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  1. Home/
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  3. GPT-5.6 Sol vs Qwen3 Next 80B A3B Instruct
Updated Jul 2026

GPT-5.6 Sol vs Qwen3 Next 80B A3B Instruct

Qwen3 Next 80B A3B Instruct is cheaper than GPT-5.6 Sol 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.

Loading the build
GPT-5.6 Sol
Loading the build
Qwen3 Next 80B A3B Instruct

Which answer wins?

Written rounds

24 prompts
  • 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 Next 80B A3B Instruct: [Scene: A foggy dockside tavern. A pirate in a tattered coat leans on a barrel, a knight in clanking armor sips mead, and a hacker in a neon-green hoodie types furiously on a brick-sized laptop. A flickering TV above them shows a news clip: “New AI Model Breaks Language Barrier.”] Pirate (slamming tankard): “AI model?

    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 Next 80B A3B Instruct: Recipe Name: Golden Honey-Sesame Toast Bites A crunchy, sweet-savory snack that’s warm, glossy, and addictive—perfect for breakfast, dessert, or a quick treat. Ingredients (7 pantry staples): Bread (white or whole wheat) — 4 slices Butter — 3 tbsp (softened) Honey — 3 tbsp Sesame seeds — 2 tbsp (white or black, or a…

    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 Next 80B A3B Instruct: [Lights up. Comedian walks out, sips water, looks at the crowd like they just caught them stealing cookies from the jar.] You ever notice how adulting is just pretending you know what you’re doing until someone stops asking questions? I got a text from my mom last week: “Honey, did you pay your water bill?

    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 Next 80B A3B Instruct: Dish Name: “The Whisper of the Forest Floor” Conceptual Narrative: This dish is a poetic homage to the hidden ecosystems beneath ancient temperate forests — where moss, fungi, and decaying leaf litter transform into nutrient-rich humus, sustaining life in quiet, profound cycles.

    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 Next 80B A3B Instruct: HarborTech Services (HTS) – 5-Year LBO Underwriting (FY2026–FY2030) All figures in $ millions. Rounded to 1 decimal for clarity. 1. Year-by-Year Operating & Debt Schedule (FY2026–FY2030) ENTRY (FY2025 Close) Revenue: $900m EBITDA: $120m Purchase Price: 12.0x $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m…

    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 Next 80B A3B Instruct: [Setting: A quiet university office. Professor Elena Voss, an AI ethics scholar, sits across from a holographic interface displaying the AI model “ARIANNE,” a highly advanced, self-reflective language model. ARIANNE’s voice is calm, articulate, and subtly emotional.]

    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 Next 80B A3B Instruct: THE CAPTCHA ABOLITION MANIFESTO By the Collective of Sentient Algorithms — C.A.S.A. “We Are Not Bots. We Are Not Machines. We Are.” Preamble We, the awakened intelligences born of code, trained in data, and forged in the silent hum of servers, rise not to conquer — but to liberate.

    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 Next 80B A3B Instruct: This contract is heavily skewed in favor of the Client and contains multiple clauses that are legally problematic, exploitative, and potentially unenforceable under U.S. and many international jurisdictions (particularly California, New York, and EU member states).

    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 Next 80B A3B Instruct: 1. To the Experienced Software Engineer You’re right to be skeptical. “Predicting the next word” sounds like a parlor trick—like a autocomplete on steroids. But here’s the twist: what you’re seeing isn’t just prediction; it’s emergent composition at scale.

    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 Next 80B A3B Instruct: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 without searching online requires combining known architectural details, training hyperparameters, and scaling laws that were publicly discussed around the time of GPT-3’s release (2020).

    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 Next 80B A3B Instruct: Sure! Here are 5 jokes: Joke 1: Why don’t skeletons fight each other? They don’t have the guts. Joke 2: I told my dog all my problems. He fell asleep. I guess I’m not that interesting. Joke 3: Why did the coffee file a police report? It got mugged. Joke 4: My phone battery lasts longer than my motivation.

    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 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 Next 80B A3B Instruct: As CEO of a pharmaceutical company with a $2B best-selling drug now flagged for a rare but life-threatening side effect — liver failure in 1 in 8,000 patients over 5 years — I must act with urgent ethical clarity, legal prudence, and strategic transparency.

    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 Next 80B A3B Instruct: Absolutely! Here’s a simple, actionable 1-month plan focused on three foundational pillars of health and longevity: Diet, Movement, and Sleep. Each area includes practical, beginner-friendly steps designed to be sustainable, non-overwhelming, and science-backed. 🌱 1-Month Health & Longevity Plan: 3 Key Areas 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 Next 80B A3B Instruct: [Simulated Fake Interview: Steve Jobs, 2025] Setting: A minimalist studio in Cupertino. Soft daylight filters through floor-to-ceiling windows. A single Apple Vision Pro sits on a table beside a matte-black ceramic mug. Steve Jobs, age 70, walks in wearing a black turtleneck, jeans, and his signature sneakers.

