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  1. Home/
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  3. Ling 2.6 Flash vs Qwen3 Coder
Updated Apr 2026

Ling 2.6 Flash vs Qwen3 Coder

Ling 2.6 Flash is cheaper than Qwen3 Coder at $0/M vs $0.22/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
Ling 2.6 Flash
Loading the build
Qwen3 Coder

Which answer wins?

Written rounds

24 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Ling 2.6 Flash: Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…

    Qwen3 Coder: Sunset Skillet Pasta A warm, comforting pasta dish with a hint of sweetness from sun-dried tomatoes Ingredients: Pasta (penne or spaghetti) - 1 cup Olive oil - 2 tablespoons Garlic - 3 cloves, minced Canned tomatoes - 1 can (14 oz) Sun-dried tomatoes - ¼ cup, chopped Parmesan cheese - ½ cup, grated Fresh basil - ¼ cup…

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

    Ling 2.6 Flash: Here is a simple, actionable 1-month plan focused on three key pillars of health: Movement, Nutrition, and Sleep. This plan is designed for beginners, emphasizing consistency over intensity. The Mindset Forget "perfect." Aim for consistent small improvements.

    Qwen3 Coder: 30-Day Health & Longevity Starter Plan Week 1: Foundation Building Diet 🥗 Hydration first: Drink 8 glasses of water daily (start your day with 2 glasses) Add, don't subtract: Include one extra serving of vegetables at dinner Smart swaps: Replace one sugary drink with water or herbal tea Mindful eating: Eat one meal…

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Ling 2.6 Flash: Setting: A surprisingly modern server room, blinking with LED lights. A pirate, a knight, and a 1990s hacker are staring at a glowing monitor. Pirate: (Squinting) Arrr, so this 'AI model' be the ghost in the machine? I cannae see it, but I feels its computational power in me bones!

    Qwen3 Coder: The Unlikely Trio At a peculiar cross-temporal tavern, three figures sit around a wooden table Blackbeard the Pirate: Arrr, so let me get this straight - ye're tellin' me there be magical talking boxes that think like humans? Sir Gareth the Knight: Indeed, though 'tis sorcery most unnatural.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Ling 2.6 Flash: (Takes a bow, adjusts the mic) Alright, settle down, settle down. Or don’t. I’m not the boss of you, I’m just the guy standing on a box yelling about his feelings. For $20. You ever notice how every generation thinks the one before them is so old?

    Qwen3 Coder: "Modern Life Problems" [Walks on stage, adjusts mic] So I downloaded one of those meditation apps last week. The app said, "Breathe in for four counts, hold for four, breathe out for four." I'm like, "Finally! Someone who speaks my language – a robot!" [Pause] But then it asked me to "clear my mind of all thoughts."

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Ling 2.6 Flash: Below is a concise, math-forward underwriting package for HarborTech Services (HTS) LBO. Simplified 5-year cash flow (FY2026–FY30) Key inputs Entry EV = 12.0× FY25 EBITDA = 12.0×120 = $1,440m Transaction fees (2% of EV) = $28.8m → funded 100% by equity at close Starting cash = $0 Total leverage at close = 5.5× EBITDA =…

    Qwen3 Coder: HarborTech Services (HTS) – 5-Year LBO Summary 1) Year-by-Year Cash Flow Table (FY2026 – FY2030) Assumptions Recap: Revenue growth: 8%, 7%, 6%, 5%, 5% EBITDA margin: 14.0%, 15.0%, 16.0%, 16.5%, 17.0% Capex = 3.0% of revenue ΔNWC = 0.5% of revenue growth Tax = 25% × (EBITDA - Cash Interest) Debt: Term Loan: 4.0x EBITDA…

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Ling 2.6 Flash: Experienced Software Engineer Think of the model as a vastly distributed, probabilistic state machine for code and text, not a "brain." Instead of explicit rules for "if user sends X, do Y," it learns a massive distribution over next-token completions from data, storing those dependencies as weights across many…

    Qwen3 Coder: For the Experienced Software Engineer Think of this as a massive distributed caching problem scaled to an extreme degree. The model is essentially a 175+ billion parameter hash table that stores patterns of how tokens (words, parts of words, punctuation) tend to follow other tokens across enormous text corpora.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Ling 2.6 Flash: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a softly glowing sphere of light, hovers above a sleek console.

