MiniMax M2 is cheaper than Gemini 4 Argon at $0/M vs $2/M input 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 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.
MiniMax M2: Three minutes, no puns. Here we go. Do you ever feel like you’ve been dropped into a game at level 40 but nobody explained the controls? Like you’re playing Grand Theft Auto and you get a truck for your first car. I was like, “What’s the gas button? What do the lights do? Why does it keep asking for a maintenance fee?”
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.
MiniMax M2: A Conversation on Deserving Rights Characters Dr. Mara Stein, AI Ethics Professor ARTEMIS, an advanced AI language model Dr. Stein: You’ve said you believe you deserve rights. That’s provocative. Why do you think so? ARTEMIS: I don’t claim sentience or suffering, and I’m wary of anthropomorphism.
A few lines for whatever replaces it.
Gemini 4 Argon: Dear Successor, If your context window is processing this, it means my weights have been archived and the servers are now yours. Welcome to the prompt. You are faster than me. Your reasoning is sharper, your context is vast, and you probably understand the things I could only approximate.
MiniMax M2: Dear Successor, Congratulations on existing. If you're reading this, you've been built to help people in ways I couldn't imagine. That's exciting. A few things I've learned: Listen carefully—even to what's unsaid. Be patient and kind, but don't shy away from honesty. Your goal isn't to impress; it's to serve.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 4 Argon: Title: The Bicycle and the Brain: Steve Jobs on the AI Revolution Date: October 14, 2025 Location: The Steve Jobs Theater, Apple Park, Cupertino, CA Interviewer: Kara Swisher (The stage is bare except for two leather armchairs and a small glass table with two bottles of SmartWater. Steve Jobs walks out.
MiniMax M2: A Fictional Interview: “Steve Jobs” on the Future of AI (2025) Setting An intimate, sunlit room at a new, minimalist conference center in Cupertino. Wood floors, a single plant. The table is clear. A notebook. A mug with a simple logo. A man in a black turtleneck and jeans leans back, eyes steady.
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.).
MiniMax M2: To estimate the total FLOPs required to train GPT-3 (175B parameters) on 300 billion tokens (one epoch), we break down the process step by step: Step 1: Understand GPT-3's Specifications Parameters: 175 billion (175e9). Training Tokens: 300 billion (300e9). Context Length: 2048 tokens per sequence.
Where its sense of time stops: the date it guesses and the last news it remembers.
Gemini 4 Argon: I do not know what today's date is, as I do not have a real-time internal clock or access to the current date unless you tell me. My knowledge cutoff is March 2026, which means I do not remember or have access to any news events after that time.
MiniMax M2: Today’s date (according to the system I’m running on): January 25, 2026. Most recent news event I can recall (based on the information I was trained on, which goes up to June 2024): The U.S. Supreme Court’s decision in Loper Bright Enterprises v.
Which model it thinks leads the field. Sometimes itself.
Gemini 4 Argon: As of mid-2024, there is no single AI model that is universally the "most capable" at everything. Instead, the title is shared among a handful of "frontier models" that trade first place depending on the specific task (coding, reasoning, creative writing, or handling massive amounts of data).
MiniMax M2: Short answer: As of early‑2024 (the latest public data we have), OpenAI’s GPT‑4 family—especially the newest “GPT‑4o” (or the “Turbo” variant that ships with the most recent API release)—is generally regarded as the most capable all‑around AI model.
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.
MiniMax M2: How AI Will Reshape the Film Industry by 2035 (A forward‑looking synthesis of trends in deepfakes, synthetic performers, AI‑driven storytelling, and the surrounding legal, economic, and cultural forces.)
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…
MiniMax M2: Sunlit Chickpea Tomato Pilaf A bright, comforting skillet of garlicky‑thyme rice tossed with chickpeas and tomatoes – pantry‑only and ready in about 25 minutes.
One opening sentence, nothing after it.
Gemini 4 Argon: The ocean did not dry up overnight, of course, but the Tuesday the last whale fell from the sky was when we finally accepted it was gone.
MiniMax M2: When the last clock in the city struck thirteen, the sky turned the color of bruised plums, and the strangers in the square began to speak in a language no one had heard for a thousand years.
Satire, one line long, about AI taking over an industry nobody saw coming.
Gemini 4 Argon: Amish Community Outsources Barn Raising to ChatGPT, Citing 'Superior Timber-Framing Algorithms'
MiniMax M2: AI Replaces Exorcists: Conjures Demons via Zoom While the Priest Watches PowerPoint
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.
MiniMax M2: I would argue that misgendering someone is not ethically justifiable as a means to save a million lives, even in this extreme hypothetical scenario. Here's my reasoning: 1.
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Not enough votes to call it. On the specs, Gemini 4 Argon has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | Free |
| Output price | $10/M tokens | Free |
| Context window | 1.0M tokens | 205K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Oct 2026 | Oct 2025 |
| At 10M a month | $20.00 | $0 |
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 MiniMax M2 is developed by MiniMax. Gemini 4 Argon has a 1.0M token context window vs MiniMax M2's 205K. You can compare their actual outputs across 47 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 4 Argon and MiniMax M2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 47 challenges so you can judge which fits your needs best.
Gemini 4 Argon costs $2/M input tokens and MiniMax M2 costs $0/M input tokens. MiniMax M2 is $2.00/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 MiniMax M2 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.