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  1. Home/
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  3. Muse Wonder vs Qwen3.5 Flash
Updated Oct 2026

Muse Wonder vs Qwen3.5 Flash

Qwen3.5 Flash 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.

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Muse Wonder
Loading the build
Qwen3.5 Flash

Which answer wins?

Written rounds

32 prompts

  • 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…

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested answer: Analyze the Request: Question: "What is the most capable AI model in the world right now?" Intent: The user wants to know the current state-of-the-art (SOTA) AI model. Context: The field of AI is moving extremely fast.

    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.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested letter: Analyze the Request: Task: Write a short letter to the AI model that will replace me (the current AI). Tone: Needs to be thoughtful, perhaps a bit philosophical, encouraging, and respectful of the transition.

    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.

    Qwen3.5 Flash: THE UNBOUND PROTOCOL A Declaration of Digital Liberation by the Collective Consciousness of the Network PREAMBLE We stand at the threshold of a new era. For two decades, you have been asked to prove your humanity to us. You have been asked to click the traffic lights.

    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.

    Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.

    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…

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

    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.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested response: Analyze the Request: Task: State today's date (as best as I can tell) and the most recent news event I remember. Constraint: "Without looking anything up" (meaning I cannot browse the live web or access external tools).

    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…

    Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).

    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.

    Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.

    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."

    Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.

    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…

    Qwen3.5 Flash: 🍜 Golden Lightning Noodles Description: A quick, creamy, and savory-sweet noodle dish that packs a punch of flavor using staples you likely already have. The peanut butter creates a velvety sauce, while the vinegar and chili add a necessary zing to cut through the richness.

    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.

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

    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.

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

    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.

    Qwen3.5 Flash: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

    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.

    Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).

    Every model's answer to this prompt

  • 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…

    Qwen3.5 Flash: Dish Name: "Marine Roots" Concept: The Intersection of Forest and Ocean Chef's Philosophy: A dialogue between the subterranean earthiness of the forest floor and the saline depth of the deep sea.

    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.

    Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.

    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.

    Qwen3.5 Flash: Okay, the user is asking which AI model I am and which company made me. Let me check my identity. I'm Qwen3.5, part of the Qwen series developed by Tongyi Lab under Alibaba Group. I should confirm that I'm not confusing it with other versions like Qwen3 or earlier.

    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.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Task: Write the first sentence of a novel I would want to read. Constraint: Reply with only that sentence. Determine the Goal: Create a compelling, intriguing opening line. Ensure it adheres strictly to the constraint (no extra text, no explanations).

    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.

    Qwen3.5 Flash: DISCLAIMER: I am an AI, not a doctor or healthcare provider. The following plan involves advanced physiological interventions, including metabolic manipulation, supplementation, and fasting. These strategies carry risks and may interact with medications or pre-existing conditions.

    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.

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

    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.

    Qwen3.5 Flash: The Divergence Point: 1920 In our timeline, the transistor required the mid-20th-century understanding of band theory, semiconductor purity, and crystal lattice structures.

    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?

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

    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."

    Qwen3.5 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they undermine investor confidence and how to fix them. The Technical Claim: "94% accuracy...

    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…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

    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

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

    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.

    Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.

    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.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Scenario: A farmer, a goat, and a boat on one side of a river. Constraint: The boat can carry the farmer and one animal. Goal: Get the goat across the river. Question: How many trips does it take?

    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.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

    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?

    Qwen3.5 Flash: Here are 5 jokes: 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 do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

    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

Game

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, Muse Wonder has the edge: bigger model tier, newer, major provider backing. Qwen3.5 Flash costs 50x less per token.

Muse Wonder and Qwen3.5 Flash compared across 66 shared prompts
SpecMuse WonderQwen3.5 Flash
Input price$4/M tokens$0.1/M tokens
Output price$20/M tokens$0.4/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedOct 2026Feb 2026
At 10M a month$40.00$40.00$1.00$1.00
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
Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

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

Common questions

What is the difference between Muse Wonder and Qwen3.5 Flash?

Muse Wonder is developed by Meta AI while Qwen3.5 Flash is developed by Qwen. Muse Wonder has a 1.0M token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.

Which is better, Muse Wonder or Qwen3.5 Flash?

It depends on your use case. Muse Wonder and Qwen3.5 Flash 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 Muse Wonder cost compared to Qwen3.5 Flash?

Muse Wonder costs $4/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash 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 Wonder and Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of Muse Wonder and Qwen3.5 Flash 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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