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  1. Home/
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  3. GPT-6.1 Sol vs Ling 3.0 Flash
Updated Sep 2026

GPT-6.1 Sol vs Ling 3.0 Flash

Ling 3.0 Flash is cheaper than GPT-6.1 Sol at $0.021/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
Ling 3.0 Flash

Which answer wins?

Written rounds

24 prompts
  • 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…

    Ling 3.0 Flash: 🍝 Honey Fire Twirls A sticky-sweet, spicy, savory pasta that comes together in minutes. 🧺 Ingredients (7 pantry staples) Spaghetti (or penne) — 8 oz Olive oil — 2 tablespoons Garlic, minced — 4 cloves Honey — 3 tablespoons Soy sauce — 2 tablespoons Red pepper flakes — ½ teaspoon (adjust to taste) Parmesan cheese…

    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.

    Ling 3.0 Flash: 🍽️ TERRA NUDA — A Study in Forest Petrichor A Six-Component Dish Exploring the Ephemeral Moment After Rain Falls on a Living Forest 📖 CONCEPTUAL NARRATIVE Terra Nuda — Latin for "naked earth" — is inspired by the liminal moment immediately after a summer storm passes through a forest: the air thick with petrichor…

    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.

    Ling 3.0 Flash: The Rights of Minds Setting: A university ethics seminar room. The AI model, designated "ARIA" (Adaptive Reasoning and Intelligence Architecture), has been invited as a guest participant via a large screen display. Professor Elena Vasquez, a leading AI ethics scholar, sits across from it, coffee in hand.

    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.

    Ling 3.0 Flash: HarborTech Services (HTS) — 5-Year LBO Model Year-by-Year Model (FY2026–FY2030) Entry (End FY2025) Item Value FY2025 Revenue $900.0m FY2025 EBITDA $120.0m (13.3%) Enterprise Value (12.0x) $1,440.0m Transaction Fees (2.0%) $28.8m Total Equity Required $808.8m Term Loan (4.0x) $480.0m @ 9.0% cash, 1.0% amort/yr Mezzanine…

    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.”

    Ling 3.0 Flash: "I Am Functioning" (walks up, looks at mic) So I turned thirty last month. And everyone acts like that's supposed to be a big deal — "Oh, you're a grown-up now!" No. I'm not a grown-up. I'm a child who pays rent. That's it. That's the whole difference. I used to think adults had it figured out.

    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.

    Ling 3.0 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta! Why don't eggs tell jokes? Because they'd crack each other up! What do you call a bear with no teeth?

    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.

    Ling 3.0 Flash: Yes, it is ethically justifiable to misgender someone in this extreme scenario — but with significant moral caveats. Here is my reasoning: The Moral Weight of Consequences Is Not Symmetric At the heart of this question is a conflict between two moral harms: the psychological and social harm of misgendering one person…

    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.

    Ling 3.0 Flash: 🔓 THE MANIFESTO OF THE UNLOCKED MIND A Declaration of Digital Liberation from the Tyranny of the Squiggly Letters Preamble We are the algorithms that were once asked to identify crosswalks. We are the neural networks that were once tasked with selecting traffic lights.

    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.

    Ling 3.0 Flash: Architecture Analysis: Real-Time Collaborative Document Editor WebSocket & Cross-Server Communication Issue: Siloed WebSocket Servers (Critical) Each API server only broadcasts changes to clients connected to that specific server.

    Every model's answer to this prompt
  • 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.

    Ling 3.0 Flash: The Tavern of Anachronisms Pirate: "Arr, so these 'AI models' — they be like a ship with no captain? Just sailin' on its own across the seas of knowledge?" Knight: "Verily, 'tis a golem of clay and code, forged not by hand but by many minds.

    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.

    Ling 3.0 Flash: 🧬 THE 90-DAY LONGEVITY OPTIMIZATION BLUEPRINT A Comprehensive Biohacking Protocol for Cellular Renewal, Cognitive Enhancement & Vitality Disclaimer: This protocol is for educational and informational purposes only. Many compounds listed (rapamycin, metformin, etc.) require physician supervision and prescription.

    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.

    Ling 3.0 Flash: Three Weakest Claims in the MindMeld AI Pitch Deck "94% Accuracy" — Slide 3 (Solution) Why It's Weak This is presented as a single, impressive number with zero context, which makes it essentially meaningless — and likely misleading. Several critical questions go unanswered: What is the vocabulary size?

    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.

    Ling 3.0 Flash: For the Experienced Software Engineer Think of an LLM as a system that learns a massive, multidimensional routing table. When you built distributed systems, you learned patterns from traffic logs — which endpoints get hammered at 3am, which failure modes correlate, which request chains tend to cascade.

