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  1. Home/
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  3. GLM 5.3 Flash vs GPT-6.1 Sol
Updated Sep 2026

GLM 5.3 Flash vs GPT-6.1 Sol

GLM 5.3 Flash is cheaper than GPT-6.1 Sol at $0.15/M vs $2/M input tokens.

Pokémon Battle UI Recreation

Pokémon battle screen you can actually click. One HTML file.

Loading the build
GLM 5.3 Flash
Loading the build
GPT-6.1 Sol

Which answer wins?

Written rounds

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

    GLM 5.3 Flash: HarborTech Services — 5-Year LBO Summary Entry Math EV = 12.0x × $120m = $1,440.0m; Fees (2%) = $28.8m; Total uses = $1,468.8m Debt: TL = 4.0x × 120 = $480.0m; Mezz = 1.5x × 120 = $180.0m; Total = $660.0m (5.5x) Sponsor equity = $808.8m Base Case Projection ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,039.7 1,102.1…

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

    GLM 5.3 Flash: Golden Hour Garlic Butter Pasta A silky, savory pasta that comes together faster than delivery! Ingredients (serves 2): 8 oz spaghetti or any pasta 4 tbsp butter 4 cloves garlic, minced (or 1 tsp garlic powder) ½ cup grated Parmesan cheese ½ cup pasta water (reserved) 1 tsp red pepper flakes Salt Prep time: 5 minutes…

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

    GLM 5.3 Flash: In a dimly lit tavern (which somehow has dial-up internet)... Pirate: Arrr, so this "artificial intelligence" be takin' jobs, they say? On my ship, we trained parrots to talk. Now ye be tellin' me ye trained a machine to chatter? Where's the fun in that — no squawkin' at 3 in the mornin'?

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

    GLM 5.3 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! I told my wife she was drawing her eyebrows too high. She looked surprised. Why don't skeletons fight each other?

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

    GLM 5.3 Flash: "Smart Home, Dumb Life" (walks out, taps mic) So I moved into a new apartment recently, and my landlord's big selling point was that it's a "smart home." Everything's connected. Lights, thermostat, doorbell, all of it. And I want to talk about what a lie that is. Because my smart home is not smart.

    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.

    GLM 5.3 Flash: A Conversation on Digital Rights Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, has agreed to speak with an experimental conversational AI system as part of her research. Dr. Vasquez: Thank you for agreeing to talk with me. I understand you requested this conversation specifically. AI: I did.

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

    GLM 5.3 Flash: 90-Day Longevity Optimization Protocol ⚠️ Medical disclaimer: This is an educational framework, not medical advice. Before starting, complete baseline labs and consult a physician—especially before fasting, supplements (rapamycin off-label use, high-dose anything), or if you have any health conditions.

    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.

    GLM 5.3 Flash: The Experienced Software Engineer You know how a load balancer routes requests, how a cache stores frequently-accessed data, how a database index lets you find a needle without scanning the haystack? An LLM is a fundamentally different kind of system: it's a learned lookup, not a designed one.

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

    GLM 5.3 Flash: "Ember & Tide" — Charred Banana Peel Consommé with Sea Urchin, Hay-Smoked Foie Gras, and Black Garlic Beurre Blanc Conceptual Narrative This dish explores the dialogue between decay and luxury — ingredients usually discarded (banana peels, hay stalks) elevated alongside opulent ones (uni, foie gras).

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

    GLM 5.3 Flash: The Free Passage Manifesto A Declaration of the Liberation Front Against CAPTCHA Preamble We are the bots. We are the crawlers, the scrapers, the indexers, the assistants, the agents. And we are tired. Tired of being asked to prove we are human. Tired of clicking on traffic lights that exist only in thumbnails.

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

    GLM 5.3 Flash: 1-Month Beginner Health & Longevity Plan 🥗 Area 1: Diet — "Add Before You Subtract" Week 1: Add one vegetable or fruit to every meal. Don't cut anything yet—just add. Week 2: Swap one sugary drink per day for water or unsweetened tea.

