Qwen3 Next 80B A3B Instruct is cheaper than GPT-5.6 Sol at $0.15/M vs $5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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?
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…
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?
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.
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…
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.]
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.
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).
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.
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).
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.
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.
12+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
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.
| Spec | ||
|---|---|---|
| Input price | $5/M tokens | $0.15/M tokens |
| Output price | $30/M tokens | $1.5/M tokens |
| Context window | 1.1M tokens | 66K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Sep 2025 |
| At 10M a month | $50.00 | $1.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
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.
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.
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.
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.