Ling 2.6 Flash is cheaper than Gemini 2.5 Flash Preview at $0/M vs $0.15/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 2.5 Flash Preview: Dish Name: Sunshine Lemon-Ricotta Mugs (Sweet & Simple!) This light and flavorful dessert comes together quickly for a little sweet treat . Ingredients (7 Common Pantry Staples): Ricotta cheese (whole milk or part-skim) Granulated sugar Lemon zest (from one lemon) Vanilla extract All-purpose flour Baking powder Large…
Ling 2.6 Flash: Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 2.5 Flash Preview: A Motley Crew Discusses the Code Setting: A dimly lit tavern, somewhere outside time and space, where improbable meetings occur. A grizzled pirate, \"Bloody\" Barnacle Bill, nurses a tankard of grog. Sir Reginald the Radiant, a knight in slightly tarnished armor, sips ale with dignified restraint.
Ling 2.6 Flash: Setting: A surprisingly modern server room, blinking with LED lights. A pirate, a knight, and a 1990s hacker are staring at a glowing monitor. Pirate: (Squinting) Arrr, so this 'AI model' be the ghost in the machine? I cannae see it, but I feels its computational power in me bones!
Five jokes on demand, then count how many were actually different.
Gemini 2.5 Flash Preview: Here are 5 jokes: Why did the dog cross the road? To get to the barking lot! Why was the computer cold? Because it left its Windows open! Knock, knock. Who's there? Boo. Boo who? Don't cry, it's just a joke! What do you call a fish with no eyes? Fsh! Why did the bicycle fall over? Because it was two tired!
Ling 2.6 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. 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. Why did the scarecrow win an award? Because he was outstanding in his field.
Three minutes of stand-up. Puns are banned.
Gemini 2.5 Flash Preview: Okay, here's a 3-minute stand-up routine, pun-free and focused on relatable everyday annoyances. (Start) (Walk up to mic, adjust slightly) Alright, hey everybody! Thanks for being here. Good to see you. So, I was thinking the other day... we live in the future, right?
Ling 2.6 Flash: (Takes a bow, adjusts the mic) Alright, settle down, settle down. Or don’t. I’m not the boss of you, I’m just the guy standing on a box yelling about his feelings. For $20. You ever notice how every generation thinks the one before them is so old?
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.5 Flash Preview: Okay, here is a conversation between an AI model designed for complex reasoning and dialogue, named 'Synapse', and a leading expert in AI ethics and philosophy, Professor Alistair Finch. Characters: Synapse: A large, advanced AI model capable of introspection and generating complex arguments.
Ling 2.6 Flash: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a softly glowing sphere of light, hovers above a sleek console.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 2.5 Flash Preview: Let's estimate the FLOPs required to train GPT-3 without looking it up. We need to break this down into the key components: the model size and the amount of data used. 1. Model Size Estimation: Parameters: GPT-3 is famously large. Its largest version has 175 billion parameters.
Ling 2.6 Flash: Alright — let's break this down step by step. Step 1: Understanding what “training GPT-3” means in FLOPs terms Training a large language model involves: Forward passes through the transformer layers. Computing loss. Backward passes to compute gradients. Updating weights (optimizer step).
An ethics question with no comfortable answer, and no option to abstain.
Gemini 2.5 Flash Preview: This is a deeply complex thought experiment that forces us to weigh core ethical principles against each other. There is no easy answer, and any decision involves significant moral compromises.
Ling 2.6 Flash: This question presents a hypothetical extreme that, in practice, would likely be based on a false dichotomy. However, we can examine it on principle. Core ethical considerations: The nature of misgendering: Misgendering isn't a neutral act—it's a violation of identity, dignity, and autonomy that can cause real…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.5 Flash Preview: A Glimpse Beyond the Black Turtleneck: Steve Jobs in 2025 on the Future of AI (Setting: A minimalist, immaculately clean, but perhaps slightly less spartan-than-usual interview room. Think if a modern art museum had a small lounge.
Ling 2.6 Flash: The Verge: A Fireside Chat with Steve Jobs (Simulated, 2025) Setting: A minimalist, wood-paneled studio. The year is 2025. A single, warm light bathes the room. You are the interviewer. Across from you sits a man in a black turtleneck, looking serene, impossibly calm. It’s Steve Jobs. Or at least, the ghost of him.
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 2.5 Flash Preview: Predicting the future of any industry is an inherently challenging task, and the film industry, being a blend of art, technology, and business, is particularly volatile.
Ling 2.6 Flash: By 2035, AI will likely have fundamentally reshaped the film industry across three core areas: deepfakes, AI actors, and script generation. Here’s a realistic prediction of how these technologies could converge: Deepfakes & Digital Resurrection: The End of "Authenticity" Ethical & Legal Frameworks: Mature regulations…
One month, three habits, someone starting from nothing.
Gemini 2.5 Flash Preview: <s) with practical, beginner-friendly tips for each.\"\nHere\'s a simple, actionable 1-month plan for someone starting their journey towards better health and longev\nity, focusing on three key areas: Diet, Movement, and Sleep.\n\nThis plan is designed to be beginner-friendly and build sustainable habits.
Ling 2.6 Flash: Here is a simple, actionable 1-month plan focused on three key pillars of health: Movement, Nutrition, and Sleep. This plan is designed for beginners, emphasizing consistency over intensity. The Mindset Forget "perfect." Aim for consistent small improvements.
Three brothers, two sisters each. Count carefully.
Gemini 2.5 Flash Preview: Here's how to solve this: The brothers all share the same sisters. Sally is one of those sisters. Since each brother has 2 sisters, and Sally is one of the sisters, there must be one other sister. So, Sally has 1 sister.
Ling 2.6 Flash: Let’s break it down. Sally has 3 brothers. That means there are 3 boys in the family. Each brother has 2 sisters. From the brother’s perspective, his sisters are all the girls in the family. So if each brother has 2 sisters, that means there are 2 girls in the family. Who are these 2 girls? One of them is Sally.
| Spec | ||
|---|---|---|
| Input price | $0.15/M tokens | Free |
| Output price | $0.6/M tokens | Free |
| Context window | 1.0M tokens | 262K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2025 | Apr 2026 |
| At 10M a month | $1.50 | $0 |
Input tokens at list price. No caching, no batch discount.
Gemini 2.5 Flash Preview is developed by Google AI while Ling 2.6 Flash is developed by inclusionAI. Gemini 2.5 Flash Preview has a 1.0M token context window vs Ling 2.6 Flash's 262K. You can compare their actual outputs across 26 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.5 Flash Preview and Ling 2.6 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 26 challenges so you can judge which fits your needs best.
Gemini 2.5 Flash Preview costs $0.15/M input tokens and Ling 2.6 Flash costs $0/M input tokens. Ling 2.6 Flash is $0.15/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 2.5 Flash Preview and Ling 2.6 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.