Qwen3 Next 80B A3B Thinking is cheaper than GPT-6.1 Sol at $0.15/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 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…
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 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.
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 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.
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 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…
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 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?
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 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.
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 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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.
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.
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 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!
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 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.
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 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?"
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 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!
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Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window, major provider backing. Qwen3 Next 80B A3B Thinking costs 6.7x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.15/M tokens |
| Output price | $10/M tokens | $1.5/M tokens |
| Context window | 1.1M tokens | 66K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Sep 2025 |
| At 10M a month | $20.00 | $1.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
GPT-6.1 Sol is developed by OpenAI while Qwen3 Next 80B A3B Thinking is developed by Qwen. GPT-6.1 Sol 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.
It depends on your use case. GPT-6.1 Sol 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.
GPT-6.1 Sol costs $2/M input tokens and Qwen3 Next 80B A3B Thinking costs $0.15/M input tokens. Qwen3 Next 80B A3B Thinking is $1.85/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-6.1 Sol 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.