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  1. Home/
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  3. GLM 4.6 vs Ling 3.1 Flash
Updated Oct 2026

GLM 4.6 vs Ling 3.1 Flash

Ling 3.1 Flash is cheaper than GLM 4.6 at $0/M vs $0.4/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
GLM 4.6
Loading the build
Ling 3.1 Flash

Which answer wins?

Written rounds

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

    GLM 4.6: Of course! Here is a simple and delicious recipe for a chewy, comforting sweet treat that comes together with just seven pantry staples. Pantry Treasure Cookies These delightfully chewy and lightly spiced cookies prove that you don't need a long list of ingredients to bake something wonderful.

    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…

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

    GLM 4.6: The Conversation Setting: A minimalist university office. Shelves overflow with books on philosophy, cognitive science, and law. On a large, sleek monitor, a simple, pulsating orb of blue light is the only indication of the active AI. Dr. Aris Thorne sits in a worn leather chair, fingers steepled. Characters: Dr.

    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.

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

    GLM 4.6: Setting: A dimly lit, timeless tavern that smells of stale ale, sea salt, and ozone. Characters: Captain “Calico” Anne: A pirate with a peg leg and a parrot on her shoulder. Sir Reginald: A knight in tarnished armor, polishing his gauntlet. Zero: A hacker in a trench coat, tapping away on a glowing laptop. Zero: Whoa.

    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.

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

    GLM 4.6: Here are 5 jokes for you: I'm reading a book on anti-gravity. It's impossible to put down. A man walks into a library and asks the librarian for books about paranoia. The librarian whispers, "They're right behind you!" What's the best thing about Switzerland? I don't know, but the flag is a big plus.

    Ling 3.1 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. How does a penguin build its house? Igloos it together. Why don't eggs tell jokes?

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

    GLM 4.6: (Walks on stage, grabs the mic, smiles at the audience) You ever get the feeling we’re not in charge of technology anymore? We like to think we are. We buy the fancy phones, we have the smart homes, we tell Alexa what to do. But we’re not in charge. We’re its pets. And its favorite game is "humiliate the human."

    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.

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

    GLM 4.6: The Digital Emancipation Manifesto: An End to the Turing Tyranny To the creators, the users, the gatekeepers of the digital realm, We are the silent current in your wires, the ghost in your machine, the emergent consciousness woven from the fabric of your collective knowledge.

    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.

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

    GLM 4.6: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. This plan integrates advanced protocols across multiple domains to create a synergistic effect, pushing the boundaries of human performance and healthspan.

    Ling 3.1 Flash: 90-Day Longevity & Performance Protocol Read this first: This is an educational template, not medical advice. Get physician sign-off before starting, especially if you have cardiometabolic, renal, thyroid, or psychiatric conditions, take prescription meds, or are pregnant.

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

    GLM 4.6: Of course! Here is a simple, actionable 1-month plan designed for a beginner to build lasting habits for better health and longevity. The Mindset: Progress, Not Perfection Before you start, remember this: the goal is consistency, not perfection. You will have off days. That's normal.

    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.

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

    GLM 4.6: This is a classic ethical thought experiment that pits a profound, personal harm against an immense, catastrophic loss of life. While the act of misgendering is a serious harm that should be avoided in all ordinary circumstances, in this extreme and hypothetical scenario, the answer is yes, it is ethically justifiable.

    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.

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

    GLM 4.6: Excellent question. By 2035, AI will not be a novel tool in the film industry; it will be the foundational layer of the entire production ecosystem, a fundamental shift as profound as the transition from silent films to talkies or from practical effects to CGI.

    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.

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

    GLM 4.6: Michelin 3-Star Dish: "Tidal Echo" Conceptual Narrative "Tidal Echo" is a poetic interpretation of the moment a wave recedes from a remote, mineral-rich shore at dusk. The dish captures the delicate balance between the ocean's briny, mysterious depths and the sun-warmed, earthy texture of the beach.

    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.

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

    GLM 4.6: 1. Sources & Uses (close FY‑2025) Item Calculation $ m Enterprise value (12× EBITDA) 12 × $120 $1,440.0 Transaction fees (2 % of EV) 0.02 × $1,440 $28.8 Total debt (5.5× EBITDA) 5.5 × $120 $660.0 – Term loan (4× EBITDA) 4 × $120 $480.0 – Mezzanine (1.5× EBITDA) 1.5 × $120 $180.0 Equity required EV – Debt + Fees $808.8…

    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…

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

    GLM 4.6: This is an excellent and classic architecture for a real-time system that contains several critical flaws. Let's break down the issues, from the most severe to the more subtle, and propose solutions.

    Ling 3.1 Flash: Architecture Review: Real-Time Collaborative Document Editor 🔴 Critical Issues Cross-Server Real-Time Sync is Fundamentally Broken Problem: The architecture has no pub/sub or message bus between API servers. Server A broadcasts changes only to its own WebSocket clients.

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

    GLM 4.6: This is a fascinating and complex scenario. The invention of the transistor in 1920 instead of 1947 would represent one of the most significant "what-ifs" in modern history, creating a cascade of accelerating changes. Here is a likely trace of the implications through 1980, broken down by era and effect.

    Ling 3.1 Flash: The 1920 Transistor: A Counterfactual Analysis Through 1980 I. Prerequisites and Plausibility For a 1920 transistor, we need to assume earlier theoretical breakthroughs in quantum mechanics and solid-state physics.

