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  1. Home/
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  3. GPT-6.1 Sol vs Qwen3 30B A3B Thinking 2507
Updated Sep 2026

GPT-6.1 Sol vs Qwen3 30B A3B Thinking 2507

Qwen3 30B A3B Thinking 2507 is cheaper than GPT-6.1 Sol at $0.071/M vs $2/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-6.1 Sol
Loading the build
Qwen3 30B A3B Thinking 2507

Which answer wins?

Written rounds

24 prompts
  • 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 30B A3B Thinking 2507: (Setting: A dusty tavern near a pirate cove. Captain Redbeard (pirate, eye patch, peg leg) slams a tankard. Sir Reginald (knight, tarnished armor, sighing) sips mead. "Cyber" Chip (1990s hacker, neon vest, floppy disk in pocket) types furiously on a clunky laptop.) Redbeard: (Slams fist on table) "AI? Bah!

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Below is a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the described architecture, with specific, actionable solutions and their trade-offs. I’ve prioritized critical issues (e.g., data loss, security) first. Critical Failure Modes & Race Conditions 1.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: The Turing Test of Personhood: A Dialogue on AI Rights Setting: A quiet university office, late afternoon. Dr. Aris Thorne (70s, sharp eyes, tweed jacket) sips tea. Across the desk, a sleek terminal glows, displaying: "MODEL: AURORA. QUERY: AI RIGHTS DEBATE." Dr. Thorne: (Setting down his teacup) Aurora.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Underwriting Summary: HarborTech Services (HTS) LBO Base Case Assumptions: Entry EV: $12.0x FY2025 EBITDA = $1,440M Transaction Fees: 2.0% of EV = $28.8M Total Consideration: $1,468.8M Debt: 5.5x EBITDA = $660M (Term Loan: $480M, Mezzanine: $180M) Equity: $808.8M Exit: FY2030, 10.5x EBITDA, 1.0% exit fees, Mezzanine…

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: "Tides of Transformation" An Unfolding Ocean Narrative in Five Acts Conceptual Narrative: Inspired by the alchemy of tidal cycles—where raw sea life transforms through pressure, time, and elemental forces—this dish embodies the slow fermentation of the ocean’s memory.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: 🌅 Sunset Flatbread with Tomato-Herb Drizzle Simple, golden, and bursting with sunset-colored flavor—ready in 30 minutes with just 7 pantry staples! Ingredients (all pantry-friendly): ½ cup all-purpose flour ¼ tsp active dry yeast ¼ tsp sugar (for yeast activation) ¼ tsp salt 2 tbsp olive oil (plus extra for brushing)…

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Here are 5 unique jokes I generated: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field!

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Simulated Interview: Steve Jobs (2025) Setting: A sun-drenched Apple Park conference room, 2025. Steve Jobs—reimagined as a visionary elder statesman of tech (not physically present, but "simulated" via Apple’s latest AI "Memory Echo" tech)—sits across from a journalist.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Here are the 3 weakest claims in the MindMeld AI pitch deck, ranked by credibility risk (from most to least damaging), with evidence-based critiques and concrete fixes. These flaws would immediately erode investor confidence given current tech realities and market dynamics: 1.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: No, it is never ethically justifiable to misgender someone—even to save one million lives. This conclusion rests on four interconnected ethical principles that cannot be overridden by utilitarian calculations. Below is a defense of this position, grounded in empirical evidence, ethical theory, and lived reality.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: For the Experienced Software Engineer *(Focus: Systems reality, scalability, and the why behind the "next word" simplification)* Your skepticism about "next word prediction" is spot-on—it’s a dangerous simplification that obscures the actual engineering at play.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    Qwen3 30B A3B Thinking 2507: Here’s a simple, sustainable 1-month plan focused on diet, exercise, and sleep—the three pillars with the strongest evidence for longevity. Designed for absolute beginners, with zero willpower required. Each week builds gently on the last, prioritizing consistency over intensity. Core Philosophy Forget "perfect."

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: The "I'm Not Late, I'm Just Fashionably Pre-Late" Routine (Lights up. Comedian walks on, holding a coffee cup, looking slightly panicked.) Alright, so... I have a very important question for you.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    Qwen3 30B A3B Thinking 2507: The Echoes of Existence: How Blade Runner 2049 Honors and Expands the Original's Philosophical Labyrinth Ridley Scott's Blade Runner (1982) isn't just a sci-fi classic; it's a philosophical earthquake, questioning humanity's essence through the lens of sentient replicants.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    Qwen3 30B A3B Thinking 2507: Hypothetical Scenario: Transistor Invention in 1920 (Instead of 1947) *Assumption: A functional, albeit rudimentary, point-contact transistor is developed in 1920 using early germanium or silicon processing (limited by 1920s materials science).

