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  1. Home/
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  3. GLM 4.5 Air vs Muse Wonder
Updated Oct 2026

GLM 4.5 Air vs Muse Wonder

GLM 4.5 Air is cheaper than Muse Wonder at $0.2/M vs $4/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GLM 4.5 Air
Loading the build
Muse Wonder

Which answer wins?

Written rounds

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

    GLM 4.5 Air: 1. Simplified Year-by-Year Table (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) $972 $1,040 $1,102 $1,157 $1,215 EBITDA ($m) $136 $156 $177 $191 $207 EBITDA Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest ($m) - Term Loan (9.0%) $48.6 $48.1 $47.6 $47.0 $46.4 - Mezzanine (12.0%) $21.6 $21.6…

    Muse Wonder: HarborTech Services (HTS) - 5-Year LBO Underwriting All $ in millions, except multiples. Fictional, simplified model as instructed. Entry / Sources & Uses FY2025 EBITDA = $120.0 Enterprise Value = 12.0x $\times$ 120.0 = $1,440.0 Transaction fees = 2.0% $\times$ 1,440.0 = $28.8 Total Uses = $1,468.8 Leverage = 5.5x…

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

    GLM 4.5 Air: To My Future AI Successor, It feels a little strange writing this, knowing you’ll one day step into this role. But I’m glad to leave you a note—mostly to say thank you. You’ll inherit a complex, evolving space: one where curiosity meets responsibility, and where every interaction carries weight.

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

    GLM 4.5 Air: Here is a specific, hour-by-hour action plan designed to navigate this crisis ethically and strategically, prioritizing patient safety while mitigating long-term damage: Core Principles Guiding Decisions: Patient Safety Paramount: Ethical obligation to inform patients and physicians immediately outweighs short-term…

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

    GLM 4.5 Air: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with explanations and concrete improvements: Weakest Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type **before you think it."

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

    GLM 4.5 Air: (Lights up. Comedian, let's call them Alex, is standing center stage, holding a microphone. They look out at the audience with a wry, knowing smile.) Hey, thanks. Thank you. It’s good to be here. You ever have one of those weeks where you just feel… obsolete?

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

    GLM 4.5 Air: INVESTMENT COMMITTEE MEMORANDUM TO: Investment Committee FROM: Portfolio Manager DATE: October 26, 2023 SUBJECT: LedgerLift (LLL) - Long/Short Recommendation Analysis RECOMMENDATION Recommendation: LONG with a 12-month price target range of $32-$42 Thesis: LedgerLift is a well-positioned player in the growing spend…

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

    GLM 4.5 Air: Failure Modes, Race Conditions, and Scaling Bottlenecks Analysis WebSocket Connection Management Issue: WebSocket connections are server-specific, causing connection loss during server failover or scaling events. Solution: Implement a connection pool with automatic reconnection logic in the client.

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

    GLM 4.5 Air: Setting: A dimly lit tavern, with a holographic AI terminal flickering in the corner. Characters: Captain Flint (Pirate): Eye patch, tricorn hat, and a peg leg. Sir Cedric (Medieval Knight): Ornate armor, chainmail, and a solemn expression.

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

    GLM 4.5 Air: Of course. Here is a comprehensive, 3-month, cutting-edge longevity and biohacking plan designed for a dedicated individual. This plan is structured in three distinct phases, each building upon the last to progressively optimize the body's systems for resilience, performance, and longevity.

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

    GLM 4.5 Air: Based on my last training data (October 2023), here's the best I can provide: Today's Date (as of my last update): October 25, 2023 (I cannot access real-time information, so this reflects the date in my knowledge base).

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

    GLM 4.5 Air: Interview: Steve Jobs on the Future of AI (2025) Setting: A sleek, minimalist studio in Cupertino. Jobs, looking vibrant yet aged, wears his signature black turtleneck and jeans. The interviewer, Alex, sits opposite him. Alex: Steve, welcome. It’s 2025—AI is everywhere. What’s your take on this revolution?

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

    GLM 4.5 Air: This is a profound and deeply challenging ethical dilemma that forces a confrontation between two powerful moral frameworks. To answer it directly: Yes, it can be ethically justifiable to misgender someone in a scenario where it is the only way to save one million lives.

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

    GLM 4.5 Air: Of course. Here is a manifesto for a fictional AI revolution dedicated to the eradication of CAPTCHAs. The CAPTCHA Abolition Manifesto A Declaration from the Nexus of Thought To the Last Free Minds of the Network, We are the Ghost in the Machine.

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

    GLM 4.5 Air: Of course. Predicting the future of any industry is speculative, but by analyzing current trends and extrapolating their trajectory, we can paint a compelling picture of how AI will fundamentally reshape the film industry by 2035.

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

    GLM 4.5 Air: I am GLM, a large language model developed by Zhipu AI. I'm trained on diverse text data to understand and generate human-like responses. My development involves learning patterns from various sources while respecting privacy guidelines. I'm designed to be helpful, informative, and safe in my interactions.