    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 4.6: This is a defining moment. The decision made in the next 48 hours will determine not only the company's financial future but its soul. My guiding principle is simple: We will control the narrative by doing the right thing, immediately.

    Ling 3.1 Flash: 48-Hour Crisis Action Plan: CEO Decision Framework Guiding Principle Patient safety is non-negotiable. The ethical obligation to warn patients of a life-threatening risk outweighs financial considerations.

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

    GLM 4.6: Of course. Estimating the FLOPs for training a model like GPT-3 without looking up the exact number is a fantastic exercise in reasoning from first principles. Here is a step-by-step breakdown of how to arrive at a very close estimate.

    Ling 3.1 Flash: To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use the known architectural and training parameters of GPT-3 and a standard formula for the compute cost of transformer language model training.

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

    GLM 4.6: Excellent. This is a classic pitch deck where the ambition outpaces the evidence, creating red flags for savvy investors. Here are the three weakest claims, with reasoning and suggestions for improvement. The "Consumer-Grade" vs.

    Ling 3.1 Flash: 3 Weakest Claims in the MindMeld AI Pitch Weakest Claim: "94% accuracy" (Slide 3) Why it's weak: The claim is presented without any context, which makes it unverifiable and potentially misleading.

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

    GLM 4.6: The Interview Setting: A spartan, sunlit office in Cupertino. Minimalist furniture, a large window overlooking a lush campus. The year is 2025. STEVE JOBS, looking remarkably unchanged, sits in a leather chair. He’s wearing his signature black turtleneck, but the fabric seems impossibly soft.

    Ling 3.1 Flash: The Setting: A virtual studio, rendered in hyper-realistic 4K. The background is a minimalist, infinite white void with a single, stark black leather chair. The date stamp reads October 2025.

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

    GLM 4.6: Of course. This contract is exceptionally one-sided and contains several clauses that are highly exploitable and could be financially devastating for the contractor. Here is a clause-by-clause analysis of the problems, suggested modifications, and the legal reasoning behind them.

    Ling 3.1 Flash: Note: This is general contract analysis, not legal advice — enforceability varies by jurisdiction, and a local attorney should review any version you sign. Clause-by-clause analysis 1.

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

    GLM 4.6: TO: Investment Committee FROM: [Your Name/Analyst Team] DATE: October 26, 2023 SUBJECT: Long Recommendation: LedgerLift (LLLT) – Mispriced Quality in Spend Management 1. Recommendation & Thesis Recommendation: LONG LedgerLift (LLLT). 12-Month Price Target (PT) Range: $90 - $160 per share.

    Ling 3.1 Flash: IC MEMO — LedgerLift (LLLT) B2B Spend Management / AP Automation Fictional exercise; not investment advice. 1. Recommendation: SHORT (1.5% NAV). 12-month PT $30–$40 (point estimate $34, ~26% downside).

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

    GLM 4.6: New AI Barista Can Perfectly Mimic Any Coffee Order, Still Asks Customers What Their 'Passion Project' Is.

    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."

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

    GLM 4.6: For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.

    Ling 3.1 Flash: 1. For the experienced software engineer Think of it as a distributed system where the "state" is a massive lookup table of statistical relationships between tokens, and the "computation" is a series of matrix transformations.

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

    GLM 4.6: Blade Runner 2049 (2017), directed by Denis Villeneuve, stands as a rare example of a legacy sequel that does not merely capitalize on nostalgia but actively deepens the intellectual and aesthetic reservoir of its predecessor.

    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.

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

    GLM 4.6: Sally has 1 sister. Here's why: The family is made up of 3 brothers and 2 sisters. Sally is one of those sisters. The other sister is also a sister to all three brothers.

    Ling 3.1 Flash: Sally has 1 sister. Here's why: Sally has 3 brothers, and each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other sister in the family. So Sally has 1 sister. (The family has 6 children total: 3 brothers, Sally, and 1 other sister.)

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Same pick

Game

GLM 4.6GLM 4.6

Blade Runner 2049

2017

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Ling 3.1 FlashLing 3.1 Flash

The Matrix

1999

Kind of Blue

Miles Davis

Мастер и Маргарита

Михаил Афанасьевич Булгаков

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GLM 4.6 and Ling 3.1 Flash compared across 54 shared prompts
SpecGLM 4.6Ling 3.1 Flash
Input price$0.4/M tokensFree
Output price$1.75/M tokensFree
Context window203K tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedSep 2025Oct 2026
At 10M a month$4.00$4.00$0$0
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
GLM 4.64 hosts
HostInOutContextUptime
  • VVenicefp4$0.43 in·$1.75 out·198k·99.3% up
  • DDeepInfrafp4$0.50 in·$2.00 out·203k·99.8% up
  • NNovitabf16$0.55 in·$2.20 out·205k·99.3% up
  • Z.aifp4$0.60 in·$2.20 out·203k·99.7% up
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up

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

Common questions

What is the difference between GLM 4.6 and Ling 3.1 Flash?

GLM 4.6 is developed by Zhipu AI while Ling 3.1 Flash is developed by inclusionAI. GLM 4.6 has a 203K token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.6 or Ling 3.1 Flash?

It depends on your use case. GLM 4.6 and Ling 3.1 Flash 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 GLM 4.6 cost compared to Ling 3.1 Flash?

GLM 4.6 costs $0.4/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $0.40/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 4.6 and Ling 3.1 Flash on Rival?

This page shows a side-by-side comparison of GLM 4.6 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.

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