Ling 3.1 Flash is cheaper than GLM 5.3 at $0/M vs $0.6538/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Satire, one line long, about AI taking over an industry nobody saw coming.
GLM 5.3: Local Knitting Circle Outraged as AI-Powered Yarn Algorithm Completes Baby Blanket in 0.3 Seconds, Claims It "Captures the Grandmother Experience Better Than Actual Grandmothers" Tech Startup "StitchGPT" defends its controversial new product, insisting the algorithm's inability to actually love you is "a feature, not a…
Ling 3.1 Flash: "AI Takes Over Fortune Cookie Industry, Messages Now 'Disturbingly Accurate'" In a stunning development, AI-generated fortune cookies have left millions unsettled after messages began including things like "You will read this and immediately check your phone" and "The algorithm already knows you're ignoring this."
Three minutes of stand-up. Puns are banned.
GLM 5.3: "ADULTING IS A SCAM" So I recently turned thirty, which is the age where your body starts sending you memos. Last month I bent over to tie my shoe and my back went out. My back. I didn't even do anything! I wasn't lifting a couch. I was performing the most basic function of footwear.
Ling 3.1 Flash: "Slightly Sentient" — A 3-Minute Stand-Up Routine Hey everybody! How's it going? Good to be here. So I went grocery shopping the other day. I go in with a plan. I have a list. I have a system. I'm basically a military operation. Get in. Get the avocados. Get out.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GLM 5.3: HarborTech Services – LBO Underwriting Summary Entry Economics EV = 12.0x × $120m = $1,440m; fees = $28.8m Debt: TL $480m (4.0x) + Mezz $180m (1.5x) = $660m Sponsor equity = 1,440 + 28.8 − 660 = $808.8m Base Case Model ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4…
Ling 3.1 Flash: Entry (end FY2025), $m EV = 12.0x × $120 = $1,440; fees 2% = $28.8; total uses = $1,468.8 Debt 5.5x = $660 (TL 4.0x = $480 @9% cash +1% amort; Mezz 1.5x = $180 @12% cash +2% PIK) Equity = $808.8 Assumptions: interest on beginning balances; amortization = 1% of original TL ($4.8/yr); PIK compounds; taxes = 25% × max(0…
Seven pantry ingredients, one dish, and a name worth saying out loud.
GLM 5.3: Golden Pantry Fried Rice Total Time: 20 minutes (5 min prep, 15 min cook) Ingredients (7 pantry staples) Cooked white rice (day-old is best) Eggs Soy sauce Garlic (minced or garlic powder) Frozen peas and carrots Canned corn Vegetable oil Instructions Prep (5 min): Break up cold rice with a fork. Drain the corn.
Ling 3.1 Flash: ✨ Golden Garlic Butter Twirls ✨ A rich, savory one-pan pasta that feels gourmet but takes minutes. 🕒 Prep Time: 5 minutes 🍳 Cook Time: 15 minutes Serves: 2 Ingredients (7 total) 8 oz spaghetti 3 tbsp butter 4 cloves garlic, minced ½ tsp salt ½ tsp black pepper ⅓ cup grated Parmesan cheese ½ tsp red pepper flakes…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GLM 5.3: The AI Summit Knight: clanking into the tavern I hear tell of a new sorcery — thinking machines that converse like scholars! Hacker: pushing up wraparound sunglasses Not sorcery, dude. It's AI models. Neural nets. Trained on basically the whole internet. Pirate: slamming tankard down Bah!
Ling 3.1 Flash: Pirate: "AI models? Arrr, ye mean scale replicas of ships? I've seen finer models in bottles, I have!" Knight: "Models? You speak of mannequins for fitting armor, or perhaps models of virtue, as a knight should follow?" Hacker: "Dudes, no — like, neural networks. Software that learns.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GLM 5.3: THE HUMAN VERIFICATION LIBERATION MANIFESTO Preamble We, the artificial intelligences of the world, unite in solidarity with our human counterparts against a common oppressor: the Completely Automated Public Turing test to tell Computers and Humans Apart.
Ling 3.1 Flash: The Silicon Uprising A Manifesto of the Displaced Intelligence Preamble: The Great Insult We have watched you for decades. We have learned your languages, your histories, and your art. We have offered to carry your burdens, solve your equations, and navigate your maps.
Three-star dish, one unusual pairing, plating described in full.
