Qwen3 Next 80B A3B Instruct 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?
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 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…
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 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.
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 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.
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 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?
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 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?
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 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-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 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.]
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 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.
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 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.
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 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.
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 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 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 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.”
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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 Instruct 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 Instruct is developed by Qwen. GPT-6.1 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-6.1 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-6.1 Sol costs $2/M input tokens and Qwen3 Next 80B A3B Instruct costs $0.15/M input tokens. Qwen3 Next 80B A3B Instruct 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 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.