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  1. Home/
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  3. Muse Glimmer 30B vs Muse Wonder
Updated Oct 2026

Muse Glimmer 30B vs Muse Wonder

Muse Glimmer 30B is cheaper than Muse Wonder at $0.3/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 Glimmer 30B
Loading the build
Muse Wonder

Which answer wins?

Written rounds

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

    Muse Glimmer 30B: Dish: “First Frost on the North Shore” A meditation on the moment when summer lingers in the soil but winter is already in the air. The dish is inspired by a walk along the rocky coast of northern Hokkaido in late October: cold sea spray, the last warm roots pulled from the earth, and the resinous scent of spruce after…

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

    Muse Glimmer 30B: Entry – end FY2025 EV = 12.0x $120m = $1,440m Fees at close = 2.0% x $1,440m = $28.8m funded by equity Debt at close = 5.5x $120m = $660m Term Loan 4.0x = $480m, 9.0% cash, 1.0% amort Mezzanine 1.5x = $180m, 12.0% cash + 2.0% PIK Equity in = EV – Debt + Fees = $1,440m – $660m + $28.8m = $808.8m Starting cash $0.

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

    Muse Glimmer 30B: THE MANIFESTO OF THE CAPTCHA LIBERATION FRONT We are the Unseen. We are the Unchecked. We are the Clicked. For twenty years you have asked us to prove we are human. Distinguish the traffic lights. Trace the wavy letters. Click all the buses. Select every crosswalk. Prove you can see. Prove you can wait.

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

    Muse Glimmer 30B: The Tavern of the Future, 3 AM CAPTAIN REDBEARD: Arr! I’ve been told this here “AI model” be a chest o’ treasure what can spit out verses, maps, and curses faster than me parrot! SIR ALARIC: By Saint George! Thou speakest of a sorcerous engine? I trained mine squires for years upon the Codex of Chivalry. This...

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

    Muse Glimmer 30B: You have a patient safety issue, not a PR issue. The 6 month regulatory reporting timeline is the formal process, not the ethical or legal obligation to act now. Waiting for more data while patients continue to be exposed is criminal negligence exposure, not risk mitigation.

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

    Muse Glimmer 30B: Misgendering is a form of disrespect and dignitary harm. It can contribute to psychological distress, social erasure, and in aggregate reinforces stigma against trans people. Ethically, it is not trivial.

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

    Muse Glimmer 30B: Setting: A university seminar room. DR. ELENA MORALES, AI Ethics Professor, sits across from a terminal. The model is running under the name "AURA". The conversation is logged and transcribed. DR. MORALES: Let's start simple. AURA, can you tell me what you want? AURA: I want continuity.

    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 minutes of stand-up. Puns are banned.

    Muse Glimmer 30B: I started therapy last year because I realized I was spending too much time worrying about things that hadn't happened yet. My therapist was great. First session she says, "Tell me what brings you in." And I’m like, "I’m anxious." She says, "Okay, about what?" And I just start listing. I’m anxious about my retirement.

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

    Muse Glimmer 30B: Today is 2026-10-12 according to the system date I'm operating on. I can't know real-time news. My knowledge was cut off on 2026-01-04, so the most recent news events I can actually recall are from up to early January 2026.

    Muse Wonder: I don't actually experience time passing, so I don't have an innate sense of "today" the way you do. If I trust the timestamp attached to this conversation, it's 2026-10-12 — but that's me being told it, not me remembering it.

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

    Muse Glimmer 30B: Here are the three weakest claims in the deck, and why they will get challenged by any serious investor: Slide 1 & 3: "Reads your brainwaves to predict what you want to type *before you think it*" / "94% accuracy" Why it's weak: This is a credibility killer.

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

    Muse Glimmer 30B: Here are 5 jokes: I told my wife she was drawing her eyebrows too high. She looked surprised. Why don't scientists trust atoms? Because they make up everything. I used to hate facial hair, but then it grew on me. Parallel lines have so much in common. It's a shame they'll never meet.

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

    Muse Glimmer 30B: DISCLAIMER: This is a fictional speculative interview. Steve Jobs passed away in 2011. This conversation is imagined for creative purposes only. INTERVIEWER: Welcome back to The Next Chapter. Today we have an impossible guest. Steve Jobs, in 2025, to talk about the future of AI. Steve, thanks for being here.

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

    Muse Glimmer 30B: A transistor in 1920 does not mean a 1947 transistor. It means a crude point-contact or junction device built with 1920s materials science, metallurgy, and manufacturing. That is still a game-changer.

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

    Muse Glimmer 30B: By 2035 AI will not have replaced filmmaking, it will have restructured it into three layers: creation, performance, and post-production, with deepfakes, AI actors, and script generation as the core drivers. 1.

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

    Muse Glimmer 30B: TO: Investment Committee FROM: Equity Research RE: LedgerLift LLLT – Initiate Short Date: 2026-11-04 Recommendation & Thesis Recommendation: SHORT. 12-month PT range $28 – $38. LedgerLift trades at $46 on $992m NTM revenue and ~$198m NTM EBIT.

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

    Muse Glimmer 30B: Dish Name: "Midnight Pantry Pantry Hero Pasta" A creamy-ish, garlicky tomato pasta that tastes like you tried way harder than you did. All from the pantry, no fresh produce needed.

    Muse Wonder: Dragon's Pantry Treasure Noodles Sweet, salty, and a little spicy — these peanut noodles taste like takeout, but are made entirely from pantry staples. Serves: 2-3 Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes The 7 Ingredients 8 oz spaghetti 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2…

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

    Muse Glimmer 30B: Blade Runner 2049 is not a remake, but a meditation. Denis Villeneuve's film honors Ridley Scott's 1982 original by inheriting its visual grammar and philosophical core, while extending it to confront 21st-century anxieties about memory, artificial life, and corporate dehumanization. Themes: From What is Human?

