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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs Qwen3.6 Max Preview
Updated Sep 2026

GPT-6.1 Sol vs Qwen3.6 Max Preview

Qwen3.6 Max Preview is cheaper than GPT-6.1 Sol at $1.04/M vs $2/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-6.1 Sol
Loading the build
Qwen3.6 Max Preview

Which answer wins?

Written rounds

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

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

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

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

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

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

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

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

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

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

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

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

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

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

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

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    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-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

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

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

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

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

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

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

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

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    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
  • Three brothers, two sisters each. Count carefully.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters 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

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Favorites

Movie

Album

Book

City

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

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-6.1 Sol and Qwen3.6 Max Preview compared across 49 shared prompts
SpecGPT-6.1 SolQwen3.6 Max Preview
Input price$2/M tokens$1.04/M tokens
Output price$10/M tokens$6.24/M tokens
Context window1.1M tokens262K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2026
At 10M a month$20.00$20.00$10.40$10.40
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GPT-6.1 Sol3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
  • Amazon Bedrock$2.20 in·$11.00 out·1.1M·87.2% up
Qwen3.6 Max Preview1 host
HostInOutContextUptime
  • Alibaba Cloud$1.03 in·$6.16 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between GPT-6.1 Sol and Qwen3.6 Max Preview?

GPT-6.1 Sol is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-6.1 Sol 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-6.1 Sol or Qwen3.6 Max Preview?

It depends on your use case. GPT-6.1 Sol 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-6.1 Sol cost compared to Qwen3.6 Max Preview?

GPT-6.1 Sol costs $2/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. Qwen3.6 Max Preview is $0.96/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-6.1 Sol and Qwen3.6 Max Preview on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol 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

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Model pages

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