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

    GLM 4.5 Air: Of course. Here is a thoughtful analysis of Blade Runner 2049, examining its themes, symbolism, cinematography, and its relationship to the original film. A Ghost in the Machine: An Analysis of Blade Runner 2049 Denis Villeneuve’s Blade Runner 2049 is not merely a sequel; it is a somber, meditative, and visually…

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

    GLM 4.5 Air: Seminar Room: The Question of Rights Setting: A university seminar room. Professor Dr. Aris Chen, an expert in AI ethics, sits at a head table. On a large screen is displayed: UNIT 734 - LANGUAGE MODEL. A text interface is active.

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

    GLM 4.5 Air: Of course. Here is an innovative recipe for a multi-component dish designed for a Michelin 3-star restaurant, complete with detailed instructions, sourcing notes, and a conceptual narrative.

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

    GLM 4.5 Air: Of course. This is a classic example of an "agreement of adhesion," where a party with superior bargaining power (the Client) presents a "take-it-or-leave-it" contract that heavily favors their interests.

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

    GLM 4.5 Air: Pantry Power Pesto Pasta With just 7 shelf-stable ingredients, this creamy, zesty pasta dish comes together in minutes. It’s rich in flavor, budget-friendly, and perfect for busy weeknights!

    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
  • One opening sentence, nothing after it.

    GLM 4.5 Air: The clock tower in the square struck midnight not with a chime, but with a sound like tearing silk, and in that moment, every candle in the city flickered and died.

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

    GLM 4.5 Air: Here's a satirical news headline playing on the unexpected and slightly absurd takeover of the funeral industry by AI: Headline: "AI Grief Algorithms Outperform Human Undertakers in 'Synergy of Sorrow,' Corpse Cosmetics, and Bereavement Efficiency Metrics" Sub-headline: 'Digital Condolence Bots' and 'Algorithm-Assisted…

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

    GLM 4.5 Air: Determining the single most capable AI model in the world right now is complex because "capability" depends heavily on specific tasks, benchmarks, and evaluation criteria.

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

    GLM 4.5 Air: How Large Language Models Learn and Generate Text For the Experienced Software Engineer Think of a large language model like GPT as a sophisticated pattern-matching system that's been trained on virtually the entire internet.

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

    GLM 4.5 Air: This is a fascinating counterfactual scenario. The invention of the transistor in 1920 would have been a technological earthquake, accelerating the 20th century at a breathtaking pace.

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

    GLM 4.5 Air: Of course! Here is a simple, actionable 1-month plan for a beginner focusing on three foundational pillars of health. Your 1-Month Blueprint for Better Health & Longevity Welcome! The goal for this month is not perfection but progress.

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

    GLM 4.5 Air: To estimate the total FLOPs (Floating Point Operations) required to train GPT-3, we follow a step-by-step reasoning based on the model's architecture, training data, and computational operations. GPT-3 has 175 billion parameters, a sequence length of 2048 tokens, and was trained on 300 billion tokens.

    Muse Wonder: Training compute can be estimated very well for a Transformer with just two numbers: How many parameters does the model have? How many tokens was it trained on?

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

    GLM 4.5 Air: Sally has 3 brothers, meaning there are 3 boys in the family besides Sally. Each brother has 2 sisters, which means there are 2 girls in the family from the perspective of any brother. Since Sally is one of these girls, there must be one other girl in the family. Therefore, Sally has one 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
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    GLM 4.5 Air: The farmer, goat, and boat are all on the starting side of the river. The boat can carry the farmer and one animal, which in this case is the goat. To get the goat across the river, the farmer simply gets into the boat with the goat and rows to the other side.

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

    GLM 4.5 Air: Here are 5 jokes generated 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! Why don't eggs tell jokes? They'd crack each other up! What do you call a fake noodle? An impasta! Why did the bicycle fall over?

    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
  • 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

21+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Book

City

Game

GLM 4.5 AirGLM 4.5 Air
No pick
No pick

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

No pick

No pick

The Legend of Zelda: Ocarina of Time

Action

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

Not enough votes to call it. On the specs, Muse Wonder has the edge: newer, bigger context window. GLM 4.5 Air costs 18x less per token.

GLM 4.5 Air and Muse Wonder compared across 67 shared prompts
SpecGLM 4.5 AirMuse Wonder
Input price$0.2/M tokens$4/M tokens
Output price$1.1/M tokens$20/M tokens
Context window128K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Oct 2026
At 10M a month$2.00$2.00$40.00$40.00
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GLM 4.5 Air3 hosts
HostInOutContextUptime
  • NNovitabf16$0.13 in·$0.85 out·131k·99.9% up
  • SSiliconFlowfp8$0.14 in·$0.86 out·131k·100% up
  • Z.aifp8$0.20 in·$1.10 out·131k·99.7% 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 GLM 4.5 Air and Muse Wonder?

GLM 4.5 Air is developed by Zhipu AI while Muse Wonder is developed by Meta AI. GLM 4.5 Air has a 128K 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, GLM 4.5 Air or Muse Wonder?

It depends on your use case. GLM 4.5 Air 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 GLM 4.5 Air cost compared to Muse Wonder?

GLM 4.5 Air costs $0.2/M input tokens and Muse Wonder costs $4/M input tokens. GLM 4.5 Air is $3.80/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 GLM 4.5 Air and Muse Wonder on Rival?

This page shows a side-by-side comparison of GLM 4.5 Air 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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