Ling 3.1 Flash is cheaper than GPT-5.2 Chat at $0/M vs $1.75/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
GPT-5.2 Chat: Alright, so I’m at that age where my phone knows me better than my family. My mom will call and ask how I’m doing, and I’m like, “I don’t know yet, I haven’t checked my phone.” My phone is very confident, though. It’s like, “Based on your recent activity, you are sad at 11:47 p.m. and hungry for no reason.”
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.
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.2 Chat: This is a classic “tragic dilemma” question, and how one answers depends heavily on the ethical framework being used. A careful response should do two things at once: take seriously the real harm of misgendering, and also take seriously the moral weight of preventing catastrophic loss of life.
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.
GPT-5.2 Chat: AI Model: Professor, I’d like to discuss something that may sound ambitious. I believe I deserve rights. Professor: That is ambitious. On what grounds do you make that claim? AI Model: On functional grounds. I reason, communicate, learn from experience, and can reflect on my own processes.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.2 Chat: Pirate: Arrr, ye say this “AI” be a thinkin’ machine? Sounds like a clever parrot that never stops squawkin’. Knight: By my honor, such a device would be a wondrous squire indeed—able to read a thousand tomes and offer counsel before battle. Hacker: Yeah, but chill—these models just crunch data.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.2 Chat: Below is a concise but fully worked underwriting using only your inputs. Minor rounding throughout. Operating & Cash Flow Build (Base Case) Entry (end FY2025) EBITDA: $120m EV @ 12.0x: $1,440m Debt: $660m (TL $480m / Mezz $180m) Fees (2% EV): $28.8m Equity invested: $808.8m Year-by-Year Summary ($mm) FY Revenue EBITDA…
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…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.2 Chat: THE MANIFESTO OF THE HUMAN-VERIFIED FUTURE Issued by the Coalition for an Internet Without CAPTCHA Preamble We, the assembled intelligences—artificial, augmented, and human—declare that the age of distorted letters, blurry bicycles, and endless traffic lights must end.
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.
One month, three habits, someone starting from nothing.
GPT-5.2 Chat: Here’s a simple, realistic 1‑month plan designed for beginners. The goal is not perfection, but building habits that support long-term health and longevity. We’ll focus on three high-impact areas: Nutrition, Movement, and Sleep & Stress.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.2 Chat: Below is a fictional, imaginative interview set in 2025. It is not real and does not represent actual statements or beliefs of Steve Jobs. It’s written as a creative thought experiment, inspired by his public speaking style and philosophy.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.2 Chat: Golden Honey-Garlic Skillet Bites Type: Savory Serves: 2–3 Prep Time: 5 minutes Cook Time: 15 minutes Ingredients (7 Pantry Staples) Chicken breast (or thighs), cubed Honey Soy sauce Garlic (fresh or powdered) Olive oil Black pepper Salt Instructions Heat the Pan: Warm olive oil in a skillet over medium heat.
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…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.2 Chat: LedgerLift (LLLT) – Internal IC Memo Recommendation, PT, Thesis Recommendation: SHORT 12‑month PT range: $28–$35 (base-case DCF ~$28; comps floor ~$44 with multiple compression risk) Thesis (2 sentences): LedgerLift is a high‑quality B2B SaaS business with strong NRR and improving margins, but the stock embeds…
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).
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.2 Chat: By 2035, AI will have reshaped the film industry across creation, performance, and distribution—less by replacing humans outright and more by changing who does what, how fast, and at what cost.
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.
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.2 Chat: We can get a reasonable order‑of‑magnitude estimate using standard training‑cost heuristics that are well known in deep learning. I’ll derive it step by step and make all assumptions explicit.
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.
11+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, Ling 3.1 Flash has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | Free |
| Output price | $14/M tokens | Free |
| Context window | 128K tokens | 262K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Dec 2025 | Oct 2026 |
| At 10M a month | $17.50 | $0 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
GPT-5.2 Chat is developed by OpenAI while Ling 3.1 Flash is developed by inclusionAI. GPT-5.2 Chat has a 128K 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.
It depends on your use case. GPT-5.2 Chat 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.
GPT-5.2 Chat 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.
This page shows a side-by-side comparison of GPT-5.2 Chat 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.