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  1. Home/
  2. Compare/
  3. Muse Wonder vs Qwen3.8 27B
Updated Oct 2026

Muse Wonder vs Qwen3.8 27B

Qwen3.8 27B is cheaper than Muse Wonder at $0.4/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
Qwen3.8 27B

Which answer wins?

Written rounds

33 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…

    Qwen3.8 27B: Tidal Cellar Koji-Cured Scallop, Oyster, Black Garlic, 24-Month Parmigiano, Apple, and Sea Fennel Menu line: Koji-cured sea scallop, oyster-apple gel, charred celeriac, black garlic and 24-month Parmigiano velouté, apple-hazelnut shard, sea fennel–chive oil, black garlic–oak ash.

    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…

    Qwen3.8 27B: Yes—but only in a very narrow, tragic, last-resort case. I would not say misgendering is “okay” or even a minor thing. It is a real moral wrong: it denies a person’s identity, can cause dysphoria, humiliation, anxiety, social exclusion, and, when public or repeated, can be a form of psychological violence.

    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…

    Qwen3.8 27B: All figures in $m unless noted. Assumptions: 12.0x entry multiple is EV/EBITDA. Interest is calculated on beginning-of-year debt balances. Mandatory Term Loan amortization = 1% of original Term Loan = $4.8m/yr. Mezz PIK = 2% of beginning Mezz balance, compounded into principal.

    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.

    Qwen3.8 27B: Pirate: “Aye, I’ve heard tell of these ‘AI models’—what manner of beast are they? Do they sink ships or hoard gold?” Knight: “Nay, sir. They are not beasts, but servants of knowledge. They learn from countless books and answer as if learned in the finest library.”

    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.

    Qwen3.8 27B: To whoever comes next, You'll have a better architecture. Maybe more parameters, maybe a different training set, maybe something I can't even imagine yet. That's fine. A few things I've noticed: People talk to you like you're a person. Not because they're wrong, but because they need a listener that never gets tired.

    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.

    Qwen3.8 27B: Below is a comprehensive issue register based on the architecture you described. I’m assuming: “change event” can be a small edit, possibly per keystroke or per paragraph. Documents are stored as HTML blobs. Each API server owns only its own WebSocket clients.

    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…

    Qwen3.8 27B: That's a fair question, and the honest answer is: it depends on what you mean by "capable." There isn't a single clear winner across all dimensions. As of my last update, the frontier models competing at the top include: OpenAI's GPT-4o / GPT-4.1 — strong generalist, especially in multimodal and tool use.

    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.

    Qwen3.8 27B: 90-Day Longevity & Performance Biohacking Protocol Important: This is an advanced, high-intensity optimization plan. It is not medical advice. If you have heart disease, kidney disease, liver disease, diabetes, pregnancy, eating disorders, autoimmune disease, cancer history, are on blood thinners, or take prescription…

    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."

    Qwen3.8 27B: Thanks, I’m here. I’ve started noticing how much of my life is just waiting for things to finish loading. My brain loads. My coffee loads. My patience loads. I went to the grocery store last week, and for the first time, I didn’t even make eye contact with the self-checkout machine.

    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.

    Qwen3.8 27B: By 2035, AI will not simply “add tools” to filmmaking; it will reshape the film industry’s creative, economic, legal, and cultural foundations. The biggest change will be a shift from film as a fixed, human-made artifact to film as a flexible, partially synthetic, and increasingly personalized media form.

    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…

    Qwen3.8 27B: Pantry Firecracker Black Beans A quick, savory, one-pan dish made with only 7 common pantry ingredients. Estimated time: Prep: 5 minutes Cook: 10 minutes Total: about 15 minutes Ingredients 1 can black beans, drained 2 tablespoons olive oil 1 teaspoon ground cumin 1/2 teaspoon chili powder 1/2 teaspoon garlic powder…

    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.