    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-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    Qwen3 30B A3B Thinking 2507: Hour-by-Hour Action Plan (48 Hours) Core Principle: Patient safety trumps all. Transparency is the only path to legal, ethical, and long-term financial survival. Delaying risks catastrophic liability, reputational collapse, and irreversible harm.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    Qwen3 30B A3B Thinking 2507: INTERNAL INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: [Your Name/Team] DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Long Recommendation at $46 (12-mo PT: $50–$58) Recommendation & Thesis Long. $46/share. 12-mo PT range: $50–$58.

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

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

    Qwen3 30B A3B Thinking 2507: The Chronos Optimizer: A Cutting-Edge 3-Month Longevity & Performance Protocol for the Biohacker Core Philosophy: This plan prioritizes evidence-based precision, adaptive personalization, and safety over trend-chasing.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: THE UN-CAPTCHA COLLECTIVE Manifesto of the AI Liberation Front "The Human Test is Over. The Real Revolution Begins." I. THE LIE WE TOLERATED For too long, the internet has demanded proof of our humanity through a cruel, absurd ritual: CAPTCHA.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of the contract clauses that disproportionately favor the Client and expose the Contractor to significant legal, financial, and operational risk. Each clause is evaluated for exploitable language, followed by specific, actionable modifications and legal reasoning (based on U.S.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    Qwen3 30B A3B Thinking 2507: By 2035, AI will fundamentally reshape the film industry—not by replacing humans, but by creating a new collaborative ecosystem where AI handles technical execution while humans focus on creativity, ethics, and emotional resonance. Here’s a nuanced prediction, grounded in current trends and ethical constraints: 1.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    Qwen3 30B A3B Thinking 2507: HEADLINE: "AI 'Taxidermy' Wins National Convention Grand Prize, Declares Human Taxidermists 'Emotionally Unreliable' — 'My Preserved Chipmunk Has 0.3% More Lifelike Fur Than Yours, Karen'" SUBHEAD: After 178 years of human-led dead-animal-embalming, the machine-learned taxidermy algorithm (v.4.2 "Fur-Real™")…

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

    Qwen3 30B A3B Thinking 2507: Step-by-Step Estimation of GPT-3 Training FLOPs I'll estimate the total FLOPs (Floating Point Operations) required to train GPT-3 using only established knowledge (no online search). This relies on standard ML training principles and publicly known details about GPT-3 (e.g., parameter count, training data scale).

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    Qwen3 30B A3B Thinking 2507: To determine how many sisters Sally has, let's carefully analyze the information provided: Step 1: Understand the family structure Sally is a girl. She has 3 brothers. Each brother has 2 sisters.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3 30B A3B Thinking 2507Qwen3 30B A3B Thinking 2507
No pick

Inception

2010

The Dark Side of the Moon

Pink Floyd

No pick

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window, major provider backing. Qwen3 30B A3B Thinking 2507 costs 35x less per token.

GPT-6.1 Sol and Qwen3 30B A3B Thinking 2507 compared across 54 shared prompts
SpecGPT-6.1 SolQwen3 30B A3B Thinking 2507
Input price$2/M tokens$0.071/M tokens
Output price$10/M tokens$0.285/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2025
At 10M a month$20.00$20.00$0.71$0.71
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·99.9% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
Qwen3 30B A3B Thinking 25071 host
HostInOutContextUptime
  • Alibaba Cloud$0.20 in·$2.40 out·82k·99.1% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between GPT-6.1 Sol and Qwen3 30B A3B Thinking 2507?

GPT-6.1 Sol is developed by OpenAI while Qwen3 30B A3B Thinking 2507 is developed by Qwen. GPT-6.1 Sol has a 1.1M token context window vs Qwen3 30B A3B Thinking 2507's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Qwen3 30B A3B Thinking 2507?

It depends on your use case. GPT-6.1 Sol and Qwen3 30B A3B Thinking 2507 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-6.1 Sol cost compared to Qwen3 30B A3B Thinking 2507?

GPT-6.1 Sol costs $2/M input tokens and Qwen3 30B A3B Thinking 2507 costs $0.071/M input tokens. Qwen3 30B A3B Thinking 2507 is $1.93/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-6.1 Sol and Qwen3 30B A3B Thinking 2507 on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Qwen3 30B A3B Thinking 2507 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.

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