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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs Muse Glimmer 30B
Updated Sep 2026

GPT-6.1 Sol vs Muse Glimmer 30B

Muse Glimmer 30B is cheaper than GPT-6.1 Sol at $0.3/M vs $2/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
GPT-6.1 Sol
Loading the build
Muse Glimmer 30B

Which answer wins?

Written rounds

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

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

    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.

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

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    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.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

    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…

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

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

    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...

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

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

    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.

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

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

    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.

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

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

    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.

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

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

    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.

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

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

    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.

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

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

    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.

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

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

    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.

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

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    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.

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

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    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.

    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.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    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.

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

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    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?

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

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

    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.

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

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    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.

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

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    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.

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

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    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.

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

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    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…

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

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

    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…

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

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

    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.

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

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    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.

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

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    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.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

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

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: bigger model tier, newer, bigger context window. Muse Glimmer 30B costs 8.3x less per token.

GPT-6.1 Sol and Muse Glimmer 30B compared across 54 shared prompts
SpecGPT-6.1 SolMuse Glimmer 30B
Input price$2/M tokens$0.3/M tokens
Output price$10/M tokens$1.2/M tokens
Context window1.1M tokens131K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2026
At 10M a month$20.00$20.00$3.00$3.00
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
GPT-6.1 Sol3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
  • Amazon Bedrock$2.20 in·$11.00 out·1.1M·87.2% up
Muse Glimmer 30B3 hosts
HostInOutContextUptime
  • PPhala$0.30 in·$1.10 out·131k·99.9% up
  • DDeepInfrabf16$0.30 in·$1.20 out·131k·96.8% up
  • TTogether$0.35 in·$1.50 out·131k·97.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between GPT-6.1 Sol and Muse Glimmer 30B?

GPT-6.1 Sol is developed by OpenAI while Muse Glimmer 30B is developed by Meta AI. GPT-6.1 Sol has a 1.1M token context window vs Muse Glimmer 30B's 131K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Muse Glimmer 30B?

It depends on your use case. GPT-6.1 Sol and Muse Glimmer 30B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does GPT-6.1 Sol cost compared to Muse Glimmer 30B?

GPT-6.1 Sol costs $2/M input tokens and Muse Glimmer 30B costs $0.3/M input tokens. Muse Glimmer 30B is $1.70/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 GPT-6.1 Sol and Muse Glimmer 30B on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Muse Glimmer 30B 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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