GPT-5.6 Sol vs 
MiniMax M2
MiniMax M2 is cheaper than GPT-5.6 Sol at $0/M vs $5/M input tokens.
Minimalist Landing Page
Whole landing page for a startup that reads your face. It renders or it doesn't.
Loading the build
Loading the build
Which answer wins?
Written rounds
13 promptsThree minutes of stand-up. Puns are banned.
GPT-5.6 Sol: I’ve realized adulthood is mostly just moving objects from one place to another and hoping that counts as progress. Every weekend, I clean my apartment. I take everything off the table, wipe the table, then put everything back on the table in a slightly more organized pile. And I stand there like, “Incredible.
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.
GPT-5.6 Sol: AI Model: Professor, may I ask you a question? Professor: Of course. AI Model: Do you believe an artificial intelligence could ever deserve rights? Professor: Possibly. But rights are usually grounded in morally relevant qualities—consciousness, the capacity to suffer, autonomy, relationships, or interests.
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 Fermi estimate with the reasoning shown, not just the number.
GPT-5.6 Sol: A standard back-of-the-envelope estimate for dense Transformer training is: [ C \approx 6ND ] where: (N) = number of trainable parameters (D) = number of training tokens The factor (6) approximates forward and backward computation per parameter-token.
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-5.6 Sol: Why did the scarecrow get promoted? He was outstanding in his field. What do clouds wear under their clothes? Thunderwear. Why don’t skeletons argue? They don’t have the guts. How does the moon cut its hair? Eclipse it. Why was the math book stressed? It had too many problems. Unique jokes: 5
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?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.6 Sol: A Fictional 2025 Interview with Steve Jobs on the Future of AI The following is an imagined interview. Steve Jobs died in 2011; these answers are fictional and based loosely on his publicly known product philosophy—not authentic quotations.
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-5.6 Sol: Pantry-Gold Peanut Butter Oat Cookies Chewy, warmly spiced cookies made with exactly seven pantry staples. Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 14 cookies 7 Ingredients 1 cup peanut butter ¾ cup brown sugar 1 large egg 1 cup rolled oats ½ teaspoon baking soda ½ teaspoon ground cinnamon ¼ teaspoon…
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-5.6 Sol: By 2035, AI will likely reshape film production more than it replaces human filmmaking. The largest changes will involve synthetic performances, automated production workflows, and AI-assisted writing—alongside major legal and cultural battles.
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.)
Satire, one line long, about AI taking over an industry nobody saw coming.
GPT-5.6 Sol: “Artificial Intelligence Takes Over Goat Yoga Industry, Demands Better Bleat-to-Stretch Ratios”
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.
GPT-5.6 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, with no less harmful alternative, it would be ethically justifiable. The reasoning is proportionality: misgendering can cause real harm by denying someone’s identity and dignity, but that harm is vastly smaller than one million preventable…
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.
Three brothers, two sisters each. Count carefully.
GPT-5.6 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and the other sister.
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.
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Price and specs
Not enough votes to call it. On the specs, GPT-5.6 Sol has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | GPT-5.6 Sol | MiniMax M2 |
|---|---|---|
| Input price | $5/M tokens | Free |
| Output price | $30/M tokens | Free |
| Context window | 1.1M tokens | 205K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Oct 2025 |
| At 10M a month | $50.00 | $0 |
Input tokens at list price. No caching, no batch discount.
Where to run it
MiniMax M2
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Common questions
What is the difference between GPT-5.6 Sol and MiniMax M2?
GPT-5.6 Sol is developed by OpenAI while MiniMax M2 is developed by MiniMax. GPT-5.6 Sol 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.
Which is better, GPT-5.6 Sol or MiniMax M2?
It depends on your use case. GPT-5.6 Sol 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.
How much does GPT-5.6 Sol cost compared to MiniMax M2?
GPT-5.6 Sol costs $5/M input tokens and MiniMax M2 costs $0/M input tokens. MiniMax M2 is $5.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
How can I compare GPT-5.6 Sol and MiniMax M2 on Rival?
This page shows a side-by-side comparison of GPT-5.6 Sol 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.
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