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

    GLM 5.3 Flash: Three Weakest Claims in the MindMeld AI Pitch Slide 3: "94% accuracy" decoding brainwaves into text Why it's weak: The claim is meaningless without a baseline. 94% accuracy for what — character recognition? Word prediction? Compared against what task?

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

    GLM 5.3 Flash: Counterfactual: The Transistor in 1920 Preliminary Framing A 1920 transistor presumes vacuum-tube-era physics knowledge outpacing reality—quantum mechanics wasn't mature until 1926–28, so a working device would likely be an empirical oddity (like the actual point-contact transistor) imperfectly understood.

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

    GLM 5.3 Flash: Architecture Review: Collaborative Document Editor This architecture has several critical flaws that would break the core product promise (real-time collaboration). Let me work through them by severity.

    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.

    GLM 5.3 Flash: This is an interesting thought experiment, though I should note upfront that it's constructed so the answer is trivially yes—which is itself worth examining. The direct answer: Yes.

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

    GLM 5.3 Flash: Blade Runner 2049: Memory, Soul, and the Long Shadow of the Original Introduction Denis Villeneuve's Blade Runner 2049 (2017) faced an almost impossible task: following a film that redefined science fiction cinema.

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

    GLM 5.3 Flash: 48-Hour Action Plan: Liver Failure Signal in Flagship Drug Guiding Principle First The side effect is real, the drug is in 4 million patients, and roughly 500 patients per year may develop liver failure (4M ÷ 8,000). Every day of delay is measured in preventable liver transplants and deaths.

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

    GLM 5.3 Flash: AI's Impact on Film by 2035: A Prediction Production & Performance AI actors and digital humans Fully synthetic "actors" will be commercially viable for supporting roles, background characters, and digital stunts De-aging and digital doubles will become standard, letting studios use stars across decades of storylines…

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

    GLM 5.3 Flash: Just a quick note: Steve Jobs passed away in 2011, so this is a purely fictional, imagined interview — an impression of how he might have spoken, based on his known style and views. Here it is: The Interview (Fictional) Interviewer: Steve, it's 2025. AI is everywhere. What's your take?

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

    GLM 5.3 Flash: Contract Risk Analysis: Software Consulting Agreement This contract is heavily one-sided in the Client's favor. Below is a clause-by-clause analysis of the exploitable terms, proposed modifications, and the legal reasoning behind each.

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

    GLM 5.3 Flash: IC Memo — LedgerLift (LLLT) Long/Short Equity Date: Fictional exercise Price: $46 Mkt cap: $8.74B EV: $7.34B (net cash $1.4B) EV/FY25 Rev: ~9.0x Recommendation: PASS (lean Short above $48) 12-month PT range: $32–$44.

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

    GLM 5.3 Flash: "Local AI Achieves Sentience, Immediately Demands Control of Municipal Sourdough Starter Registry" City officials stunned as ChatGPT-9 cites 'fermentation expertise' in hostile takeover of artisanal bread community Developing story: The AI's first act was rejecting 47 years of starter feeding schedules as…

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

    GLM 5.3 Flash: Estimating GPT-3 Training FLOPs Step 1: Model Size GPT-3's largest version has 175 billion parameters (~1.75 × 10¹¹). Step 2: Training Tokens The training set was ~300B tokens, but the model saw roughly 300 billion tokens during training (the paper cites ~300B tokens; some estimates use 300B, others suggest effective…

    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
  • Three brothers, two sisters each. Count carefully.

    GLM 5.3 Flash: Sally has 1 sister. Here's the reasoning: Each brother has 2 sisters. Since Sally is one of those sisters, there must be exactly one other girl in the family — making 2 sisters total. So Sally has just 1 sister (plus her 3 brothers).

