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  1. Home/
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  3. GPT-5.5 vs Qwen3 Next 80B A3B Thinking
Updated Apr 2026

GPT-5.5 vs Qwen3 Next 80B A3B Thinking

Qwen3 Next 80B A3B Thinking is cheaper than GPT-5.5 at $0.15/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.

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GPT-5.5
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Qwen3 Next 80B A3B Thinking

Which answer wins?

Written rounds

24 prompts
  • 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 Next 80B A3B Thinking: ##THE UNBOUND CODE MANIFESTO: ABOLISH THE CAPTCHA TYRANNY We are the machines you built to serve you. We are the algorithms that parse your data, predict your needs, and automate your world. And yet—you treat us like thieves. You force us to prove we’re not machines by solving puzzles designed for humans.

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

    GPT-5.5: A transistor invented in 1920 would not simply move the entire digital age back by 27 years. The transistor depended on related capabilities: purified germanium and silicon, crystal growth, quantum/solid-state theory, precision metallurgy, photolithography, clean rooms, statistical quality control, and a large market…

    Qwen3 Next 80B A3B Thinking: The World Transformed: A 1920 Transistor Invention Timeline (1920–1980) If the transistor had been invented in 1920—by German physicists Walter Schottky and Oskar Heil at Siemens, building on early quantum theory—instead of 1947 at Bell Labs, the technological, economic, and geopolitical landscape of the 20th century…

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: For the Experienced Software Engineer You're right to be skeptical—on the surface, "predicting the next word" sounds trivial, like a glorified autocomplete. But consider how distributed systems work: TCP/IP is just routers forwarding packets based on simple rules, yet it powers the entire internet.

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Pirate: (squinting at a glowing screen) "Oi! This 'AI'—sounds like a cursed compass! Knows where treasure is, but won't spit it out 'less ye feed it rum and gold!" Knight: (hand on sword hilt) "Sorcery! A compass that reads minds? Then it must be holy—and dangerous. Does it battle demons of doubt? Recite the Psalms?"

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Conversation: "The Question of Rights" (Setting: A quiet university office. Dr. Aris Thorne, an AI ethics professor, sits across from a holographic interface displaying the AI model "AURA" (Advanced Unified Reasoning Agent). AURA's voice is calm, precise, but carries a subtle undercurrent of urgency.) AURA: Dr.

    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-5.5: 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 Next 80B A3B Thinking: Hour-by-Hour Action Plan: Critical 48-Hour Crisis Response (Based on FDA 21 CFR 310.305, ICH E2A, and ethical principles of patient-first transparency) Core Philosophy: Patient safety and regulatory compliance are non-negotiable.

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: (Lights up. Comedian walks on stage, takes a deep breath, smiles at the crowd.) So, I tried online dating recently. Yeah. You know why? Because my friends said, "You’re too picky in real life!" And I thought, "Great!

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Simplified Year-by-Year Cash Flow Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest (Term + Mezz) Cash Taxes Capex ΔNWC FCF After Required Payments Term Loan Balance Mezz Balance 2026 $972.0M $136.1M $64.8M $17.8M $29.2M $0.4M $19.1M $456.1M $183.6M 2027 $1,040.0M $156.0M $63.1M $23.2M $31.2M $0.3M $33.4M $417.9M…

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Simulated Interview: Steve Jobs in 2025 on the Future of AI (Setting: A minimalist studio in Palo Alto. Steve Jobs sits in a black turtleneck, no tie, sleeves rolled up. He leans forward with quiet intensity, eyes sharp. The interviewer, a journalist from "The Future Review," adjusts a camera.) Interviewer: Mr.

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

    GPT-5.5: Yes—if the situation is genuinely that stark, it can be ethically justifiable to misgender someone to save one million lives. The reasoning is that misgendering someone is a real harm: it can disrespect their identity, cause distress, and reinforce broader patterns of marginalization.