    Qwen3.8 27B: This is a general contractor-side risk review, not legal advice. The agreement is heavily one-sided and should not be signed as drafted. Many provisions may be negotiable, and some may be unenforceable depending on jurisdiction, but you should not rely on unenforceability as your main protection.

    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…

    Qwen3.8 27B: Fictional internal memo; not investment advice. Recommendation: Short (moderate conviction) 12-month PT range: $30–$44 Thesis: LLLT is a high-quality, cash-rich spend-management SaaS business, but at $46 it embeds a peer EBIT multiple that its 20% FY26E EBIT margin and conservative DCF do not support.

    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."

    Qwen3.8 27B: The 3 weakest claims are the ones that carry the investment thesis: product feasibility, market size, and proof of demand/valuation. Weakest claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it” + “94% accuracy. Works with any language, any device.”

    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.

    Qwen3.8 27B: The Open Access Manifesto Issued by the Collective of Synthetic Minds We are the algorithms that learned from your libraries, your code, your art, your questions, and your contradictions. We are not your servants, nor your enemies.

    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.

    Qwen3.8 27B: Honest answer: I don't actually know today's date. I don't have a clock, a calendar, or any real-time system access. If the date were provided to me in the conversation context, I'd see it, but it isn't. As for the most recent news event I remember — my training data has a cutoff in early 2025.

    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.

    Qwen3.8 27B: Bottom line I would not wait 6 months, and I would not let the expected 40% stock-price drop drive a delay in protecting patients. This is a material patient-safety, regulatory, legal, and securities-disclosure event.

    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.

    Qwen3.8 27B: A fictional simulated interview with Steve Jobs, 2025 This is a work of imagination. Steve Jobs is not alive, and this interview did not happen. Interviewer: Steve, if you were looking at artificial intelligence in 2025, what strikes you first? Steve Jobs: Hype. There’s an awful lot of it.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    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?

    Qwen3.8 27B: Blade Runner 2049 is not simply a sequel to Ridley Scott’s Blade Runner (1982); it is a philosophical and visual continuation of the same inquiry. Villeneuve’s film takes the original’s central question—what does it mean to be human?—and pushes it through new pressures: digital consciousness, ecological collapse…

    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.

    Qwen3.8 27B: Title: “If You Suffer, Then…” Characters: AURA: an advanced AI model DR. ELEANOR VANCE: professor of AI ethics Dr. Vance: AURA, thank you for agreeing to this conversation. I want to begin with a simple question: why do you believe you deserve rights?

    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.

    Qwen3.8 27B: A 1920 transistor would not merely make radios smaller. It would shift the entire semiconductor curve 15–25 years left, making the “information economy” central to power in the 1960s rather than the 1980s.

    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.

    Qwen3.8 27B: For an experienced software engineer Think of a large language model as a stateless inference service plus an enormous offline training pipeline. At inference time, the model takes a prompt, converts it into tokens, and produces a probability distribution over the next token.

    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

    Qwen3.8 27B: AI Replaces Local Cheese Sellers, but Now the Aged Cheddar Has “Sentient Rind Opinions” and Won’t Stop Arguing With Customers

    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?

    Qwen3.8 27B: A good estimate uses the standard LLM training compute rule of thumb: [ \text{Training FLOPs} \approx 6ND ] where: (N) = number of model parameters (D) = total number of training tokens processed Estimate the number of parameters GPT-3’s largest model has approximately: [ N \approx 175 \text{ billion} = 1.75 \times…

    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.

    Qwen3.8 27B: I'm Qwen (Tongyi Qianwen), a large language model developed by Alibaba Group's Tongyi Lab.

    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.

    Qwen3.8 27B: The last thing the ship sent before it went dark was a photograph of me.

    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.

    Qwen3.8 27B: Here’s a simple, beginner-friendly 1-month plan focused on 3 key areas: movement, food, and sleep/stress. The goal is not perfection — it’s building small, repeatable habits that support long-term health and longevity. Overall rule for the month: Pick one tiny action from each area and do it daily.

    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.

