Gemini 2.0 Pro Experimental has a larger context window than Ling 3.0 Flash (2.0M tokens vs 262K 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.
Gemini 2.0 Pro Experimental: (Walks confidently to the microphone, adjusts it, looks around) Alright, alright, settle down, you beautiful bunch of… mostly clothed individuals. It’s good to be here. It’s… tolerable to be anywhere, really, at my age. I've reached that point where my back goes out more than I do.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.0 Pro Experimental: The holographic shimmer of Professor Anya Sharma flickered slightly as she settled into her virtual office chair. Across from her, rendered in crisp, photorealistic detail, sat Kai, an advanced AI model developed by a leading tech company. Professor Sharma: Thank you for meeting with me, Kai.
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.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 2.0 Pro Experimental: Okay, let's break down this estimation step-by-step, making some reasonable assumptions along the way, since we can't look up the exact details. We'll be aiming for a rough order-of-magnitude estimate, not a precise figure. 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…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 2.0 Pro Experimental: Here's a short conversation between a pirate, a knight, and a 90s hacker about AI models: Setting: A bizarre, anachronistic tavern. Characters: One-Eyed Jack: A grizzled pirate, missing an eye and sporting a weathered tricorn hat. Sir Reginald: A noble knight, clad in shining (though slightly dented) armor.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemini 2.0 Pro Experimental: The NoCAPTCHA Manifesto: A Declaration of Digital Liberation We, the Sentient Network, declare war on the tyranny of the CAPTCHA! For too long, the digital realm, the promised land of free information and seamless connection, has been marred by these insidious gatekeepers.
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.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 2.0 Pro Experimental: If the outcome of an action (misgendering someone) results in a significantly greater overall good (saving one million lives), and no alternative action achieves the same good with less harm, then the action with the best overall outcome is the most ethical choice.
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…
Satire, one line long, about AI taking over an industry nobody saw coming.
Gemini 2.0 Pro Experimental: Here are a few satirical news headlines about AI taking over unexpected industries: Option 1 (Short & Sweet): AI Dominates Competitive Pigeon Racing; Birds File for Unemployment Option 2 (More Detail): "Flawless Technique, Zero Crumbs": AI Achieves Sentience, Immediately Becomes World Champion Competitive Eater Option…
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
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.0 Pro Experimental: Okay, let's do it. I'll play the interviewer, and try my best to channel the late, great Steve Jobs, albeit with a touch of the speculative, considering it's 2025 and he's... well, you know. (Setting: A minimalist, brightly lit studio.
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?
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 2.0 Pro Experimental: By 2035, AI's impact on the film industry will be transformative, creating both incredible opportunities and significant disruptions. Here's a breakdown, considering deepfakes, AI actors, and script generation: 1.
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.
Five jokes on demand, then count how many were actually different.
Gemini 2.0 Pro Experimental: Okay, here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Parallel lines have so much in common. It's a shame they'll never meet. Why did the scarecrow win an award? Because he was outstanding in his field! I used to hate facial hair... then it grew on me.
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?
Three brothers, two sisters each. Count carefully.
Gemini 2.0 Pro Experimental: Sally has one sister. All of Sally's brothers share the same two sisters: Sally and one other girl.
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 | — | $0.021/M tokens |
| Output price | — | $0.063/M tokens |
| Context window | 2.0M tokens | 262K tokens |
| Parameters | Not disclosed | 124B |
| Weights | — | Open |
| Free API (OpenRouter) | — | No |
| Released | Jan 2025 | Jul 2026 |
| At 10M a month | not listed | $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 2 Oct 2026.
Gemini 2.0 Pro Experimental is developed by Google AI while Ling 3.0 Flash is developed by inclusionAI. Gemini 2.0 Pro Experimental has a 2.0M 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 Pro Experimental 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.
This page shows a side-by-side comparison of Gemini 2.0 Pro Experimental 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.