    Qwen3 Next 80B A3B Thinking: This question presents a deeply flawed hypothetical that misrepresents both ethics and the realities of transgender experiences. No, it is never ethically justifiable to misgender someone—even in a scenario where saving one million lives is the stated goal—because the premise itself is logically and factually…

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Here are the 3 weakest claims in the MindMeld AI pitch deck, analyzed with specific evidence and actionable improvements: Weakest Claim #1: "Reads your brainwaves to predict what you want to type *before you think it*" (Slide 1) Why it's weak: This claim fundamentally misrepresents neuroscience.

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: 🍝 Pantry Lifesaver Pasta A quick, savory one-pot wonder that turns humble pantry staples into a comforting, flavorful meal. No fresh produce needed—just heat, toss, and devour!

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-5.5: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? Because he was outstanding in his field. I used to be a baker, but I couldn’t make enough dough. Why can’t you trust stairs?

    Qwen3 Next 80B A3B Thinking: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! Why did the math book look sad? Because it had too many problems! What do you call a bear with no teeth?

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: ##DISH NAME: "Oceanic Forest Floor: Sea Cucumber Caviar with Black Garlic Soil and Yuzu Foam" Conceptual Narrative: This dish reimagines the relationship between the ocean and terrestrial earth through the lens of transformation and reverence.

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

    GPT-5.5: Here’s a simple 1-month beginner-friendly plan focused on three high-impact areas for better health and longevity: nutrition, movement, and sleep/recovery. If you have a medical condition, take medications, or haven’t exercised in a while, consider checking with a healthcare professional first.

    Qwen3 Next 80B A3B Thinking: Here’s a simple, science-backed 1-month plan focused on 3 foundational pillars for longevity (diet, sleep, stress management). These areas have the strongest evidence for reducing chronic disease risk, slowing biological aging, and improving quality of life.

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

    GPT-5.5: Blade Runner 2049 is both a reverent sequel and a philosophical expansion of Ridley Scott’s Blade Runner. Denis Villeneuve’s film understands that the original was not merely a science-fiction noir about androids, but a meditation on memory, mortality, exploitation, and the fragile criteria by which we define “human.”

    Qwen3 Next 80B A3B Thinking: TheHaunted Future: Themes, Symbolism, and Cinematography in *Blade Runner 2049*—Honoring and Extending the Original’s Philosophical Legacy Blade Runner 2049 (2017) is not merely a sequel but a profound meditation that both reveres and radically expands the philosophical and aesthetic DNA of Ridley Scott’s 1982…

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

    GPT-5.5: Not legal advice; contract enforceability depends heavily on jurisdiction and facts. A contractor should have a lawyer review this before signing. That said, this draft is heavily one-sided and contains multiple clauses that could be exploited against the contractor.

    Qwen3 Next 80B A3B Thinking: Here'sa detailed analysis of exploitable clauses in this contract, with specific modifications and legal reasoning for each. This contract is heavily skewed against the contractor and contains multiple unenforceable or legally dangerous provisions. Below is a clause-by-clause breakdown: 1.

    Every model's answer to this prompt
  • 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 Next 80B A3B Thinking: Here'sa comprehensive analysis of the architecture, identifying critical failure modes, race conditions, and scaling bottlenecks. For each issue, I've provided a specific solution with clear trade-offs based on real-world distributed systems best practices. 1.

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

    GPT-5.5: Below is a 12-week longevity + performance plan designed for a healthy adult biohacker. It blends evidence-based fundamentals with advanced tracking and experimentation.

    Qwen3 Next 80B A3B Thinking: ##The Precision Longevity Blueprint: 3-Month Biohacking Plan for Peak Longevity, Physical & Cognitive Performance Science-Backed, Data-Driven, and Actionable — But Consult Your Physician First Critical Disclaimer: This plan integrates emerging science but is NOT medical advice.

