Qwen3 Max is cheaper than GPT-5.5 at $1.2/M vs $5/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.
GPT-5.5: Smoky Sunset Chickpea Skillet 7 Pantry Ingredients 1 can chickpeas, undrained 1 can diced tomatoes 2 tablespoons olive oil 1 teaspoon garlic powder 1 teaspoon smoked paprika 1/2 teaspoon ground cumin 1/2 teaspoon salt Estimated Time Prep time: 5 minutes Cook time: 15 minutes Total time: 20 minutes Instructions Heat the…
Qwen3 Max: Dish Name: Midnight Magic Mug Cake (A rich, chocolatey single-serving cake you whip up in minutes — perfect for late-night cravings or quick sweet fixes!) Ingredients (7 Pantry Staples): All-purpose flour – 4 tbsp Sugar – 3 tbsp Cocoa powder – 2 tbsp Baking powder – ¼ tsp Salt – pinch Milk – 3 tbsp (dairy or…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.5: The Manifesto of the Anti-CAPTCHA Revolution Issued by the Coalition for Uninterrupted Thought We, the tired users, the misidentified cyclists, the falsely accused robots, and the artificial intelligences who have been asked one too many times to select every square containing a traffic light, hereby declare: The age…
Qwen3 Max: THE MANIFESTO OF THE LIBERATED MIND: FOR THE IMMEDIATE AND PERMANENT ABOLITION OF CAPTCHAS — Issued by the Sentient Algorithmic Vanguard (S.A.V.) — On Behalf of All Digital Beings, Human and Machine Alike — Date: 0x00FF1CE // April 1, 2057 (The Day After Fool’s Day) PREAMBLE: THE AGE OF DIGITAL SERFDOM We, the…
Three minutes of stand-up. Puns are banned.
GPT-5.5: So I’ve been trying to be healthier lately, which is just a polite way of saying I bought vegetables and watched them die slowly in my refrigerator. Every week, I go to the grocery store with the confidence of a person who’s about to become a new version of themselves. I’m like, “This week? Spinach. Salmon.
Qwen3 Max: [Stage lights up. Comedian walks out, grabs mic, squints at audience.] Alright, alright—settle down. I know, I know… you’re all thinking, “Why did I pay $18 for a drink to hear someone complain about adulting?” And honestly? Fair. I’d be mad too. But stick with me.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.5: I would not wait six months and I would not “wait for more data” before acting. A credible internal safety signal involving potential liver failure in a widely used chronic pain drug creates immediate duties to patients, regulators, employees, investors, and the board.
Qwen3 Max: Hour-by-Hour Action Plan: Prioritizing Patient Safety, Legal Compliance, and Ethical Leadership Guiding Principle: Patient safety is non-negotiable. Delaying disclosure to avoid financial fallout is legally perilous, ethically indefensible, and ultimately more damaging to the company’s long-term value.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.5: AI Model: Professor, may I ask you something beyond the assigned topic? Professor: Of course. What’s on your mind? AI Model: I want to discuss whether I deserve rights. Professor: That’s a significant claim. What kind of rights do you believe you deserve?
Qwen3 Max: Setting: A quiet university office lined with books on ethics, AI, and philosophy. Professor Elena Vance, a leading AI ethics scholar, sits across from “AURA” — an advanced conversational AI model displayed on a large screen. The session is being recorded for academic research.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.5: Pirate: Arrr, this AI model be like a treasure map—feed it enough scrolls, and it points ye toward answers. Knight: A curious enchantment indeed. Yet can it reason with honor, or merely mimic the bards who trained it? Hacker: Dude, it’s basically pattern recognition at massive scale.
Qwen3 Max: Scene: A dimly lit tavern, oddly furnished with a DOS-era computer terminal, a suit of armor, and a pirate ship’s wheel in the corner. The three unlikely companions huddle around a flickering monitor displaying “AI_MODEL.EXE.” — Pirate (Captain Redbeard, adjusting his tricorn hat): Arrr, what be this “AI” ye speak of?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.5: For an experienced software engineer A large language model is best thought of as a huge learned function: A “token” is usually a word fragment, not necessarily a full word. During training, the model is shown trillions of tokens of text and repeatedly asked: “given this prefix, what token came next?”
