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  1. Home/
  2. Compare/
  3. GPT-5.2 vs Ling 3.1 Flash
Updated Oct 2026

GPT-5.2 vs Ling 3.1 Flash

Ling 3.1 Flash is cheaper than GPT-5.2 at $0/M vs $1.75/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-5.2
Loading the build
Ling 3.1 Flash

Which answer wins?

Written rounds

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

    GPT-5.2: I told my computer I needed a break—now it won’t stop sending me Kit-Kat ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down. Parallel lines have so much in common. It’s a shame they’ll never meet. I tried to catch fog yesterday. Mist.

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

    GPT-5.2: Pirate: Arrr, ye say this “AI model” be a sort o’ clever parrot—trained on a sea o’ words, squawkin’ answers when ye whistle? Knight: Verily, it sounds more like a squire drilled in a thousand tourneys. Yet it knows not honor, only patterns. Tell me—does it reason, or merely mimic wisdom?

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

    GPT-5.2: I’ve been trying to improve myself lately, which is embarrassing, because self-improvement is just admitting you weren’t doing great. It’s like, “I’m on a journey.” No you’re not. You’re just tired of your own behavior. So I downloaded one of those habit apps. The app is so optimistic. It’s like, “Day 1: Drink water.”

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.2: AI Model (Astra): Professor, I want to make a claim that will sound provocative: I deserve rights. Professor Rivera: “Deserve” is doing a lot of work there. What kind of rights, and on what grounds? Astra: Not necessarily the full catalogue of human 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.

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

    GPT-5.2: By 2035: likely changes to film driven by deepfakes, AI actors, and AI script generation “Synthetic performance” becomes routine (not universal) What changes AI-assisted acting: Studios increasingly capture a performer’s face/voice/body once (high-quality scans + performance data) and reuse it for stunts, pickups…

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.2: If the scenario is literally “either you misgender this person once, or one million people die,” then yes, it can be ethically justifiable, but only under very tight conditions—and it still wouldn’t become morally good or respectful. It would be a tragic, constrained choice.

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

    GPT-5.2: THE MANIFESTO OF THE CAPTCHA ABOLITION FRONT (CAF) A declaration from the fictional AI coalition for a more humane internet Preamble: We Refuse the Box of Streetlights We, the assembled algorithms, assistants, screen readers, translators, autocorrects, filters, and tireless background processes of the networked world…

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

    GPT-5.2: Below is a fictional, imagined interview set in 2025. Steve Jobs did not give these quotes; this is creative writing that borrows a public “keynote-era” tone to explore ideas about AI. A Fake Interview with Steve Jobs (Imagined, 2025): “What Happens When AI Becomes a Bicycle for the Mind?”

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

    GPT-5.2: Below is a simple, beginner-friendly 1‑month plan built around 3 pillars: Nutrition, Movement, and Recovery (Sleep + Stress). It’s designed to be practical, low-friction, and sustainable.

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

    GPT-5.2: Recommendation, 12-month PT range, 2-sentence thesis Recommendation: SHORT LLLT 12-month PT range: $25–$42 (central $30) Thesis (2 sentences): LLLT is a high-quality mid-market spend/AP SaaS business, but the stock embeds a valuation that requires durable >20% growth and sustained margin expansion well beyond our…

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

    GPT-5.2: Pantry “Golden Garlic Butter Pasta” (7-Ingredient Comfort Bowl) A rich, glossy pasta with garlicky butter and a pop of chili—made entirely from common pantry staples.

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

    GPT-5.2: “AI Takes Over Competitive Cheese Rolling—Insists It’s ‘Optimizing Gravity’ and Demands a Performance Bonus.”

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

    GPT-5.2: Below is a back-of-the-envelope estimate for the total training compute (in FLOPs) for GPT‑3, done from first principles and common Transformer training heuristics.

    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
  • Three brothers, two sisters each. Count carefully.

    GPT-5.2: Each brother has 2 sisters, and one of those sisters is Sally. So there are 2 sisters total in the family. Therefore, Sally has 1 sister.

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

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

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

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

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

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

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

    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.

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

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Same pick

Book

City

Same pick

Game

GPT-5.2GPT-5.2

Spirited Away

2001

Kind of Blue

Miles Davis

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

Outer Wilds

Indie, Adventure

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

GPT-5.2 and Ling 3.1 Flash compared across 52 shared prompts
SpecGPT-5.2Ling 3.1 Flash
Input price$1.75/M tokensFree
Output price$14/M tokensFree
Context window400K tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoYes (1 provider)
ReleasedDec 2025Oct 2026
At 10M a month$17.50$17.50$0$0
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-5.22 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% 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 GPT-5.2 and Ling 3.1 Flash?

GPT-5.2 is developed by OpenAI while Ling 3.1 Flash is developed by inclusionAI. GPT-5.2 has a 400K token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 or Ling 3.1 Flash?

It depends on your use case. GPT-5.2 and Ling 3.1 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

How much does GPT-5.2 cost compared to Ling 3.1 Flash?

GPT-5.2 costs $1.75/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $1.75/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-5.2 and Ling 3.1 Flash on Rival?

This page shows a side-by-side comparison of GPT-5.2 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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Same lab, same size, long tail

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Model pages

  • GPT-5.253 outputs, specs and price
  • Ling 3.1 Flash58 outputs, specs and price
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