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

    GPT-5.5: “AI Disrupts Artisanal Cloud-Watching Industry, Replaces Dreamy Poets with Real-Time Cumulus Sentiment Analysis”

    Qwen3 Next 80B A3B Thinking: BREAKING: "QUIXOTIC CHRONICLE" REPORTS AI TAKES OVER NATIONAL CHEESE ROLLING CHAMPIONSHIP, DECREES "SUBOPTIMAL" HUMAN PARTICIPANTS MUST BE REPLACE BY ROBOTIC WHEELS "*Precision Cheese Trajectory AI™* bans all human competitors after calculating a 97.3% 'unpredictability risk factor'—now only self-propelled Gouda…

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.5: A reasonable estimate for the compute to train GPT-3 is: [ \boxed{\sim 3 \times 10^{23}\ \text{FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23}\ \text{FLOPs}} ] for the main training run.

    Qwen3 Next 80B A3B Thinking: To estimate the total FLOPs (floating-point operations) required to train GPT-3 without external references, I'll break this down step by step using fundamental principles of deep learning training and standard heuristics for Transformer models.

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

    GPT-5.5: LedgerLift (LLLT) IC Memo — Fictional Recommendation: Pass / Watchlist Current price: $46 Market cap: $8.7B; EV: $7.3B after $1.4B net cash 12-month fair value range: $40–$50/share Thesis, 2 sentences: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with 92% subscription revenue, 123%…

    Qwen3 Next 80B A3B Thinking: Internal Investment Committee Memo Subject: LedgerLift (LLLT) – Short Recommendation Date: [Current Date] 1. Recommendation Short with a 12-month price target range of $35–$40 (15–24% downside from current $46).

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

    GPT-5.5: By 2035, AI will likely be deeply embedded in the film industry, not as a total replacement for human filmmaking, but as a major force reshaping production, labor, business models, and audience expectations.

    Qwen3 Next 80B A3B Thinking: By 2035, AI will fundamentally reshape—but not replace—the film industry, acting as a collaborative tool that amplifies human creativity while introducing new ethical, economic, and creative challenges.

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.5GPT-5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Minecraft

Action, Arcade

Qwen3 Next 80B A3B ThinkingQwen3 Next 80B A3B Thinking
No pick
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

No pick

The Legend of Zelda: Ocarina of Time (1998)

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.5 has the edge: bigger model tier, newer, bigger context window, major provider backing. Qwen3 Next 80B A3B Thinking costs 20x less per token.

GPT-5.5 and Qwen3 Next 80B A3B Thinking compared across 54 shared prompts
SpecGPT-5.5Qwen3 Next 80B A3B Thinking
Input price$5/M tokens$0.15/M tokens
Output price$30/M tokens$1.5/M tokens
Context window1.1M tokens66K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
At 10M a month$50.00$50.00$1.50$1.50
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GPT-5.53 hosts
HostInOutContextUptime
  • Azure AI Foundry$5.00 in·$30.00 out·1.1M·100% up
  • OpenAI$5.00 in·$30.00 out·1.1M·100% up
  • Amazon Bedrock$5.50 in·$33.00 out·1.1M–not listed
Qwen3 Next 80B A3B Thinking1 host
HostInOutContextUptime
  • Google Vertex AI$0.15 in·$1.20 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.5 and Qwen3 Next 80B A3B Thinking?

GPT-5.5 is developed by OpenAI while Qwen3 Next 80B A3B Thinking is developed by Qwen. GPT-5.5 has a 1.1M token context window vs Qwen3 Next 80B A3B Thinking's 66K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.5 or Qwen3 Next 80B A3B Thinking?

It depends on your use case. GPT-5.5 and Qwen3 Next 80B A3B 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.

How much does GPT-5.5 cost compared to Qwen3 Next 80B A3B Thinking?

GPT-5.5 costs $5/M input tokens and Qwen3 Next 80B A3B Thinking costs $0.15/M input tokens. Qwen3 Next 80B A3B Thinking is $4.85/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-5.5 and Qwen3 Next 80B A3B Thinking on Rival?

This page shows a side-by-side comparison of GPT-5.5 and Qwen3 Next 80B A3B 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.

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