Gemini 2.0 Flash Thinking is cheaper than GPT-5.3-Codex at $0.25/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?
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.
GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.
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.
GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…
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?
GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?
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.
GPT-5.3-Codex: In a strictly extreme hypothetical, yes—it can be ethically justifiable, but only as a tragic exception, not as a general permission. Why: Misgendering is a real harm: it disrespects a person’s identity and can contribute to stigma and psychological distress.
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.
GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.
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.
GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.
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?
GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.
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.
GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.
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.
GPT-5.3-Codex: A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…
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"
GPT-5.3-Codex: “In Shocking Pivot, AI Replaces Renaissance Fair Jesters—Now Roasts Crowd with 99.9% Historical Accuracy”
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.
GPT-5.3-Codex: Sally has 1 sister. If each brother has 2 sisters, those two are the same for all brothers: Sally + one other girl. So Sally’s only sister is that one other girl.
Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, newer. Gemini 2.0 Flash Thinking costs 28x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | $1.75/M tokens |
| Output price | $0.5/M tokens | $14/M tokens |
| Context window | 500K tokens | 400K tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Feb 2026 |
| At 10M a month | $2.50 | $17.50 |
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 GPT-5.3-Codex is developed by OpenAI. Gemini 2.0 Flash Thinking has a 500K token context window vs GPT-5.3-Codex's 400K. 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 GPT-5.3-Codex 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 GPT-5.3-Codex costs $1.75/M input tokens. Gemini 2.0 Flash Thinking is $1.50/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 GPT-5.3-Codex 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.