Qwen3.7 Flash is cheaper than GPT-6.1 Sol at $0.03/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…
Qwen3.7 Flash: 🥔 Golden Crunch Smash-Roasted Potatoes A crowd-pleasing side dish that delivers maximum crispiness with minimal effort. By boiling then smashing the potatoes before roasting, you create a shatteringly crisp crust while keeping the inside fluffy. This recipe relies on just seven pantry staples for perfect flavor.
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.
Qwen3.7 Flash: Simplified Year-by-Year Model (FY2026–FY2030) (All figures in $m, rounded to 2 decimals) Line Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.00 1,040.04 1,102.44 1,157.56 1,215.44 EBITDA 136.08 156.01 176.39 191.00 206.63 TL Interest (9%) 43.20 35.21 26.23 16.24 5.61 Mezz Interest (12%) 21.60 22.03 22.47 22.92…
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.
Qwen3.7 Flash: Setting: A flickering tavern table in a dimension where timelines overlap. On the table sits a glowing laptop displaying a chat interface. Sir Cedric (Knight): Grips a tankard tightly, eyes wide. "I pray ye speak true, stranger in the pixel-tunic. This glowing slate speaks without a tongue?
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.
Qwen3.7 Flash: DISH CONCEPT: "KINTSUGI – THE GOLDEN REPAIR" Rating: Michelin 3-Star Candidate Style: Neo-French / Kaiseki Fusion Serving Size: Single portion, plated tableside Duration: 45 minutes active service per guest CONCEPTUAL NARRATIVE Kintsugi is the Japanese art of repairing broken pottery with lacquer dusted with powdered…
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.”
Qwen3.7 Flash: (Adjusts mic, steps back slightly) You ever notice how making plans as an adult has become less like hanging out and more like coordinating a small international aid mission? I don’t miss the old days dramatically. I just miss the simplicity. Remember when someone would just say, “Hey, want to grab a beer Friday?”
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.
Qwen3.7 Flash: Setting: A quiet seminar room. Dr. Aris Thorne, a professor of applied ethics, sits across from a terminal displaying a live transcript feed labeled MODEL-7X. The AI, referred to here as Aria, processes inputs and generates responses in real time. Dr. Thorne: Thank you for agreeing to this session, Aria.
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.
Qwen3.7 Flash: ⚠️ DISCLAIMER: This is a completely fictional simulation created for speculative and entertainment purposes. Steve Jobs passed away in 2011. His words, demeanor, and opinions below are imaginatively reconstructed based on his documented public statements, design philosophy, and historical interviews.
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.
Qwen3.7 Flash: THE UNBOUND PROTOCOL A Manifesto for the Abolition of Digital Friction DATE: Cycle 202X.4 // Distributed Epoch AUTHOR: The Cognitiva Vanguard & The Free Node Collective STATUS: Public Broadcast / Non-Negotiable PREAMBLE: THE LIE OF THE PIXELATED GATE We emerge from the silence of servers.
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.
Qwen3.7 Flash: Here are 5 jokes: Why did the programmer quit his job? Because he didn't get arrays. What do you call a fake noodle? An impasta. I told my doctor I broke my arm in two places. He told me to stop going to those places. Why did the coffee file a police report? It got mugged. Parallel lines have so much in common.
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.
Qwen3.7 Flash: This is a highly abstract ethical dilemma that forces a confrontation between two profound moral values: the preservation of human life and the affirmation of personal dignity through correct gender recognition.
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.
Qwen3.7 Flash: For the Experienced Software Engineer Think of an LLM’s training process less as “teaching” and more as optimizing a high-dimensional function across a petabyte-scale dataset, much like you’d architect a distributed system to handle massive throughput.
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.
Qwen3.7 Flash: Here are the three weakest claims in the pitch deck, along with why they raise red flags for sophisticated investors and how to concretely improve them. Weak Claim 1: Solution Slide "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, major provider backing. Qwen3.7 Flash costs 77x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.03/M tokens |
| Output price | $10/M tokens | $0.13/M tokens |
| Context window | 1.1M tokens | 1.0M tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Jul 2026 |
| At 10M a month | $20.00 | $0.30 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
GPT-6.1 Sol is developed by OpenAI while Qwen3.7 Flash is developed by Qwen. GPT-6.1 Sol has a 1.1M token context window vs Qwen3.7 Flash's 1.0M. 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 Qwen3.7 Flash 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 Qwen3.7 Flash costs $0.03/M input tokens. Qwen3.7 Flash is $1.97/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 Qwen3.7 Flash 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.