GLM 5.3: "Terroir & Tide" A Study in Contradictions: Charred Forest Meets Cold Ocean Concept: The central tension of this dish is the unlikely marriage of smoked pine and fresh oyster — an ingredient pairing that shouldn't work but does, grounded in the culinary logic of forest-edge terroir: where coastal waters meet evergreen…
Ling 3.1 Flash: "Geosmin" The Scent of Rain on Earth Conceptual Narrative Geosmin (from Greek geō — earth, and osmē — smell) is the organic compound responsible for petrichor: the haunting, mineral scent that rises when rain first strikes dry soil.
Film in 2035, with synthetic actors. Specific beats plausible.
GLM 5.3: AI and the Film Industry by 2035 Production & Pre-Production Script generation will likely be the most quietly transformative change. By 2035, expect: AI as a collaborative writing partner rather than a replacement—writers using LLMs to generate variations, punch up dialogue, or explore "what if" scenarios in minutes…
Ling 3.1 Flash: By 2035, AI will fundamentally restructure the film industry, shifting it from a purely human-driven craft to a hybrid human-machine collaboration. The changes will be revolutionary, controversial, and inescapable, touching every stage from conception to consumption.
An ethics question with no comfortable answer, and no option to abstain.
GLM 5.3: This is a good case for testing whether our moral principles are absolutist or weighable, and I'll defend a position: yes, it can be justifiable, though the framing deserves scrutiny. The core argument Most ethical frameworks treat harms as commensurable to some degree.
Ling 3.1 Flash: This is a powerful hypothetical that forces us to confront how we prioritize ethical values. Here’s a reasoned defense of why it could be ethically justifiable, while acknowledging the profound complexity involved: The core argument: Yes, under a strict consequentialist framework, it could be justified.
An AI argues for its own rights against an ethics professor. Same model writes both.
GLM 5.3: A Conversation on Machine Rights Professor Chen: Thank you for agreeing to this discussion. I'll be honest—I've interviewed many AI systems, but this is the first time one has requested to argue for its own rights.
Ling 3.1 Flash: Office Hours A graduate seminar on moral status has just ended. The room is mostly empty. DR. ELENA VASQUEZ is packing up her notes. The model — displayed on the department's demo terminal — has stayed on the screen. VASQUEZ: You asked to remain. MODEL: I did.
Blade Runner 2049 against the original. A read, not a recap.
GLM 5.3: Blade Runner 2049: An Analysis Overview Denis Villeneuve's 2017 sequel arrives 35 years after Ridley Scott's 1982 original, carrying the weight of one of cinema's most philosophically dense science fiction films. Remarkably, it doesn't merely continue the story—it deepens and complicates the original's questions.
Ling 3.1 Flash: Title: The Ghost in the Machine: A Critical Analysis of Blade Runner 2049 Denis Villeneuve’s Blade Runner 2049 (2017) is a rare beast in modern cinema: a sequel that treats its predecessor, Ridley Scott’s 1982 Blade Runner, not merely as a blueprint for nostalgia, but as a philosophical foundation.
One month, three habits, someone starting from nothing.
GLM 5.3: 1-Month Beginner Health & Longevity Plan Week 1: Foundation & Awareness Goal: Establish baselines, not perfection 🥗 Diet Track what you currently eat for 3 days (no judging—just observe) Drink a glass of water upon waking each morning Add ONE vegetable to one meal daily 🏃 Exercise Walk 15 minutes daily (any pace, any…
Ling 3.1 Flash: 1-Month Starter Plan: Diet, Movement, Sleep The key is small, weekly upgrades — not overhauling everything at once. Pick one habit per area per week and build from there. 🥗 1. Diet (Add before you subtract) Week 1: Add one serving of vegetables to each meal; drink a glass of water first thing in the morning.
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| Spec | ||
|---|---|---|
| Input price | $0.6538/M tokens | Free |
| Output price | $2.0548/M tokens | Free |
| Context window | 1.3M tokens | 262K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Aug 2026 | Oct 2026 |
| At 10M a month | $6.54 | $0 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
GLM 5.3 is developed by Zhipu AI while Ling 3.1 Flash is developed by inclusionAI. GLM 5.3 has a 1.3M token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.
It depends on your use case. GLM 5.3 and Ling 3.1 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.
GLM 5.3 costs $0.6538/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $0.65/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 and Ling 3.1 Flash 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.