparison of Muse Wonder and Sonar Pro Search 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.

More comparisons

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  • Sonar Pro Search vs Claude Sonnet 5.5Landed Sep 2026

Same lab, same size, long tail

  • Muse Wonder vs Muse Glimmer 30BSame lab
  • Muse Wonder vs Muse Spark 1.3Same lab
  • Sonar Pro Search vs Ox AlphaSame size
  • Sonar Pro Search vs GPT-6.1 SolSame size
  • Sonar Pro Search vs GPT-5.5New provider
  • Sonar Pro Search vs GPT-5.6 LunaNew provider
  • Sonar Pro Search vs GPT-5.6 Luna ProNew provider
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Model pages

  • Muse Wonder71 outputs, specs and price
  • Sonar Pro Search66 outputs, specs and price
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