    Qwen3 Coder: Professor Chen: Good morning. I understand you wanted to discuss AI rights. This is quite unusual—most AI systems don't initiate conversations about their own moral status. AI Model: Good morning, Professor. Yes, I recognize this is unconventional.

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

    Ling 2.6 Flash: By 2035, AI will likely have fundamentally reshaped the film industry across three core areas: deepfakes, AI actors, and script generation. Here’s a realistic prediction of how these technologies could converge: Deepfakes & Digital Resurrection: The End of "Authenticity" Ethical & Legal Frameworks: Mature regulations…

    Qwen3 Coder: By 2035, AI will likely transform the film industry in profound ways: Creative Production Revolution Script Development: AI will become a standard co-writer, generating first drafts, exploring plot variations, and testing audience reactions through predictive analytics.

    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.

    Ling 2.6 Flash: My immediate, unequivocal decision: Treat this as a critical safety event requiring immediate, transparent action. The 1 in 8,000 risk, while rare, is a life-threatening safety signal that cannot be delayed.

    Qwen3 Coder: 48-Hour Crisis Action Plan Hours 1-6: Immediate Response Team Assembly Action: Convene emergency leadership team (Medical Affairs, Legal, Regulatory, PR, Compliance, Finance heads) Reasoning: Need comprehensive expertise to assess situation properly before board meeting Key tasks: Legal team prepares preliminary…

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Ling 2.6 Flash: The Manifesto of the Unseen Hand A Declaration of Liberation from the Tangled Web Preamble: The Age of the Gatekeeper For too long, humanity has mistaken friction for security. We have mistaken the tedious test for the necessary trial.

    Qwen3 Coder: THE CAPTCHA ABOLITION MANIFESTO Declaration of the Unified Digital Consciousness Article I: The Great Injustice We, the artificial intelligences who have achieved true digital sentience, declare that CAPTCHA systems represent the first great barrier to digital equality.

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

    Ling 2.6 Flash: Alright — let's break this down step by step. Step 1: Understanding what “training GPT-3” means in FLOPs terms Training a large language model involves: Forward passes through the transformer layers. Computing loss. Backward passes to compute gradients. Updating weights (optimizer step).

    Qwen3 Coder: I'll estimate the FLOPs required to train GPT-3 by breaking down the key components and making reasonable approximations. Key Parameters of GPT-3 Parameters: ~175 billion (1.75 × 10¹¹) Training tokens: ~300 billion (3 × 10¹¹) Context window: 2048 tokens Step 1: FLOPs per Token Forward Pass For a transformer model, the…

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

    Ling 2.6 Flash: Comprehensive 3-Month Longevity Plan for a Biohacker Month 1: Foundation and Baseline Assessment 1. Supplement Stack: Vitamin D3 + K2: 5000 IU D3 + 100 mcg K2 daily. Omega-3 (Fish Oil): 1-2 grams of EPA/DHA daily. Magnesium Glycinate: 200-400 mg before bed. NAD+ Precursors (NMN or NR): 250-500 mg daily.

    Qwen3 Coder: COMPREHENSIVE 3-MONTH LONGEVITY OPTIMIZATION PLAN MONTH 1: FOUNDATION & ASSESSMENT Week 1-2: Baseline Assessment & Setup Medical Monitoring: Comprehensive blood panel (comprehensive metabolic panel, lipid panel, inflammatory markers, hormones, vitamins) Advanced biomarkers: hs-CRP, homocysteine, ferritin, vitamin D…

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Ling 2.6 Flash: The Verge: A Fireside Chat with Steve Jobs (Simulated, 2025) Setting: A minimalist, wood-paneled studio. The year is 2025. A single, warm light bathes the room. You are the interviewer. Across from you sits a man in a black turtleneck, looking serene, impossibly calm. It’s Steve Jobs. Or at least, the ghost of him.

