GLM 5.3 Flash is cheaper than GPT-6.1 Sol at $0.15/M vs $2/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
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.
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…
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.
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.
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.”
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.
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.
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.
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.
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.
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.
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.
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| Spec | ||
|---|---|---|
| Input price | $0.15/M tokens | $2/M tokens |
| Output price | $0.5/M tokens | $10/M tokens |
| Context window | 1.3M tokens | 1.1M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Sep 2026 |
| At 10M a month | $1.50 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
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.
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.
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.
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.