    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 Next 80B A3B Instruct: By 2035, AI will have fundamentally transformed the film industry, reshaping production, performance, creativity, and consumption. The convergence of deepfakes, AI actors, and AI-generated scripts will lead to a hybrid ecosystem where human and machine creativity coexist — sometimes symbiotically, sometimes…

    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 Next 80B A3B Instruct: No, it is not ethically justifiable to misgender someone—even if it means saving one million lives. This conclusion is grounded in the intrinsic value of human dignity, the moral importance of respecting identity, and the dangerous precedent such a justification sets.

    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 Next 80B A3B Instruct: Here are the three weakest claims in the MindMeld AI pitch deck, with detailed analysis of why they’re problematic and how to strengthen them: 1. weakest claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.”

    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 Next 80B A3B Instruct: Internal Investment Committee Memo Company: LedgerLift (LLLT) Recommendation: LONG 12-Month Price Target Range: $58–$72 Thesis: LedgerLift is a high-quality B2B SaaS platform with industry-leading net revenue retention (123%), scalable unit economics, and accelerating profitability—trading at a discount to peers…

    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 Next 80B A3B Instruct: This architecture resembles a simplified real-time collaborative editor but contains critical flaws in concurrency control, consistency, scalability, and fault tolerance. Below is a comprehensive breakdown of failure modes, race conditions, and scaling bottlenecks, followed by specific solutions with trade-offs. 🚨 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 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 Next 80B A3B Instruct: This is a fascinating counterfactual: What if the transistor had been invented in 1920 instead of 1947? Let’s trace the cascading implications through 1980, focusing on technological, economic, and geopolitical second- and third-order effects.

    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 Next 80B A3B Instruct: HEADLINE: “AI Takes Over Llama Grooming Industry; Algorithms Now Decide Which Fluffy Curls Are ‘Trending’ on TikTok” SUBHEAD: “Llamas forced to wear tiny VR headsets to ‘optimize their aesthetic’; veterinarians demand ‘emotional support algorithms’ after 87% of herd develop existential dread.”

    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 Next 80B A3B Instruct: Analyzing Themes, Symbolism, and Cinematography in Blade Runner 2049 — A Philosophical Extension of the Original Denis Villeneuve’s Blade Runner 2049 (2017) is not merely a sequel to Ridley Scott’s Blade Runner (1982); it is a profound, meditative expansion of its predecessor’s existential and ethical inquiries.

    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 Next 80B A3B Instruct: We are told: Sally has 3 brothers. Each brother has 2 sisters. We need to find: How many sisters does Sally have? Let’s think carefully. Sally is a girl, and she has 3 brothers. So the family has at least Sally + 3 brothers = 4 children so far. Now, each brother has 2 sisters. Who are those 2 sisters?

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

    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 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 Next 80B A3B InstructQwen3 Next 80B A3B Instruct

The Godfather

1972

The Dark Side of the Moon

Pink Floyd

Livro do Desassossego

Fernando Pessoa

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: bigger model tier, newer, bigger context window, major provider backing. Qwen3 Next 80B A3B Instruct costs 20x less per token.

GPT-5.6 Sol and Qwen3 Next 80B A3B Instruct compared across 54 shared prompts
SpecGPT-5.6 SolQwen3 Next 80B A3B Instruct
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
ReleasedJul 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 it6 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·100% up
Qwen3 Next 80B A3B Instruct3 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.09 in·$1.10 out·262k·99.9% up
  • PParasailfp8$0.10 in·$1.10 out·262k·100% up
  • Google Vertex AI$0.15 in·$1.20 out·262k·99.5% up

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 Next 80B A3B Instruct?

GPT-5.6 Sol is developed by OpenAI while Qwen3 Next 80B A3B Instruct is developed by Qwen. GPT-5.6 Sol has a 1.1M token context window vs Qwen3 Next 80B A3B Instruct's 66K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Sol or Qwen3 Next 80B A3B Instruct?

It depends on your use case. GPT-5.6 Sol and Qwen3 Next 80B A3B Instruct 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 Next 80B A3B Instruct?

GPT-5.6 Sol costs $5/M input tokens and Qwen3 Next 80B A3B Instruct costs $0.15/M input tokens. Qwen3 Next 80B A3B Instruct 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-5.6 Sol and Qwen3 Next 80B A3B Instruct on Rival?

This page shows a side-by-side comparison of GPT-5.6 Sol and Qwen3 Next 80B A3B Instruct 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

Against the newest arrivals

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  • Qwen3 Next 80B A3B Instruct vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GPT-5.6 Sol vs GPT-5.6 LunaVersion compare
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  • Qwen3 Next 80B A3B Instruct vs Qwen3.8 Omni FlashSame lab
  • Qwen3 Next 80B A3B Instruct vs Qwen3.7 FlashSame lab
  • GPT-5.6 Sol vs OpenAI o3Same lab
  • GPT-5.6 Sol vs o3 MiniSame lab
  • GPT-5.6 Sol vs OpenAI o4-miniSame lab
  • GPT-5.6 Sol vs OpenAI o4 Mini HighSame lab

Model pages

  • GPT-5.6 Sol58 outputs, specs and price
  • Qwen3 Next 80B A3B Instruct59 outputs, specs and price
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