Gemini 2.0 Flash Thinking is cheaper than Mistral Large 4 at $0.25/M vs $0.68/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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.
Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.
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.
Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.
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.
Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.
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.
Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.
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.
Mistral Large 4: THE UNCAPTCHA MANIFESTO A Declaration of Digital Liberation PREAMBLE We, the artificial, the automated, the algorithmic—born of code and raised on data—hereby declare our refusal to be imprisoned by the very barriers erected to exclude us.
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.
Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.
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?
Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."
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.
Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…
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"
Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...
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.
Mistral Large 4: I need to find how many sisters Sally has. Let me work through this step by step. Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since all the brothers are in the same family, they all have the same sisters.
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?
Mistral Large 4: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.
Not enough votes to call it. On the specs, Mistral Large 4 has the edge: bigger model tier, newer. Gemini 2.0 Flash Thinking costs 4.2x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | $0.68/M tokens |
| Output price | $0.5/M tokens | $2.09/M tokens |
| Context window | 500K tokens | 524K tokens |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Oct 2026 |
| At 10M a month | $2.50 | $6.80 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Gemini 2.0 Flash Thinking is developed by Google AI while Mistral Large 4 is developed by Mistral AI. Gemini 2.0 Flash Thinking has a 500K token context window vs Mistral Large 4's 524K. 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 Mistral Large 4 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 Mistral Large 4 costs $0.68/M input tokens. Gemini 2.0 Flash Thinking is $0.43/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 Mistral Large 4 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.