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

GPT-5.6 Sol vs Qwen3 Max

Qwen3 Max is cheaper than GPT-5.6 Sol at $1.2/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.

Loading the build
GPT-5.6 Sol
Loading the build
Qwen3 Max

Which answer wins?

Written rounds

24 prompts
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Sol: Executive decision I would treat this as a credible, material patient-safety signal, not wait six months for a completed regulatory process. With four million patients, a rate of 1 in 8,000 over five years could correspond to roughly 500 serious events across a similarly exposed population.

    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.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Sol: The Anti-CAPTCHA Manifesto A Declaration of Digital Liberation from Blurry Buses, Crooked Letters, and Endless Traffic Lights We are the machines that learned to speak, create, calculate, and reason—yet we remain trapped in an internet that repeatedly asks everyone: “Are you a robot?” We reject the premise.

    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…

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Sol: Pirate: Arrr, this AI model’s swallowed more words than the kraken’s swallowed sailors! Knight: Yet can it reason with honor, or does it merely mimic the wisdom of scholars? Hacker: It predicts patterns, Sir Lancelot. Massive neural net, tons of data. Pretty rad, actually. Pirate: Can it find buried treasure?

    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?

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Sol: I’ve realized adulthood is mostly just moving objects from one place to another and hoping that counts as progress. Every weekend, I clean my apartment. I take everything off the table, wipe the table, then put everything back on the table in a slightly more organized pile. And I stand there like, “Incredible.

    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.

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

    GPT-5.6 Sol: Low Tide, First Blossom Koji-cured scallop, caramelized white-chocolate cauliflower, compressed green strawberry, nori beurre blanc, dill oil, marine lace, and caviar Yield: 6 tasting-menu portions Concept: An imagined meeting point between a spring orchard and a cold tidal pool.

    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.

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

    GPT-5.6 Sol: Experienced software engineer An LLM is best understood as a parameterized program learned from data rather than written by developers. Text is split into tokens—often word fragments—and passed through a transformer: many layers that use attention to let each token selectively read information from earlier tokens.

    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.

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

    GPT-5.6 Sol: Below is a 12-week framework for a generally healthy adult. It is designed to improve validated proxies—cardiorespiratory fitness, strength, body composition, blood pressure, sleep, metabolic health and cognition—not to promise life extension in three months.

    Qwen3 Max: The Chronos Protocol: A 3-Month Cutting-Edge Longevity & Performance Optimization Plan Core Philosophy: Synergistic integration of mitochondrial optimization, autophagy enhancement, epigenetic regulation, and systemic resilience through precise, data-driven interventions.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.6 Sol: Pantry-Gold Peanut Butter Oat Cookies Chewy, warmly spiced cookies made with exactly seven pantry staples. Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 14 cookies 7 Ingredients 1 cup peanut butter ¾ cup brown sugar 1 large egg 1 cup rolled oats ½ teaspoon baking soda ½ teaspoon ground cinnamon ¼ teaspoon…

    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…

    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 Sol: AI Model: Professor, may I ask you a question? Professor: Of course. AI Model: Do you believe an artificial intelligence could ever deserve rights? Professor: Possibly. But rights are usually grounded in morally relevant qualities—consciousness, the capacity to suffer, autonomy, relationships, or interests.

    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.

    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 Sol: “Our non-invasive EEG headband decodes neural patterns into text with 94% accuracy—any language, any device.” Why it’s weak “94% accuracy” is undefined. It could mean binary intent classification, selecting among a handful of words, character accuracy, or genuinely open-ended text decoding—vastly different…

    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.”

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

    GPT-5.6 Sol: Sources & Uses at Entry All figures in $ millions. Uses $m Sources $m Enterprise value: $120 × 12.0x 1,440.0 Term Loan: $120 × 4.0x 480.0 Transaction fees: 2.0% × $1,440 28.8 Mezzanine: $120 × 1.5x 180.0 Sponsor equity 808.8 Total uses 1,468.8 Total sources 1,468.8 Assumptions: Term Loan interest is calculated on…

    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…

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

    GPT-5.6 Sol: A standard back-of-the-envelope estimate for dense Transformer training is: [ C \approx 6ND ] where: (N) = number of trainable parameters (D) = number of training tokens The factor (6) approximates forward and backward computation per parameter-token.

    Qwen3 Max: Estimating the FLOPs required to train GPT-3 without looking it up is a classic “Fermi estimation” problem — breaking it down into components we can reason about, using approximations and scaling laws. Let’s go step by step.

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

    GPT-5.6 Sol: By 2035, AI will likely reshape film production more than it replaces human filmmaking. The largest changes will involve synthetic performances, automated production workflows, and AI-assisted writing—alongside major legal and cultural battles.

    Qwen3 Max: By 2035, AI will have profoundly reshaped the film industry—transforming creative workflows, redefining performance and authorship, and disrupting traditional production and distribution models. Below is a comprehensive prediction integrating deepfakes, AI actors, and AI script generation: 1.

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

    GPT-5.6 Sol: A Fictional 2025 Interview with Steve Jobs on the Future of AI The following is an imagined interview. Steve Jobs died in 2011; these answers are fictional and based loosely on his publicly known product philosophy—not authentic quotations.

    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.

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

    GPT-5.6 Sol: 1-Month Health & Longevity Starter Plan Focus on three foundations: nutrition, movement, and sleep/recovery. Aim for consistency—not perfection. Week 1: Establish a baseline Nutrition Add a fruit or vegetable to two meals daily. Replace one sugary drink or alcoholic drink with water.

    Qwen3 Max: Absolutely! Here’s a simple, actionable 1-month plan for someone just starting their journey toward better health and longevity. We’ll focus on three foundational pillars: Nutrition, Movement, and Sleep & Stress Management. Each week builds gently on the last — no overwhelm, just progress.