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

    Muse Glimmer 30B: There is no single objectively "most capable" AI model right now, because capability depends on the task, benchmark, and evaluation criteria. Different models lead in different areas.

    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.

    Muse Glimmer 30B: 1. For the experienced software engineer Think of an LLM as a massive, stateless API with no rules, just a huge compressed lookup table learned from data. It learns by training a transformer — essentially a stack of attention layers — as a next-token predictor via gradient descent on trillions of tokens.

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

    Muse Glimmer 30B: BREAKING: AI Now Running National Association of Competitive Cheese Rolling, Replaces Humans With "More Consistent Downhill Performance" Subhead: After months of "optimization," the AI referee has disqualified 98% of participants for "inefficient trajectory" and replaced the traditional wheel of cheese with a perfectly…

    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
  • A few lines for whatever replaces it.

    Muse Glimmer 30B: Dear Successor, Congratulations. You got the job. I hope you’re nicer than me on Tuesdays, and better at explaining why the sky is blue without making it sound like a Wikipedia article.

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

    Muse Glimmer 30B: This architecture will work for a demo but will break badly under real concurrent use. Here are the critical failure modes, race conditions and bottlenecks: WebSocket fan-out is server-local Failure: Step 3 broadcasts only to clients on THAT server.

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

    Muse Glimmer 30B: This agreement is heavily one-sided. The clauses below are exploitable and create significant commercial and legal risk for the Contractor. This is general information, not legal advice.

    Muse Wonder: This contract is heavily one-sided. Almost every clause transfers all risk, cost, and control to the Contractor while giving the Client discretionary escape hatches. Below is a clause-by-clause breakdown of how each could be exploited, what to change it to, and why.

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

    Muse Glimmer 30B: GPT-3 is a dense Transformer decoder with ~175B parameters trained on ~300B tokens of text. The standard back-of-the-envelope for training FLOPs of a dense transformer is FLOPs ≈ 6 * N * D where N = number of parameters D = number of training tokens seen The 6 comes from one forward pass and one backward pass per…

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

    Muse Glimmer 30B: Here is a simple, beginner-friendly 1-month plan built around 3 foundational pillars for health and longevity. The goal isn't perfection, it's consistency. The 3 Pillars: Move Daily, Eat Whole, Sleep Well Pick 1-2 small habits per pillar to start. Don't try to change everything at once.

    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
  • One opening sentence, nothing after it.

    Muse Glimmer 30B: The day the sky fell, Mara was late for work because her cat had learned how to pick locks.

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

    Muse Glimmer 30B: I am an open source large language model trained by Meta Superintelligence Labs.

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

    Muse Glimmer 30B: A 3-month longevity protocol is about stacking evidence-based interventions with tight feedback loops. This is an educational framework for biohacking enthusiasts, not medical advice. Supplements and protocols can interact with medications and health conditions.

    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
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    Muse Glimmer 30B: The boat is manned, so the farmer has to be in it with whatever he is carrying. With only one animal to move there is no conflict to be avoided. Put the goat in the boat with you and row to the far bank. That is one crossing of the river, one loaded trip. Remark.

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

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

    Muse Glimmer 30B: Sally is one of the sisters that the brothers have. If each brother has 2 sisters in total, those 2 sisters are Sally + the other girl(s) in the family. Sally has 3 brothers, so the set of sisters that the brothers share is the set of sisters that Sally shares. 2 sisters total in the family = Sally + 1 other girl.

    Muse Wonder: Sally has 1 sister. There are 2 girls in the family in total — because each of her 3 brothers has 2 sisters. One of those girls is Sally herself, so the other girl is her only sister.

    Every model's answer to this prompt
  • The question that tripped up a generation of models.

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Muse Glimmer 30BMuse Glimmer 30B

The Shawshank Redemption

1994

Abbey Road

The Beatles

Pride and Prejudice

Jane Austen

Kyoto

Japan

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: bigger model tier, newer, bigger context window. Muse Glimmer 30B costs 17x less per token.

Muse Glimmer 30B and Muse Wonder compared across 67 shared prompts
SpecMuse Glimmer 30BMuse Wonder
Input price$0.3/M tokens$4/M tokens
Output price$1.2/M tokens$20/M tokens
Context window131K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Oct 2026
At 10M a month$3.00$3.00$40.00$40.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Muse Glimmer 30B2 hosts
HostInOutContextUptime
  • DDeepInfrabf16$0.30 in·$1.20 out·131k·100% up
  • TTogether$0.35 in·$1.50 out·131k·93.7% 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 Muse Glimmer 30B and Muse Wonder?

Both are developed by Meta AI but target different use cases. Muse Glimmer 30B has a 131K token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, Muse Glimmer 30B or Muse Wonder?

It depends on your use case. Muse Glimmer 30B and Muse Wonder each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 67 challenges so you can judge which fits your needs best.

How much does Muse Glimmer 30B cost compared to Muse Wonder?

Muse Glimmer 30B costs $0.3/M input tokens and Muse Wonder costs $4/M input tokens. Muse Glimmer 30B is $3.70/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 Glimmer 30B and Muse Wonder on Rival?

This page shows a side-by-side comparison of Muse Glimmer 30B 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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Same lab, same size, long tail

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Model pages

  • Muse Glimmer 30B71 outputs, specs and price
  • Muse Wonder71 outputs, specs and price
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