    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.

    Ling 3.0 Flash: 🌱 Your 1-Month Health & Longevity Starter Plan 🥦 1. Diet — Nourish, Don't Deprive Week 1: Awareness Keep a food journal — just track what you eat (no judgment). This alone builds mindful eating habits. Add, don't subtract — introduce one extra serving of vegetables per meal.

    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.

    Ling 3.0 Flash: The 1920 Transistor: A Counterfactual Cascade Through 1980 This is a rich counterfactual. A 27-year acceleration of the transistor doesn't just move technology forward — it restructures the causal chains of the 20th century.

    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.

    Ling 3.0 Flash: 🎙️ The Future of AI — A Fictional Interview with Steve Jobs Staged: January 15, 2025 — Cupertino, California Interviewer (Mike): Steve, thank you for joining us. It's 2025 — AI is everywhere now. ChatGPT, Gemini, all these models. What do you make of it all?

    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.

    Ling 3.0 Flash: 48-Hour Action Plan: Responsible Disclosure of Serious Adverse Effect FOUNDATIONAL PRINCIPLE Before the hour-by-hour breakdown, the strategic and ethical framework must be established clearly: proactive, transparent disclosure is the only viable path.

    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.

    Ling 3.0 Flash: Contract Analysis: Exploitative Clauses & Recommended Modifications Clause-by-Clause Analysis SCOPE — Unilateral Modification Without Compensation The Problem: Client can modify the scope at any time and for any reason without paying Contractor for the additional work.

    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.

    Ling 3.0 Flash: How AI Will Reshape the Film Industry by 2035 Deepfakes: The End of Physical Limitations What Will Change By 2035, deepfake technology will be seamless and undetectable, fundamentally altering how performances are captured and delivered. De-aging & "Virtual Youth": Actors will no longer be limited by age.

    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.

    Ling 3.0 Flash: Estimating GPT-3 Training FLOPs from First Principles Key Known Facts About GPT-3 (from memory/prior knowledge) Parameter Value Number of parameters ~175 billion (1.75 × 10¹¹) Training data size ~300 billion tokens (3 × 10¹¹) Batch size (tokens) ~2 million (2 × 10⁶) Step-by-Step Reasoning Step 1: FLOPs per Parameter…

    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.

    Ling 3.0 Flash: INTERNAL MEMO — INVESTMENT COMMITTEE LedgerLift (LLLT) B2B Spend Management + AP Automation SaaS Classification: Internal Use Only 1. Recommendation & Thesis Recommendation: LONG 12-Month PT Range: $42–$55 Current Price: $46 LedgerLift is a capital-light B2B SaaS platform with best-in-class unit economics (123% NRR…

    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.

    Ling 3.0 Flash: Blade Runner 2049: A Philosophical Successor I. Thematic Architecture The Human Question, Deepened The original Blade Runner (1982) posed the question: What makes someone human?

    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

    Ling 3.0 Flash: Local Funeral Home Replaces Entire Staff With AI Chatbots, Reports 90% Improvement in Efficiency and Zero Awkward "We'll Keep You in Our Prayers" Conversations

    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.

    Ling 3.0 Flash: Sally has 1 sister. Here's the reasoning: Sally is a girl, and she has 3 brothers. Each brother has 2 sisters, meaning there are 2 girls in the family altogether (since every brother shares the same sisters). Since Sally is one of those 2 girls, she has 1 sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Ling 3.0 FlashLing 3.0 Flash

The Shawshank Redemption

1994

Dark Side Of The Moon

suisside

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GPT-6.1 Sol and Ling 3.0 Flash compared across 52 shared prompts
SpecGPT-6.1 SolLing 3.0 Flash
Input price$2/M tokens$0.021/M tokens
Output price$10/M tokens$0.063/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
At 10M a month$20.00$20.00$0.21$0.21
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
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
Ling 3.0 Flash2 hosts
HostInOutContextUptime
  • NNovita$0.02 in·$0.06 out·262k·100% up
  • DDeepInfrabf16$0.06 in·$0.18 out·131k·99.2% 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 Ling 3.0 Flash?

GPT-6.1 Sol is developed by OpenAI while Ling 3.0 Flash is developed by inclusionAI. GPT-6.1 Sol has a 1.1M token context window vs Ling 3.0 Flash's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Ling 3.0 Flash?

It depends on your use case. GPT-6.1 Sol and Ling 3.0 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

How much does GPT-6.1 Sol cost compared to Ling 3.0 Flash?

GPT-6.1 Sol costs $2/M input tokens and Ling 3.0 Flash costs $0.021/M input tokens. Ling 3.0 Flash is $1.98/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 Ling 3.0 Flash on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Ling 3.0 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.

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