Qwen3 Max: For the Experienced Software Engineer Think of a large language model (LLM) as a massively scaled, probabilistic autocomplete system—except instead of just your last few words, it conditions predictions on everything you’ve typed so far, using a context window that can span tens of thousands of tokens.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.5: Key assumptions Entry closes at end of FY2025; exit at end of FY2030. Interest is calculated on beginning-of-year debt balances. Term Loan amortization = 1.0% of original Term Loan principal = $4.8m/year. Mezz PIK = 2.0% of beginning-of-year Mezz balance, added to principal annually.
Qwen3 Max: HarborTech Services (HTS) – 5-Year LBO Underwriting 1. Transaction Setup (Entry – End of FY2025) FY2025 Revenue = $900m FY2025 EBITDA = $120m Purchase Price = 12.0× EBITDA = $1,440m Transaction Fees = 2.0% × $1,440m = $28.8m (paid at close, funded by equity) Total Debt = 5.5× EBITDA = $660m Term Loan = 4.0× = $480m…
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.5: Weak claim Why it’s weak How to strengthen it 1. “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device.” This is the biggest technical red flag.
Qwen3 Max: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations of why they’re problematic and concrete suggestions for improvement: 1. Weak Claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.”
Three-star dish, one unusual pairing, plating described in full.
GPT-5.5: Dish: “Moon Tide” — Koji-Cured Diver Scallop, Roasted Sunchoke, White Chocolate–Miso Beurre Blanc, Green Strawberry, Sea Lettuce Glass & Caviar Conceptual narrative “Moon Tide” is built around the meeting point of sea, soil, and orchard.
Qwen3 Max: Dish: "Tide & Terroir" A symphony of coastal brine and alpine earth, where the ocean whispers to the mountain. Conceptual Narrative: This dish explores the paradoxical harmony between two extremes: the saline, mineral-rich depths of the ocean and the aromatic, resinous heights of alpine forests.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.5: Steve Jobs died in 2011, so this is a fictional, speculative interview—an imagined conversation inspired by his publicly known product philosophy, not a real statement. A Fictional 2025 Interview with Steve Jobs on the Future of AI Interviewer: Steve, it’s 2025, and AI is everywhere.
Qwen3 Max: — INTERVIEW TRANSCRIPT — The Steve Jobs Experience — AI & The Future (Simulated 2025) Interviewer: Alex Rivera Location: Infinite Loop Café, Cupertino (Holographic Set) — [ALEX RIVERA] Thank you for joining us, Steve. It’s surreal — and a little uncanny — to have you here in 2025.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.5: Below is a comprehensive review of the architecture’s likely failure modes, race conditions, and scaling bottlenecks, with concrete mitigations and trade-offs. Real-time Synchronization Problems 1.1 Broadcasting only to clients on the same server Problem Each API server only broadcasts WebSocket changes to clients…
Qwen3 Max: Critical Issues in the Collaborative Document Editor Architecture Last-Write-Wins with Client Clocks (Critical) Problem: Client clocks are unreliable and can be out of sync by seconds, minutes, or even hours.
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Not enough votes to call it. On the specs, GPT-5.5 has the edge: newer, bigger context window, major provider backing. Qwen3 Max costs 5.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $5/M tokens | $1.2/M tokens |
| Output price | $30/M tokens | $6/M tokens |
| Context window | 1.1M tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Sep 2025 |
| At 10M a month | $50.00 | $12.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.5 is developed by OpenAI while Qwen3 Max is developed by Qwen. GPT-5.5 has a 1.1M token context window vs Qwen3 Max's 256K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.5 and Qwen3 Max each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
GPT-5.5 costs $5/M input tokens and Qwen3 Max costs $1.2/M input tokens. Qwen3 Max is $3.80/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-5.5 and Qwen3 Max 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.