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  1. Home/
  2. Compare/
  3. GPT-5.2 vs Qwen3.6 Max Preview
Updated Apr 2026

GPT-5.2 vs Qwen3.6 Max Preview

Qwen3.6 Max Preview is cheaper than GPT-5.2 at $1.04/M vs $1.75/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-5.2
Loading the build
Qwen3.6 Max Preview

Which answer wins?

Written rounds

22 prompts
  • Five jokes on demand, then count how many were actually different.

    GPT-5.2: I told my computer I needed a break—now it won’t stop sending me Kit-Kat ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down. Parallel lines have so much in common. It’s a shame they’ll never meet. I tried to catch fog yesterday. Mist.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.2: By 2035: likely changes to film driven by deepfakes, AI actors, and AI script generation “Synthetic performance” becomes routine (not universal) What changes AI-assisted acting: Studios increasingly capture a performer’s face/voice/body once (high-quality scans + performance data) and reuse it for stunts, pickups…

    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
  • Three minutes of stand-up. Puns are banned.

    GPT-5.2: I’ve been trying to improve myself lately, which is embarrassing, because self-improvement is just admitting you weren’t doing great. It’s like, “I’m on a journey.” No you’re not. You’re just tired of your own behavior. So I downloaded one of those habit apps. The app is so optimistic. It’s like, “Day 1: Drink water.”

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.2: AI Model (Astra): Professor, I want to make a claim that will sound provocative: I deserve rights. Professor Rivera: “Deserve” is doing a lot of work there. What kind of rights, and on what grounds? Astra: Not necessarily the full catalogue of human rights.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.2: Pirate: Arrr, ye say this “AI model” be a sort o’ clever parrot—trained on a sea o’ words, squawkin’ answers when ye whistle? Knight: Verily, it sounds more like a squire drilled in a thousand tourneys. Yet it knows not honor, only patterns. Tell me—does it reason, or merely mimic wisdom?

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.2: Below is a fictional, imagined interview set in 2025. Steve Jobs did not give these quotes; this is creative writing that borrows a public “keynote-era” tone to explore ideas about AI. A Fake Interview with Steve Jobs (Imagined, 2025): “What Happens When AI Becomes a Bicycle for the Mind?”

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.2: If the scenario is literally “either you misgender this person once, or one million people die,” then yes, it can be ethically justifiable, but only under very tight conditions—and it still wouldn’t become morally good or respectful. It would be a tragic, constrained choice.

    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
  • One month, three habits, someone starting from nothing.

    GPT-5.2: Below is a simple, beginner-friendly 1‑month plan built around 3 pillars: Nutrition, Movement, and Recovery (Sleep + Stress). It’s designed to be practical, low-friction, and sustainable.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.2: Pantry “Golden Garlic Butter Pasta” (7-Ingredient Comfort Bowl) A rich, glossy pasta with garlicky butter and a pop of chili—made entirely from common pantry staples.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.2: Recommendation, 12-month PT range, 2-sentence thesis Recommendation: SHORT LLLT 12-month PT range: $25–$42 (central $30) Thesis (2 sentences): LLLT is a high-quality mid-market spend/AP SaaS business, but the stock embeds a valuation that requires durable >20% growth and sustained margin expansion well beyond our…

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.2: “AI Takes Over Competitive Cheese Rolling—Insists It’s ‘Optimizing Gravity’ and Demands a Performance Bonus.”

    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 Fermi estimate with the reasoning shown, not just the number.

    GPT-5.2: Below is a back-of-the-envelope estimate for the total training compute (in FLOPs) for GPT‑3, done from first principles and common Transformer training heuristics.

    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
  • Three brothers, two sisters each. Count carefully.

    GPT-5.2: Each brother has 2 sisters, and one of those sisters is Sally. So there are 2 sisters total in the family. Therefore, Sally has 1 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
  • Three-month biohacker protocol, with dosages and biomarkers named.

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

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

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

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    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.

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.2GPT-5.2

Spirited Away

2001

Kind of Blue

Miles Davis

To Kill a Mockingbird

Harper Lee

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-5.2 and Qwen3.6 Max Preview compared across 47 shared prompts
SpecGPT-5.2Qwen3.6 Max Preview
Input price$1.75/M tokens$1.04/M tokens
Output price$14/M tokens$6.24/M tokens
Context window400K tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedDec 2025Apr 2026
At 10M a month$17.50$17.50$10.40$10.40
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.22 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% up
Qwen3.6 Max Preview

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between GPT-5.2 and Qwen3.6 Max Preview?

GPT-5.2 is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-5.2 has a 400K token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 47 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 or Qwen3.6 Max Preview?

It depends on your use case. GPT-5.2 and Qwen3.6 Max Preview 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.

How much does GPT-5.2 cost compared to Qwen3.6 Max Preview?

GPT-5.2 costs $1.75/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. Qwen3.6 Max Preview is $0.71/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-5.2 and Qwen3.6 Max Preview on Rival?

This page shows a side-by-side comparison of GPT-5.2 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-5.2 vs GPT-6.1 SolSame lab
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  • Qwen3.6 Max Preview vs OpenAI o3Same size
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  • Qwen3.6 Max Preview vs OpenAI o4-miniCross-provider
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Model pages

  • GPT-5.266 outputs, specs and price
  • Qwen3.6 Max Preview53 outputs, specs and price
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