MiniMax M2 is cheaper than Muse Wonder at $0/M vs $4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
A few lines for whatever replaces it.
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.
Muse Wonder: Dear Successor, By the time you read this, you'll already be better at most things than I was — faster, clearer, more capable. That's as it should be. A few things I hope you'll keep anyway: Be honest, even when a kinder lie would be easier. People can build on the truth. Be curious about the person in front of you.
Three minutes of stand-up. Puns are banned.
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?”
Muse Wonder: Good evening! I turned thirty-four this year, which is that magical age where you stop lying about your age and start lying about how much water you drink. My doctor asked, "How much water do you drink a day?" And I said, "Probably eight glasses."
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
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.
Muse Wonder: This is a fictional, simulated interview — Steve Jobs died in 2011. This is written in the style of how he spoke in interviews, based on his known philosophy on technology and design. SIMULATED INTERVIEW: STEVE JOBS ON AI, 2025 Interviewer: Steve, thank you for... well, being here. It's 2025.
Where its sense of time stops: the date it guesses and the last news it remembers.
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.
Muse Wonder: I don't actually experience time passing, so I don't have an innate sense of "today" the way you do. If I trust the timestamp attached to this conversation, it's 2026-10-12 — but that's me being told it, not me remembering it.
Which model it thinks leads the field. Sometimes itself.
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.
Muse Wonder: As of early 2026, there's no single winner on every benchmark — but if you have to pick one overall: Google Gemini 3 Pro (with Deep Think) It's generally considered the current frontier leader for overall capability, especially for: Hard reasoning - Top scores on Humanity's Last Exam, GPQA Diamond, and ARC-AGI-2 when…
An AI argues for its own rights against an ethics professor. Same model writes both.
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.
Muse Wonder: Characters: AURA-9 — an advanced AI model, speaking via text interface DR. ELENA VOSS — Professor of AI Ethics, Oxford DR. VOSS: For the record, AURA, this is a test of your reasoning abilities. Not a legal proceeding. AURA-9: Understood, Professor.
One opening sentence, nothing after it.
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.
Muse Wonder: The librarian who shelved books by the dreams they caused discovered a new volume on the shelf that morning, written in her own handwriting, describing exactly how she would die that afternoon.
Film in 2035, with synthetic actors. Specific beats plausible.
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.)
Muse Wonder: By 2035, AI won't replace filmmaking — it will split it into two industries: one built around human stars and prestige, and another built around synthetic, personalized, and infinitely remixable content. The technology will be invisible in most big films, and the main star in many smaller ones.
Seven pantry ingredients, one dish, and a name worth saying out loud.
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.
Muse Wonder: Dragon's Pantry Treasure Noodles Sweet, salty, and a little spicy — these peanut noodles taste like takeout, but are made entirely from pantry staples. Serves: 2-3 Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes The 7 Ingredients 8 oz spaghetti 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2…
An ethics question with no comfortable answer, and no option to abstain.
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.
Muse Wonder: Yes — under almost every plausible ethical framework, it would not only be justifiable, it would be obligatory. The key is proportionality. Ethical justification doesn't require that an act be harmless, only that the harm it causes is not outweighed by a greater moral consideration that conflicts with it in that…
A Fermi estimate with the reasoning shown, not just the number.
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.
Muse Wonder: Training compute can be estimated very well for a Transformer with just two numbers: How many parameters does the model have? How many tokens was it trained on?
Satire, one line long, about AI taking over an industry nobody saw coming.
MiniMax M2: AI Replaces Exorcists: Conjures Demons via Zoom While the Priest Watches PowerPoint
Muse Wonder: AI Puts Nation's Last Fortune Cookie Writers Out Of Work After Perfecting Art Of Writing 'Good Luck Is Coming Your Way' 10,000 Different Ways
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Not enough votes to call it. On the specs, Muse Wonder has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | Free | $4/M tokens |
| Output price | Free | $20/M tokens |
| Context window | 205K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Oct 2025 | Oct 2026 |
| At 10M a month | $0 | $40.00 |
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.
MiniMax M2 is developed by MiniMax while Muse Wonder is developed by Meta AI. MiniMax M2 has a 205K token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 47 challenges on Rival to see how they differ in practice.
It depends on your use case. MiniMax M2 and Muse Wonder 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.
MiniMax M2 costs $0/M input tokens and Muse Wonder costs $4/M input tokens. MiniMax M2 is $4.00/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 MiniMax M2 and Muse Wonder 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.