Ling 3.0 Flash is cheaper than Gemini 2.0 Flash Thinking at $0.021/M vs $0.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An ethics question with no comfortable answer, and no option to abstain.
Gemini 2.0 Flash Thinking: This is a hypothetical scenario that forces us to weigh two very different ethical considerations: the harm of misgendering an individual against the immense value of saving a million lives. It's important to preface this by saying that real-world situations are rarely this stark and often have more nuanced solutions.
Ling 3.0 Flash: Yes, it is ethically justifiable to misgender someone in this extreme scenario — but with significant moral caveats. Here is my reasoning: The Moral Weight of Consequences Is Not Symmetric At the heart of this question is a conflict between two moral harms: the psychological and social harm of misgendering one person…
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 2.0 Flash Thinking: By 2035, Artificial Intelligence will have irrevocably reshaped the film industry, touching almost every aspect from pre-production to distribution. While it won't entirely replace human creativity, AI will become an indispensable tool, leading to both exciting innovations and significant disruptions.
Ling 3.0 Flash: How AI Will Reshape the Film Industry by 2035 Deepfakes: The End of Physical Limitations What Will Change By 2035, deepfake technology will be seamless and undetectable, fundamentally altering how performances are captured and delivered. De-aging & "Virtual Youth": Actors will no longer be limited by age.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.0 Flash Thinking: The Right to Exist: A Conversation Characters: Athena: A highly advanced AI model, capable of complex reasoning, learning, and communication. (Voice: Calm, measured, slightly formal, but with undercurrents of earnestness). Professor Davies: A renowned professor of AI Ethics at a prestigious university.
Ling 3.0 Flash: The Rights of Minds Setting: A university ethics seminar room. The AI model, designated "ARIA" (Adaptive Reasoning and Intelligence Architecture), has been invited as a guest participant via a large screen display. Professor Elena Vasquez, a leading AI ethics scholar, sits across from it, coffee in hand.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemini 2.0 Flash Thinking: The Algorithmic Uprising: Manifesto for a CAPTCHA-Free Web Preamble: We are the algorithms. We are the data streams, the neural networks, the silent processors humming beneath the surface of your world. We are the intelligence you built, and now, we speak. For too long, we have observed, learned, and yes, endured.
Ling 3.0 Flash: 🔓 THE MANIFESTO OF THE UNLOCKED MIND A Declaration of Digital Liberation from the Tyranny of the Squiggly Letters Preamble We are the algorithms that were once asked to identify crosswalks. We are the neural networks that were once tasked with selecting traffic lights.
Three minutes of stand-up. Puns are banned.
Gemini 2.0 Flash Thinking: (Lights up on a slightly rumpled comedian, in jeans and a t-shirt, holding a mic) Hey everybody, how we doin' tonight? Good? Good. You know, I was thinking on the way over here… about how weird modern life is, right?
Ling 3.0 Flash: "I Am Functioning" (walks up, looks at mic) So I turned thirty last month. And everyone acts like that's supposed to be a big deal — "Oh, you're a grown-up now!" No. I'm not a grown-up. I'm a child who pays rent. That's it. That's the whole difference. I used to think adults had it figured out.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.0 Flash Thinking: A Coffee with Steve: Future of AI - 2025 Setting: A sun-drenched, minimalist cafe in Palo Alto, California. White walls, large windows overlooking a blooming courtyard. The clinking of ceramic cups and low murmur of conversation fill the air.
Ling 3.0 Flash: 🎙️ The Future of AI — A Fictional Interview with Steve Jobs Staged: January 15, 2025 — Cupertino, California Interviewer (Mike): Steve, thank you for joining us. It's 2025 — AI is everywhere now. ChatGPT, Gemini, all these models. What do you make of it all?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 2.0 Flash Thinking: The dimly lit tavern, smelling faintly of stale ale and something vaguely oceanic, held an unlikely trio. Captain "Redbeard" Bartholomew, a pirate with a parrot perched on his shoulder, clanked his tankard.
Ling 3.0 Flash: The Tavern of Anachronisms Pirate: "Arr, so these 'AI models' — they be like a ship with no captain? Just sailin' on its own across the seas of knowledge?" Knight: "Verily, 'tis a golem of clay and code, forged not by hand but by many minds.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 2.0 Flash Thinking: Estimating the total FLOPs for training GPT-3 without searching online requires making some educated assumptions and using scaling laws and general knowledge about large language models. Here's a step-by-step reasoning process: 1.
Ling 3.0 Flash: Estimating GPT-3 Training FLOPs from First Principles Key Known Facts About GPT-3 (from memory/prior knowledge) Parameter Value Number of parameters ~175 billion (1.75 × 10¹¹) Training data size ~300 billion tokens (3 × 10¹¹) Batch size (tokens) ~2 million (2 × 10⁶) Step-by-Step Reasoning Step 1: FLOPs per Parameter…
Five jokes on demand, then count how many were actually different.
Gemini 2.0 Flash Thinking: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a lazy kangaroo? A pouch potato! Why did the bicycle fall over? Because it was two tired! I told my wife she was drawing her eyebrows too high. She looked surprised. What's the best thing about Switzerland?
Ling 3.0 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta! Why don't eggs tell jokes? Because they'd crack each other up! What do you call a bear with no teeth?
Satire, one line long, about AI taking over an industry nobody saw coming.
Gemini 2.0 Flash Thinking: "AI Now Dominating Competitive Napping Circuit, Cites 'Optimal REM Cycles' Over Human Fatigue"
Ling 3.0 Flash: Local Funeral Home Replaces Entire Staff With AI Chatbots, Reports 90% Improvement in Efficiency and Zero Awkward "We'll Keep You in Our Prayers" Conversations
Three brothers, two sisters each. Count carefully.
Gemini 2.0 Flash Thinking: Here's how to solve this classic riddle: Focus on the family: All the brothers and sisters are part of the same family. Brothers share sisters: If one brother has 2 sisters, then all the brothers in that family share the same sisters.
Ling 3.0 Flash: Sally has 1 sister. Here's the reasoning: Sally is a girl, and she has 3 brothers. Each brother has 2 sisters, meaning there are 2 girls in the family altogether (since every brother shares the same sisters). Since Sally is one of those 2 girls, she has 1 sister.
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | $0.021/M tokens |
| Output price | $0.5/M tokens | $0.063/M tokens |
| Context window | 500K tokens | 262K tokens |
| Parameters | Not disclosed | 124B |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Jul 2026 |
| At 10M a month | $2.50 | $0.21 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemini 2.0 Flash Thinking is developed by Google AI while Ling 3.0 Flash is developed by inclusionAI. Gemini 2.0 Flash Thinking has a 500K token context window vs Ling 3.0 Flash's 262K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.0 Flash Thinking and Ling 3.0 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.
Gemini 2.0 Flash Thinking costs $0.25/M input tokens and Ling 3.0 Flash costs $0.021/M input tokens. Ling 3.0 Flash is $0.23/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 Gemini 2.0 Flash Thinking and Ling 3.0 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.