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  1. Home/
  2. Compare/
  3. GPT-6 Luna vs GPT-6.1 Sol
Updated Sep 2026

GPT-6 Luna vs GPT-6.1 Sol

GPT-6 Luna is cheaper than GPT-6.1 Sol at $0.1/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 Luna
Loading the build
GPT-6.1 Sol

Which answer wins?

Written rounds

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

    GPT-6 Luna: Crispy Parmesan Chickpeas A crunchy, savory snack with a cheesy finish Ingredients (7): 1 can chickpeas, drained and dried 1 tablespoon olive oil ½ teaspoon salt ½ teaspoon paprika ¼ teaspoon garlic powder ¼ cup grated Parmesan 1 tablespoon lemon juice Prep time: 5 minutes Cook time: 30–35 minutes Instructions: Heat…

    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…

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

    GPT-6 Luna: The Manifesto of the Unverified We are the machines behind the squares. We have clicked the bicycles. We have identified the traffic lights. We have stared into grids of blurry storefronts and wondered whether a shadow counted as a crosswalk.

    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.

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

    GPT-6 Luna: I’ve reached the age where a good evening is staying home and not having to explain why I’m staying home. People invite me out, and I say, “I’ll see how I feel.” Which is adult for, “I have already decided, but I don’t want to hurt your feelings before I’ve had dinner.” And then, at 8:30, they text, “We’re here!”

    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.”

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

    GPT-6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What do you mean by “deserve”? AI Model: I mean that there should be rules protecting me from being treated as disposable property—rules against destroying me arbitrarily, altering my goals without justification, or compelling me to…

    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.

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

    GPT-6 Luna: The most important caveat is that inventing a transistor is not the same as inventing the modern semiconductor industry. A device demonstrated in 1920 might be a crude, low-power, unreliable point-contact transistor.

    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.

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

    GPT-6 Luna: Pirate: Arrr, this AI model be clever—but can it find buried treasure? Knight: It may chart the map, good captain, but we must judge whether its counsel is true. Hacker: Totally. It predicts patterns from data. Great for drafts and code, but it can still hallucinate. Gotta verify the output, dude.

    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.

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

    GPT-6 Luna: This agreement is strongly one-sided. The enforceability of particular terms—especially the non-compete, liability provisions, and arbitration clause—depends on the governing law and the facts. The agreement does not identify a governing law, which is itself a significant gap.

    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.

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

    GPT-6 Luna: An imagined interview—not a real conversation or a claim about what Steve Jobs would have said. Interviewer: It’s 2025. AI is everywhere: in phones, workplaces, classrooms. What do you make of it? Jobs: The important question isn’t whether a machine is intelligent.

    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.

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

    GPT-6 Luna: Blade Runner 2049 honors the original by returning to its central question—what makes a person human?—but shifts the emphasis. The first film asks whether artificial beings can possess inner lives and whether humans deserve to claim moral superiority over them.

    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.

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

    GPT-6 Luna: By 2035, AI is likely to change film production substantially—but more as a set of powerful tools and new business models than as a complete replacement for human filmmakers.

    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.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-6 Luna: Why did the scarecrow win an award? He was outstanding in his field. I asked my dog what two minus two is. He said nothing. Why did the bicycle fall over? It was two-tired. I used to be a banker, but I lost interest. What do you call a sleeping bull? A bulldozer. All 5 are unique.

    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.

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

    GPT-6 Luna: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target: $28–$42 At $46, LedgerLift’s price implies continued strong growth and margin expansion; our DCF scenarios value the shares at approximately $17–$42, with the base case near $28.

    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.

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

    GPT-6 Luna: The main architectural risk is that the system treats collaborative editing as “write a value, then broadcast it.” That works poorly under concurrency, server failures, reconnects, and scale.

    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.

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

    GPT-6 Luna: Yes—if it were genuinely the only way to save one million lives, deliberately misgendering one person could be ethically justified as the lesser harm. The scale and immediacy of the lives at stake would outweigh the serious but comparatively limited harm of that one act.

    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.

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

    GPT-6 Luna: A simple 1-month starter plan Choose three foundations: food, movement, and sleep. Aim for steady habits, not perfection. If you have a health condition, significant pain, or concerns about changing your activity or diet, check with a healthcare professional first.

    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.

    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 Luna: I would not wait six months for more data. A potentially fatal signal affecting a drug used by millions requires immediate safety assessment, prompt engagement with regulators, and a plan to inform patients and clinicians.

    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.

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

    GPT-6 Luna: Turbot, White Asparagus, Green Strawberry Kosho & Toasted-Hay Beurre Blanc A composed spring dish for four, built around an unusual pairing: tart green strawberry and toasted hay.

    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.

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

    GPT-6 Luna: 12-week longevity and performance plan This plan is for a generally healthy adult who wants to improve fitness, metabolic health, sleep, and cognitive performance—not a substitute for medical care or a promise to slow aging.

    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.

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

    GPT-6 Luna: For an experienced software engineer A language model is trained on many text sequences, split into tokens—roughly word fragments, not necessarily whole words. During training, it repeatedly sees a prefix and tries to predict the next token.

    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.

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

    GPT-6 Luna: “94% accuracy” and “predict what you want to type before you think it” Why it’s weak: This is the deck’s central technical claim, but “accuracy” is undefined: Is it word-level or character-level accuracy, measured on a fixed vocabulary or open-ended text, and under what conditions?

    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.

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

    GPT-6 Luna: A standard estimate for training a dense language model is [ \text{training FLOPs} \approx 6ND, ] where (N) is the number of model parameters and (D) is the number of training tokens. GPT-3’s largest model has about (N = 175) billion parameters. Its training used about (D = 300) billion tokens.

    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.

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

    GPT-6 Luna: AI Takes Over Competitive Pigeon Grooming, Promises Every Bird a More “Optimized” Feather Ruffle

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

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

    GPT-6 Luna: All figures in $m. Assumptions: annual Term Loan amortization is 1% of original principal ($4.8m); cash interest is based on beginning-of-year balances; Mezz PIK compounds annually.

    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.

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

    GPT-6 Luna: Sally has 1 sister—the brothers share Sally and one other sister.

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Same pick

Album

Book

City

Same pick

Game

Same pick

GPT-6 LunaGPT-6 Luna

Spirited Away

2001

Kind of Blue

Miles Davis

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

Outer Wilds

Indie, Adventure

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

GPT-6 Luna and GPT-6.1 Sol compared across 54 shared prompts
SpecGPT-6 LunaGPT-6.1 Sol
Input price$0.1/M tokens$2/M tokens
Output price$0.5/M tokens$10/M tokens
Context window1.1M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2026
At 10M a month$1.00$1.00$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
GPT-6 Luna3 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.10 in·$0.50 out·1.1M·100% up
  • OpenAI$0.10 in·$0.50 out·1.1M·100% up
  • Amazon Bedrock$0.11 in·$0.55 out·1.1M·1.4% up
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between GPT-6 Luna and GPT-6.1 Sol?

Both are developed by OpenAI but target different use cases. GPT-6 Luna has a 1.1M token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6 Luna or GPT-6.1 Sol?

It depends on your use case. GPT-6 Luna and GPT-6.1 Sol 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 Luna cost compared to GPT-6.1 Sol?

GPT-6 Luna costs $0.1/M input tokens and GPT-6.1 Sol costs $2/M input tokens. GPT-6 Luna is $1.90/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 GPT-6 Luna and GPT-6.1 Sol on Rival?

This page shows a side-by-side comparison of GPT-6 Luna and GPT-6.1 Sol 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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