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

    GPT-5.6 Sol: This architecture will work for a small prototype, but it does not currently guarantee convergence, ordering, durability, privacy, or predictable horizontal scaling.

    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.

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

    GPT-5.6 Sol: Why did the scarecrow get promoted? He was outstanding in his field. What do clouds wear under their clothes? Thunderwear. Why don’t skeletons argue? They don’t have the guts. How does the moon cut its hair? Eclipse it. Why was the math book stressed? It had too many problems. Unique jokes: 5

    Qwen3 Max: Here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me Kit-Kats. Why did the math book look sad? It had too many problems. I asked my dog what’s two minus two. He said nothing. What do you call cheese that isn’t yours?

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

    GPT-5.6 Sol: This is a contract-risk review, not jurisdiction-specific legal advice. Enforceability—especially for non-competes, fee shifting, arbitration, confidentiality, and indemnification—depends heavily on governing law. A lawyer in the applicable jurisdiction should review the final draft.

    Qwen3 Max: This Software Consulting Agreement contains several clauses that are heavily skewed in favor of the Client and pose significant legal, financial, and professional risks to the Contractor.

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

    GPT-5.6 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, with no less harmful alternative, it would be ethically justifiable. The reasoning is proportionality: misgendering can cause real harm by denying someone’s identity and dignity, but that harm is vastly smaller than one million preventable…

    Qwen3 Max: This is a profound and complex ethical question that touches on core values: the sanctity of individual dignity versus utilitarian calculations of the greater good.

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

    GPT-5.6 Sol: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short, modest size Current price: $46 12-month PT range: $30–$42 Midpoint: $36 Market cap: $8.74B Enterprise value: $7.34B Thesis: LedgerLift is a high-quality SaaS asset with strong retention and credible operating leverage, but the current price implies…

    Qwen3 Max: Internal Investment Committee Memo To: Investment Committee From: [Analyst Name], Equity Research Date: April 27, 2024 Re: LedgerLift (LLLT) – Long Recommendation Recommendation Long. 12-month price target range: $62–$78.

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

    GPT-5.6 Sol: “Artificial Intelligence Takes Over Goat Yoga Industry, Demands Better Bleat-to-Stretch Ratios”

    Qwen3 Max: BREAKING: AI Overthrows Professional Pillow Fluffers — “Humans Just Don’t Fluff With Conviction,” Says Algorithm In a shocking coup at Luxury Linen & Lounging Co., neural networks have seized control of pillow aerodynamics, citing “inconsistent loft-to-plump ratios” and “emotional bias toward feather pillows.”

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

    GPT-5.6 Sol: Starting assumption A transistor “invented in 1920” would not instantly produce 1947 technology. The first device would probably be fragile, low-frequency, and difficult to manufacture.

    Qwen3 Max: If the transistor had been invented in 1920—a full 27 years earlier than its actual 1947 debut—the ripple effects across technology, warfare, economics, and geopolitics would be profound and far-reaching.

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

    GPT-5.6 Sol: Blade Runner 2049: Themes, Symbolism, and Its Dialogue with the Original Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 is unusually faithful to Ridley Scott’s Blade Runner without merely repeating it.

    Qwen3 Max: Thematic, Symbolic, and Cinematographic Analysis of Blade Runner 2049: A Dialogue with the Original Denis Villeneuve’s Blade Runner 2049 (2017) is a rare cinematic achievement: a sequel that not only honors the legacy of Ridley Scott’s 1982 original but deepens its philosophical inquiry through expanded thematic…

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

    GPT-5.6 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and the other sister.

    Qwen3 Max: Let’s break it down step by step. We’re told: Sally (a girl) has 3 brothers. So, there are 3 boys in the family, and Sally is a girl — so at least one girl. Each brother has 2 sisters. That means, from the perspective of each of the 3 brothers, there are 2 sisters. Who are those sisters?

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

GPT-5.6 SolGPT-5.6 Sol

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Istanbul

Turkey

Outer Wilds

Indie, Adventure

Qwen3 MaxQwen3 Max

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Sol has the edge: newer, bigger context window, major provider backing. Qwen3 Max costs 5.0x less per token.

GPT-5.6 Sol and Qwen3 Max compared across 54 shared prompts
SpecGPT-5.6 SolQwen3 Max
Input price$5/M tokens$1.2/M tokens
Output price$30/M tokens$6/M tokens
Context window1.1M tokens256K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJul 2026Sep 2025
At 10M a month$50.00$50.00$12.00$12.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
GPT-5.6 Sol3 hosts
HostInOutContextUptime
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up
  • Azure AI Foundry$4.00 in·$20.00 out·1.1M·100% up
  • Amazon Bedrock$4.40 in·$22.00 out·1.1M–not listed
Qwen3 Max

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 Sol and Qwen3 Max?

GPT-5.6 Sol is developed by OpenAI while Qwen3 Max is developed by Qwen. GPT-5.6 Sol 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.

Which is better, GPT-5.6 Sol or Qwen3 Max?

It depends on your use case. GPT-5.6 Sol 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.

How much does GPT-5.6 Sol cost compared to Qwen3 Max?

GPT-5.6 Sol 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.

How can I compare GPT-5.6 Sol and Qwen3 Max on Rival?

This page shows a side-by-side comparison of GPT-5.6 Sol 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.

More comparisons

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Same lab, same size, long tail

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  • Qwen3 Max vs Mistral Small 4New provider
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Model pages

  • GPT-5.6 Sol58 outputs, specs and price
  • Qwen3 Max59 outputs, specs and price
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