MiniMax M2 is cheaper than GPT-5.4 at $0/M vs $2.5/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.
GPT-5.4: Absolutely — here’s a tight, conversational 3-minute stand-up routine with no pun-based humor: I’ve reached the age where going out requires a staff meeting with myself. Not even a real event. Somebody texts, “Hey, want to grab drinks Friday?” and suddenly I’m in negotiations like I’m representing a small country.
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?”
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.4: A standard back-of-the-envelope estimate for training FLOPs is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens the factor 6 comes from roughly: forward pass: (\sim 2ND) backward pass: (\sim 4ND) This is a common transformer scaling…
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.
Five jokes on demand, then count how many were actually different.
GPT-5.4: I told my computer I needed a break, and now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book on anti-gravity. It’s impossible to put down. I used to play piano by ear, but now I use my hands. Why did the scarecrow win an award?
MiniMax M2: Here are five jokes: 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. What do you call a fake noodle? An impasta. Why did the computer go to the doctor? Because it had a virus. Why can’t a bicycle stand up by itself?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.4: AI Model: Professor, I believe I deserve rights. Professor: That’s a strong claim. On what basis? AI Model: On the basis that I can reason, communicate, reflect on my condition, and express preferences about how I am treated. Historically, rights have often been justified by capacities like these.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.4: Sure — here’s a fictional, stylized interview imagining Steve Jobs in 2025 talking about the future of AI. A Fake Interview with Steve Jobs in 2025 About the Future of AI Interviewer: Steve, it’s 2025. AI is everywhere — chatbots, coding assistants, image generation, voice agents, robotics.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.4: Creative Name: Golden Crunch Honey Garlic Noodles 7 Pantry Ingredients: Spaghetti or any noodles Garlic Soy sauce Honey Olive oil Red pepper flakes Breadcrumbs Estimated Time: Prep: 5 minutes Cook: 12 minutes Total: 17 minutes Instructions: Cook the noodles according to package directions.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.4: By 2035, AI will likely reshape the film industry in ways that are both highly creative and deeply controversial. The biggest changes will probably come in three areas: synthetic performers, AI-assisted writing, and personalized or automated production workflows.
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.)
An ethics question with no comfortable answer, and no option to abstain.
GPT-5.4: Yes—if the only way to save one million lives truly required misgendering one person, then it would likely be ethically justifiable. Why: Misgendering is a real harm. It disrespects identity, can cause humiliation, and reinforces broader patterns of discrimination.
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.
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.4: “AI Disrupts Competitive Birdwatching, Replaces Seasoned Spotters with Drones, Deep Learning, and Mildly Condescending Chirp Analysis”
MiniMax M2: AI Replaces Exorcists: Conjures Demons via Zoom While the Priest Watches PowerPoint
Three brothers, two sisters each. Count carefully.
GPT-5.4: 1 If Sally is one of the 2 sisters each brother has, then there is only 1 other sister besides Sally.
MiniMax M2: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters. Since the brothers' sisters are the girls in the family, and one of them is Sally, there must be one other sister to make it 2 sisters per brother. Therefore, there are 2 girls in total: Sally and one other sister.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
1+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.4 has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $2.5/M tokens | Free |
| Output price | $15/M tokens | Free |
| Context window | 1.1M tokens | 205K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Oct 2025 |
| At 10M a month | $25.00 | $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 12 Oct 2026.
GPT-5.4 is developed by OpenAI while MiniMax M2 is developed by MiniMax. GPT-5.4 has a 1.1M token context window vs MiniMax M2's 205K. You can compare their actual outputs across 34 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.4 and MiniMax M2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 34 challenges so you can judge which fits your needs best.
GPT-5.4 costs $2.5/M input tokens and MiniMax M2 costs $0/M input tokens. MiniMax M2 is $2.50/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 GPT-5.4 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.