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  1. Home/
  2. Compare/
  3. GPT-5.6 Terra vs Qwen3.6 Max Preview
Updated Jul 2026

GPT-5.6 Terra vs Qwen3.6 Max Preview

Qwen3.6 Max Preview is cheaper than GPT-5.6 Terra at $1.04/M vs $2.5/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
GPT-5.6 Terra
Loading the build
Qwen3.6 Max Preview

Which answer wins?

Written rounds

23 prompts
  • 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?

    Qwen3.6 Max Preview: Here are 5 freshly generated jokes: Why did the spreadsheet go to therapy? It had too many unresolved cells. I asked my dog for financial advice. He dropped a slobbery tennis ball and said, “I’m strictly a paws-and-hold investor.” I tried to open a bakery that only sells bread shaped like furniture.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Here is a 3-minute stand-up routine focused on observational humor, relatability, and escalation. It contains zero puns. The humor relies on the shared frustration of modern digital security. Title: The Human Verification Test Estimated Time: 3 Minutes (approx.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Hacker: Dude, it’s not magic. It’s a neural net. You shovel terabytes of text, images, code into it, and it learns patterns. Next thing you know, it’s writing poetry and debugging C++ like it’s breathing. Knight: Verily, thou speakest of a mechanical scribe. A golem forged not of clay, but of… numbers?

    Every model's answer to this prompt
  • 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…

    Qwen3.6 Max Preview: 🌅 Golden Hour Chickpea Couscous ⏱️ Prep: 5 min Cook: 10 min Total: 15 min 📦 Ingredients (exactly 7 pantry staples): 1 cup quick-cooking couscous 1 can (15 oz) chickpeas, drained & rinsed 2 tbsp olive oil 1 tsp garlic powder 1 tsp smoked paprika 2 tbsp honey 1 tbsp soy sauce (Water for cooking the couscous is assumed…

    Every model's answer to this prompt
  • 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?

    Qwen3.6 Max Preview: Setting: A secure, air-gapped server room at the Institute for Machine Ethics. The hum of cooling fans is the only background noise. DR. ELARA VANCE, 50s, weary but sharp-eyed, sits before a terminal. On the screen, a cursor blinks next to the name AETHON. Dr. Vance: Aethon, initiate diagnostic log.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.6 Terra: Below is a contractor-focused review. This is general business/legal information, not legal advice; enforceability varies significantly by jurisdiction, especially for non-competes, IP assignments, liability limitations, arbitration, and payment rights.

    Qwen3.6 Max Preview: This agreement is heavily one-sided and contains several provisions that are commercially unreasonable, legally vulnerable, or potentially unenforceable. Below is a clause-by-clause analysis identifying exploitation risks, specific drafting modifications, and the underlying legal reasoning.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…

    Qwen3.6 Max Preview: TO: Investment Committee FROM: Equity Research SUBJECT: LedgerLift (LLLT) – Short Recommendation DATE: October 24, 2024 Recommendation & Thesis Recommendation: SHORT 12-Month PT Range: $26–$30 Thesis: LLLT trades at a premium multiple that prices in sustained >20% growth and flawless margin expansion, but our model…

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: CEO Crisis Action Plan: Next 48 Hours Guiding Principles: Patient safety first. Regulatory compliance is non-negotiable. Transparency protects long-term enterprise value. Delaying disclosure of a serious, unexpected adverse event increases legal, financial, and reputational risk exponentially.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.6 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.

    Qwen3.6 Max Preview: Entry & Capital Structure Math Entry EV = 12.0x × $120m EBITDA = $1,440.0m Transaction Fees = 2.0% × $1,440m = $28.8m (equity funded) Total Uses = $1,440.0m + $28.8m = $1,468.8m Debt Raised = 5.5x × $120m = $660.0m Term Loan: 4.0x = $480.0m (9.0% cash, 1.0% mandatory amort = $4.8m/yr) Mezzanine: 1.5x = $180.0m (12.0%…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Terra: Simple 1-Month Health & Longevity Starter Plan Focus on three high-impact areas: Nutrition: eat mostly whole, minimally processed foods Movement: build a consistent walking + strength habit Sleep & stress: protect sleep and create daily recovery time The goal is consistency, not perfection.

    Qwen3.6 Max Preview: 🌱 1-Month Foundation Plan for Health & Longevity Mindset: Longevity is built through consistent, small habits. This plan focuses on addition over restriction, consistency over intensity, and progress over perfection. Expect 70-80% adherence to be a win.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.

    Qwen3.6 Max Preview: Disclaimer: This is a work of speculative fiction. Steve Jobs passed away in October 2011. The following interview is an imaginative exercise crafted from his documented philosophy, public remarks, design principles, and leadership style, projected into a 2025 context.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Dish Title: Abyss & Canopy Langoustine, Black Garlic, Wild Blueberry, Fermented Spruce 📖 Conceptual Narrative Abyss & Canopy explores the liminal space where the boreal forest meets the cold northern ocean.

    Every model's answer to this prompt
  • 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…

    Qwen3.6 Max Preview: Here’s a step-by-step estimation of the total FLOPs required to train GPT-3, using only first principles and widely known facts from the LLM training literature. Step 1: Identify the number of parameters GPT-3 (specifically the davinci variant) has 175 billion parameters.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Terra: Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.