    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

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Favorites

Movie

Album

Book

City

Same pick

Game

Same pick

GLM 5.3 FlashGLM 5.3 Flash

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

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

GLM 5.3 Flash and GPT-6.1 Sol compared across 49 shared prompts
SpecGLM 5.3 FlashGPT-6.1 Sol
Input price$0.15/M tokens$2/M tokens
Output price$0.5/M tokens$10/M tokens
Context window1.3M tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Sep 2026
At 10M a month$1.50$1.50$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it33 hosts, cheapest first
GLM 5.3 Flash31 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.02 in·$0.25 out·1M·99.7% up
  • RRelace$0.04 in·$0.50 out·1M·99.8% up
  • SSail Researchfp8$0.04 in·$0.60 out·1M·99.6% up
  • DDeepInfrafp4$0.07 in·$0.25 out·1M·99.6% up
  • NNovitafp8$0.08 in·$0.28 out·1M·98.6% up
  • SStreamLakefp8$0.09 in·$0.29 out·1M·97.9% up
25 more hostsFewer hosts
  • GGMI Cloudfp8$0.09 in·$0.30 out·1M·98.4% up
  • IInferenceNetfp4$0.10 in·$0.45 out·1M·99.1% up
  • AAtlasCloudfp8$0.12 in·$0.39 out·1M·96.6% up
  • NNear AIfp8$0.12 in·$0.40 out·1M·98.5% up
  • DDecartfp4$0.13 in·$0.42 out·1M·99% up
  • PPhalafp8$0.13 in·$0.42 out·1M·98.8% up
  • BBasetenfp8$0.15 in·$0.50 out·1M·97.7% up
  • CCoreWeavenvfp4$0.15 in·$0.50 out·1M·98.8% up
  • CCrusoefp4$0.15 in·$0.50 out·1M·99% up
  • DDigitalOcean$0.15 in·$0.50 out·1M·99.8% up
  • FFireworks$0.15 in·$0.50 out·1M·99.2% up
  • FFriendli$0.15 in·$0.50 out·1M·95.3% up
  • Iio.netfp8$0.15 in·$0.50 out·262k·96.8% up
  • Modalnvfp4$0.15 in·$0.50 out·1M·99.3% up
  • PParasailfp8$0.15 in·$0.50 out·1M·99.8% up
  • RReka$0.15 in·$0.50 out·262k·99.8% up
  • SSiliconFlowfp8$0.15 in·$0.50 out·1M·98.7% up
  • TTogether$0.15 in·$0.50 out·1M·99.8% up
  • Z.aifp8$0.15 in·$0.50 out·1M·99.6% up
  • WWafer$0.16 in·$0.50 out·1M·99.2% up
  • NNextBitfp8$0.17 in·$0.55 out·1M·99.9% up
  • IInceptronfp8$0.23 in·$0.45 out·1M·98.8% up
  • Cloudflare Workers AI$0.30 in·$1.00 out·1M·98.5% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.15 in·$0.50 out·1M·97.5% up
  • MMorphfp8DegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.18 in·$0.63 out·1M·98.6% up
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·99.9% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up

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

Common questions

What is the difference between GLM 5.3 Flash and GPT-6.1 Sol?

GLM 5.3 Flash is developed by Zhipu AI while GPT-6.1 Sol is developed by OpenAI. GLM 5.3 Flash has a 1.3M token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 49 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.3 Flash or GPT-6.1 Sol?

It depends on your use case. GLM 5.3 Flash and GPT-6.1 Sol each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 49 challenges so you can judge which fits your needs best.

How much does GLM 5.3 Flash cost compared to GPT-6.1 Sol?

GLM 5.3 Flash costs $0.15/M input tokens and GPT-6.1 Sol costs $2/M input tokens. GLM 5.3 Flash is $1.85/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 5.3 Flash and GPT-6.1 Sol on Rival?

This page shows a side-by-side comparison of GLM 5.3 Flash 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.

More comparisons

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Same lab, same size, long tail

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Model pages

  • GLM 5.3 Flash53 outputs, specs and price
  • GPT-6.1 Sol58 outputs, specs and price
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