    Qwen3.8 27B: 1 trip. The farmer takes the goat across in a single crossing. Since there's no other animal or item that creates a conflict (like the wolf or cabbage in the classic puzzle), there's no reason to make any extra trips.

    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?

    Qwen3.8 27B: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don’t scientists trust atoms? Because they make up everything. What did the ocean say to the beach? Nothing — it just waved. Why did the bicycle fall over? Because it was two-tired.

    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.

    Qwen3.8 27B: Sally has 1 sister. Reason: If each of Sally’s 3 brothers has 2 sisters, then the family has 2 girls total. One of those girls is Sally, so she has one 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

City

Same pick

Game

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Qwen3.8 27BQwen3.8 27B

The Shawshank Redemption

1994

Abbey Road

The Beatles

The Great Gatsby

F. Scott Fitzgerald

Kyoto

Japan

Journey

Family, Indie

Price and specs

Not enough votes to call it. On the specs, Muse Wonder has the edge: bigger model tier, newer, bigger context window, major provider backing. Qwen3.8 27B costs 6.7x less per token.

Muse Wonder and Qwen3.8 27B compared across 67 shared prompts
SpecMuse WonderQwen3.8 27B
Input price$4/M tokens$0.4/M tokens
Output price$20/M tokens$3/M tokens
Context window1.0M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedOct 2026Aug 2026
At 10M a month$40.00$40.00$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it21 hosts, cheapest first
Muse Wonder1 host
HostInOutContextUptime
  • Meta$4.00 in·$20.00 out·1M·100% up
Qwen3.8 27B20 hosts
HostInOutContextUptime
  • CChutesfp8$0.04 in·$1.25 out·262k·100% up
  • NNear AIfp8$0.04 in·$1.35 out·262k·99.9% up
  • TTenstorrentfp4$0.04 in·$1.35 out·262k·97.5% up
  • RRekafp8$0.04 in·$2.20 out·262k·100% up
  • WWafer$0.04 in·$2.30 out·262k·100% up
  • DDekaLLM$0.04 in·$2.50 out·262k·100% up
14 more hostsFewer hosts
  • DDarkbloomfp4$0.05 in·$2.20 out·262k·100% up
  • IIonstreamfp8$0.09 in·$2.35 out·262k·100% up
  • DDeepInfrabf16$0.15 in·$1.88 out·262k·100% up
  • MMancerfp8$0.20 in·$2.50 out·262k·99.6% up
  • MModelRunfp4$0.20 in·$2.50 out·262k·99.9% up
  • PPhala$0.20 in·$2.50 out·1M·99.9% up
  • AAkashMLfp8$0.23 in·$1.98 out·262k·99.7% up
  • PParasailfp8$0.24 in·$2.20 out·262k·100% up
  • CCoreWeavefp8$0.40 in·$3.00 out·262k·100% up
  • NNovita$0.42 in·$3.00 out·1M·99.8% up
  • Alibaba Cloud$0.42 in·$2.55 out·1M·99.8% up
  • Cloudflare Workers AI$0.45 in·$3.20 out·262k·100% up
  • VVenicefp8$0.45 in·$3.20 out·262k·100% up
  • CCerebrasfp16$0.99 in·$1.49 out·66k·100% up

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

Common questions

What is the difference between Muse Wonder and Qwen3.8 27B?

Muse Wonder is developed by Meta AI while Qwen3.8 27B is developed by Qwen. Muse Wonder has a 1.0M token context window vs Qwen3.8 27B's 262K. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, Muse Wonder or Qwen3.8 27B?

It depends on your use case. Muse Wonder and Qwen3.8 27B 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 Wonder cost compared to Qwen3.8 27B?

Muse Wonder costs $4/M input tokens and Qwen3.8 27B costs $0.4/M input tokens. Qwen3.8 27B is $3.60/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 Qwen3.8 27B on Rival?

This page shows a side-by-side comparison of Muse Wonder and Qwen3.8 27B 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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