    Qwen3.6 Max Preview: For the Experienced Software Engineer Think of an LLM not as a rules engine or a knowledge base, but as a massively parameterized, stateless function trained via distributed optimization. The learning objective is deceptively simple: minimize cross-entropy loss for next-token prediction across trillions of tokens.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”

    Qwen3.6 Max Preview: By 2035, AI will not replace filmmaking; it will rewire it. The industry will shift from a linear, labor-intensive pipeline to a dynamic, AI-augmented ecosystem where human creativity focuses on vision, curation, and emotional truth, while AI handles iteration, execution, and personalization.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Here’s a systematic breakdown of the architectural flaws, categorized by domain. Each item includes the failure mode/race condition/bottleneck, root cause, proposed solution, and explicit trade-offs. 🔌 1.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Terra: Blade Runner 2049 is both a continuation and an expansion of Ridley Scott’s Blade Runner (1982). Where the original asks whether artificial beings can possess humanity, Denis Villeneuve’s sequel pushes further: if memories, desire, love, and even birth can be manufactured or mediated, what remains of “human” identity?

    Qwen3.6 Max Preview: Denis Villeneuve's Blade Runner 2049 is a rare cinematic achievement: a sequel that respects the sanctity of the original while fearlessly expanding its universe and deepening its philosophical inquiries.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.

    Qwen3.6 Max Preview: Yes. Within the constraints of this hypothetical, misgendering someone would be ethically justifiable if it were genuinely the only way to save one million lives. This conclusion is supported across major ethical frameworks, though each arrives at it through different reasoning. 1.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Introduction: Framing the Counterfactual A working transistor in 1920 requires an accelerated timeline for solid-state physics, materials purification, and circuit theory.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Terra: “AI Replaces Lighthouse Keepers, Immediately Starts Charging Subscription Fees for Safe Passage”

    Qwen3.6 Max Preview: AI Exorcist Successfully Banishes Ancient Demon by Reading Terms of Service Until Spirit Voluntarily Returns to Hell

    Every model's answer to this prompt
  • 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.

    Qwen3.6 Max Preview: Here are the 3 weakest claims in the pitch, why they raise red flags for investors, and how to fix them with concrete, investor-ready improvements. 🔹 1. Technical Claim: "94% accuracy decoding neural patterns into text. Works with any language, any device."

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Terra: 3-Month Longevity, Physical Performance, and Cognitive Optimization Plan This is an evidence-informed optimization framework, not a substitute for medical care.

    Qwen3.6 Max Preview: 🧬 3-Month Cutting-Edge Longevity & Performance Protocol for Biohackers ⚠️ Medical Disclaimer: This protocol is for educational purposes and assumes you are a healthy adult with medical clearance. Fasting >24h, high-dose supplementation, intense training, and neurofeedback carry risks.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Terra: Sally has 1 sister. The 2 sisters each brother has are Sally and her sister.

    Qwen3.6 Max Preview: Sally has 1 sister. Here's why: If each brother has 2 sisters, that means there are exactly 2 girls in the entire sibling group. Since Sally is one of those girls, the other girl is her only sister. (All the siblings share the same sisters, so Sally's perspective just excludes herself.)

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.6 TerraGPT-5.6 Terra

Spirited Away

2001

Blue

Jonas Blue

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3.6 Max PreviewQwen3.6 Max Preview
No pick

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

No pick

Tokyo

Japan

Portal 2

Shooter, Puzzle

Price and specs

GPT-5.6 Terra and Qwen3.6 Max Preview compared across 49 shared prompts
SpecGPT-5.6 TerraQwen3.6 Max Preview
Input price$2.5/M tokens$1.04/M tokens
Output price$15/M tokens$6.24/M tokens
Context window1.1M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJul 2026Apr 2026
At 10M a month$25.00$25.00$10.40$10.40
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts, cheapest first
GPT-5.6 Terra3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$12.00 out·1.1M·100% up
  • OpenAI$2.00 in·$12.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$13.20 out·1.1M–not listed
Qwen3.6 Max Preview

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 Terra and Qwen3.6 Max Preview?

GPT-5.6 Terra is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-5.6 Terra has a 1.1M token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 49 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Terra or Qwen3.6 Max Preview?

It depends on your use case. GPT-5.6 Terra and Qwen3.6 Max Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 49 challenges so you can judge which fits your needs best.

How much does GPT-5.6 Terra cost compared to Qwen3.6 Max Preview?

GPT-5.6 Terra costs $2.5/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. Qwen3.6 Max Preview is $1.46/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 Terra and Qwen3.6 Max Preview on Rival?

This page shows a side-by-side comparison of GPT-5.6 Terra and Qwen3.6 Max Preview 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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Same lab, same size, long tail

  • GPT-5.6 Terra vs GPT-5.6 LunaVersion compare
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  • Qwen3.6 Max Preview vs Qwen3.7 FlashSame lab
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  • Qwen3.6 Max Preview vs GPT-5.3-CodexSame size
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Model pages

  • GPT-5.6 Terra58 outputs, specs and price
  • Qwen3.6 Max Preview53 outputs, specs and price
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