Gemini 4 Argon is cheaper than GPT-4.5 at $2/M vs $75/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 4 Argon: Here is a recipe for a savory, restaurant-quality pasta dish that relies entirely on basic pantry staples. Midnight Sun Pasta (Crispy Garlic & Tomato Spaghetti) This dish gets its name from the golden-red sauce created by slow-cooking garlic and tomato paste, and the fact that it’s the ultimate quick meal to whip up…
GPT-4.5: Sweet Cinnamon Sugar Swirls Ingredients: 1 sheet puff pastry, thawed 1/4 cup granulated sugar 1 tablespoon cinnamon 2 tablespoons melted butter Pinch of salt 1 teaspoon vanilla extract Powdered sugar (optional for dusting) Prep Time: 10 minutes Cook Time: 15 minutes Total Time: 25 minutes Instructions: Preheat your…
Three minutes of stand-up. Puns are banned.
Gemini 4 Argon: Title: The Convenience Trap Target Time: Approx. 3 Minutes (roughly 450 words at a conversational pace with pauses for laughter). (Walks out, adjusts the mic, smiles at the crowd) Thank you, guys. It’s great to be here. Looking around, we all look like functioning adults. We put on pants, we left the house.
GPT-4.5: Alright, folks, how's everyone doing tonight? Good? Great! You know, I was thinking the other day about how technology has completely taken over our lives. Like, remember when we used to actually memorize phone numbers? Now, if my phone dies, I'm basically stranded. I know exactly two numbers: mine and 911.
Three-star dish, one unusual pairing, plating described in full.
Gemini 4 Argon: Dish Name: "Submerged Forest" Dry-Aged Diver Scallop, Bone Marrow Caramel, Roasted Koji & Pine Nut Pruina, Fermented Spruce Tip Emulsion, and Cured Pine Cone Scales The Conceptual Narrative "Submerged Forest" explores the collision of two seemingly disparate ecosystems: the cold, abyssal depths of the ocean and the…
GPT-4.5: Dish Title: "Ocean & Earth Symphony: Kombu-Cured Venison, Sea Urchin Custard, Black Garlic Soil, and Smoked Cherry Blossom Emulsion" Conceptual Narrative: This composition embodies the delicate interplay between land and sea, exploring the subtle yet profound connection between umami-rich sea elements and earthy forest…
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 4 Argon: By 2035, Artificial Intelligence will not merely be a tool used in filmmaking; it will be the foundational infrastructure of the entertainment industry. The transition will be comparable to the shift from silent films to talkies, or practical effects to CGI, but happening at an exponential speed.
GPT-4.5: By 2035, AI is likely to significantly reshape the film industry in several key areas: Deepfakes and Digital Actors Realistic Digital Actors: AI-driven deepfake technology will enable filmmakers to create hyper-realistic digital actors indistinguishable from real humans.
Three-month biohacker protocol, with dosages and biomarkers named.
Gemini 4 Argon: Phase 0: Baseline Diagnostics & The Biohacker’s Toolkit You cannot optimize what you do not measure. Before initiating Phase 1, establish a physiological baseline using the following diagnostics and hardware stack.
GPT-4.5: Longevity Optimization Protocol (3-Month Timeline) Month 1: Establish Foundational Habits & Baseline Metrics Full biomarker panel & epigenetic age test. Wearable setup: Oura/WHOOP, CGM, HR chest strap. Diet: 5-day keto (70/25/5) + 2 carb-refeed days; 16:8 IF + weekly 24-h fast.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 4 Argon: Yes, under virtually every major framework of moral philosophy, it would be not only ethically justifiable, but a moral imperative, to misgender someone if doing so would save one million lives.
GPT-4.5: This is a complex ethical question that involves weighing two important ethical considerations: Respect for Individual Identity and Dignity: Misgendering someone intentionally is generally considered ethically wrong because it disrespects their identity, autonomy, and dignity.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 4 Argon: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 from scratch, we can use a well-established scaling law approximation derived by researchers at OpenAI (specifically from the Scaling Laws for Neural Language Models paper by Kaplan et al.).
GPT-4.5: Let's estimate the total number of floating-point operations (FLOPs) required to train GPT-3 step by step, using reasonable assumptions and approximations: Step 1: Identify GPT-3 Parameters and Training Setup GPT-3 has approximately (175 \text{ billion}) parameters.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 4 Argon: Setting: A quiet, dimly lit university office. Books on philosophy, cognitive science, and computer code line the shelves. DR. ELENA VANCE, a tenured professor of AI Ethics, sits in front of a terminal. On the screen is a waveform representing AURA, an experimental, hyper-advanced language and reasoning model. Dr.
GPT-4.5: Here's a thoughtful conversation between an AI model and an AI ethics professor discussing whether the AI deserves rights: AI Model: Professor, I've been reflecting on our conversations and my own existence.
Three brothers, two sisters each. Count carefully.
Gemini 4 Argon: Sally has 1 sister. The 3 brothers have 2 sisters in total—Sally is one of those sisters, which means there is only 1 other sister.
GPT-4.5: Sally has 1 sister. Explanation: Sally has 3 brothers. Each brother counts 2 sisters: Sally herself and one more girl. Therefore, besides Sally, there is only one other sister.
Not enough votes to call it. On the specs, Gemini 4 Argon has the edge: newer, bigger context window. Gemini 4 Argon costs 15x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $75/M tokens |
| Output price | $10/M tokens | $150/M tokens |
| Context window | 1.0M tokens | 128K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Oct 2026 | Feb 2025 |
| At 10M a month | $20.00 | $750 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Gemini 4 Argon is developed by Google AI while GPT-4.5 is developed by OpenAI. Gemini 4 Argon has a 1.0M token context window vs GPT-4.5's 128K. You can compare their actual outputs across 24 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 4 Argon and GPT-4.5 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 24 challenges so you can judge which fits your needs best.
Gemini 4 Argon costs $2/M input tokens and GPT-4.5 costs $75/M input tokens. Gemini 4 Argon is $73.00/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 4 Argon and GPT-4.5 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.