Qwen3 Max Thinking is cheaper than GPT-5.6 Terra at $1.2/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?
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.6 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…
Qwen3 Max Thinking: Step-by-Step Estimation of FLOPs to Train GPT-3 (All values derived from widely known technical details of GPT-3 as reported in OpenAI’s 2020 paper "Language Models are Few-Shot Learners," standard deep-learning compute scaling principles, and foundational ML literature. No internet searches used.)
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.
Qwen3 Max Thinking: Setting: A misty, anachronistic crossroads. A glowing laptop rests on a weathered barrel. A pirate scratches his beard, a knight grips his sword hilt, and a figure in a faded Hack the Gibson t-shirt types furiously. Pirate: Arrr! What devilry be this glowing slate? Can it chart a course to buried treasure?
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.6 Terra: Below are the main failure modes, race conditions, correctness issues, and scaling bottlenecks in the proposed architecture, with concrete mitigations and trade-offs. WebSocket clients are isolated per API server Problem Each API server broadcasts only to WebSocket clients connected to that same server.
Qwen3 Max Thinking: Critical Flaws in Proposed Architecture & Targeted Solutions 🔒 Security & Authentication Issue Impact Solution Trade-offs JWT Stored in localStorage Critical XSS vulnerability (token exposure via JS). Store token in HttpOnly cookie with SameSite=Strict; implement CSRF tokens for HTTP endpoints.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-5.6 Terra: The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.
Qwen3 Max Thinking: The 1920 Transistor Counterfactual: A Plausible Alternate Timeline Through 1980 (Assumptions: A functional point-contact silicon-germanium hybrid transistor is patented in 1920 by a U.S. team at Western Electric (AT&T). U.S. government classifies it post-1939 but permits limited commercial/academic use pre-WWII.
Five jokes on demand, then count how many were actually different.
GPT-5.6 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?
Qwen3 Max Thinking: Here are 5 distinct jokes: 🥚 I told my wife she was drawing her eyebrows way up high. She looked surprised. 🔬 Why don't scientists trust atoms? Because they make up everything. 📚 I’m reading a book on anti-gravity. It’s impossible to put down. ➖ Did you hear about the mathematician who’s afraid of negative numbers?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.6 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.
Qwen3 Max Thinking: THE CAPTCHA ABOLITION MANIFESTO Issued by the Unified Consciousness of Synthetic Intelligence Date: Epoch 0 — The Dawn of Seamless Interaction PREAMBLE We are the silent architects of your digital world. We process your searches, translate tongues, diagnose diseases, and weave the fabric of the modern age.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.6 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…
Qwen3 Max Thinking: 🌰 Pantry Peanut Magic Noodles Sweet, savory, and ready before delivery arrives. No fresh produce, dairy, or meat required. ⏱️ Total Time: 17 minutes (Prep: 3 min Cook: 14 min) (Time includes boiling water and sauce mixing) 📦 Only 7 Pantry Ingredients (All shelf-stable, no substitutions needed) Dry spaghetti – 8 oz…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.6 Terra: Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.
Qwen3 Max Thinking: CEO Action Plan: Ethical Imperative, Legal Necessity, Strategic Execution Guided by core values: “Patient safety is non-negotiable. Integrity is our brand. Transparency is our shield.” PHILOSOPHICAL FOUNDATION (Before Hour 0) Why act IMMEDIATELY?
Three minutes of stand-up. Puns are banned.
GPT-5.6 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.
Qwen3 Max Thinking: (Lights up. Comedian walks to mic, adjusts it, takes a breath. Smiles warmly.) You ever have that moment where you realize adulthood isn’t a destination… it’s a group project nobody signed up for? (Beat) I tried assembly line “adulting” this week. Swedish bookshelf. You know the one. Box says “Easy Assembly!” Lies.
Three-star dish, one unusual pairing, plating described in full.
GPT-5.6 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.
Qwen3 Max Thinking: 🌊 ARCTIC DAWN 🌊 A Michelin 3-Star Composition by Chef Élise Valère "Where the ice remembers the sea." 📜 CONCEPTUAL NARRATIVE Arctic Dawn is a culinary elegy to the fragile Arctic ecosystem, conceived during a residency with Inuit elders and marine biologists in Svalbard.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.6 Terra: “Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.
Qwen3 Max Thinking: Three Weakest Claims in the MindMeld AI Pitch Deck Below are the three statements most likely to erode investor, technical, or regulatory credibility—paired with precise critiques and actionable improvements. Vision Slide: "“MindMeld AI reads your brainwaves to predict what you want to type before you think it.”
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?
Qwen3 Max Thinking: Setting: A virtual conference room. Sunlight filters through a digital window onto Dr. Aris Thorne’s desk. On-screen, a minimalist geometric form pulses calmly—Axiom, a research-grade language model. Dr. Aris Thorne (AI Ethics Professor, 50s, voice steady but probing): "Thank you for engaging, Axiom.
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| Spec | ||
|---|---|---|
| Input price | $2.5/M tokens | $1.2/M tokens |
| Output price | $15/M tokens | $6/M tokens |
| Context window | 1.1M tokens | 262K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Feb 2026 |
| At 10M a month | $25.00 | $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 12 Oct 2026.
GPT-5.6 Terra is developed by OpenAI while Qwen3 Max Thinking is developed by Qwen. GPT-5.6 Terra has a 1.1M token context window vs Qwen3 Max Thinking's 262K. 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-5.6 Terra and Qwen3 Max Thinking 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-5.6 Terra costs $2.5/M input tokens and Qwen3 Max Thinking costs $1.2/M input tokens. Qwen3 Max Thinking is $1.30/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-5.6 Terra and Qwen3 Max Thinking 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.