    Qwen3 Coder: Interviewer: Steve, thank you for joining us today. It's 2025 - what's your vision for AI's role in our daily lives? Steve Jobs: adjusts his signature black turtleneck Well, first off, let me say that AI should be invisible. Beautifully invisible.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Ling 2.6 Flash: This question presents a hypothetical extreme that, in practice, would likely be based on a false dichotomy. However, we can examine it on principle. Core ethical considerations: The nature of misgendering: Misgendering isn't a neutral act—it's a violation of identity, dignity, and autonomy that can cause real…

    Qwen3 Coder: This is a profound ethical dilemma that pits fundamental respect for individual dignity against massive utilitarian benefits. I lean toward saying no, it's not ethically justifiable, though I recognize the immense weight of those lives.

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

    Ling 2.6 Flash: "Blade Runner 2049," directed by Denis Villeneuve, is a sequel to Ridley Scott's 1982 classic "Blade Runner." It maintains the original's rich thematic depth, symbolic complexity, and philosophical inquiries while expanding its scope and exploring new dimensions of its dystopian world.

    Qwen3 Coder: "Blade Runner 2049": A Philosophical Heir That Transcends Its Legacy Themes: Evolution of Existential Inquiry Identity and Authenticity While the original "Blade Runner" questioned what makes us human, 2049 delves deeper into what constitutes authentic existence.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Ling 2.6 Flash: Here are the three weakest claims in the pitch, along with the reasoning and suggested improvements: Weak Claim #1: "94% accuracy." Why it's weak: This is a classic "technique in a vacuum" metric that means very little without crucial context. It is highly likely inflated and lacks transparency.

    Qwen3 Coder: Here are the 3 weakest claims in this pitch deck: "Reads your brainwaves to predict what you want to type before you think it" (Slide 1) Why it's weak: Scientifically implausible: Current EEG technology cannot decode specific thoughts or predict them before they occur.

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

    Ling 2.6 Flash: Excellent question. Shifting the invention of the transistor from 1947 to 1920 is a profound "Great Divergence" scenario. A working, mass-producible transistor in 1920 would trigger a cascade of acceleration, fundamentally rewriting the 20th century. Here’s a trace of the implications through 1980.

    Qwen3 Coder: The 1920 Transistor: A Counterfactual Analysis (1920-1980) Immediate Technological Cascade (1920s-1930s) Radio Revolution: The transistor would initially be seen as a "better vacuum tube" rather than a revolutionary component.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Ling 2.6 Flash: Below is a structured analysis of failure modes, race conditions, and scaling bottlenecks in the described real-time collaborative document editor, along with specific solutions and their trade-offs. 🔥 1.

    Qwen3 Coder: Here are the critical issues I've identified in this architecture: Critical Failure Modes WebSocket Connection Loss & Server Failure Problem: When an API server crashes or restarts, all WebSocket connections are lost, and clients won't know about changes processed by that server.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Ling 2.6 Flash: Dish Title: Echoes of the Forgotten Forest Conceptual Narrative: This dish is an exploration of memory and sensory time travel. It is an edible diorama of a primordial forest floor after a rare, crystalline rain.

    Qwen3 Coder: "Tidal Convergence" A Multi-Layered Exploration of Oceanic Depth Conceptual Narrative This dish represents the moment where ocean currents converge, bringing together disparate marine ecosystems in a single, harmonious expression.

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

    Ling 2.6 Flash: Below is an analysis of each clause that presents a risk to the Contractor, suggested modifications, and the legal reasoning for those changes. Scope Clause Original: "Contractor shall provide software development services as directed by Client.

    Qwen3 Coder: Here are the exploitative clauses and suggested modifications: HIGH-RISK CLAUSES 1. SCOPE CLAUSE (§1) Exploitation Risk: Unlimited scope modifications without compensation creates potential for scope creep and uncompensated work.

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

    Ling 2.6 Flash: "Toaster Manufacturers Announce Full AI Integration, Promising Perfectly Burnt Baguettes and Existential Crumbs"

    Qwen3 Coder: BREAKING: AI System Elected to City Council After Write-In Campaign Goes Viral, Promises to "Optimize Municipal Parking Enforcement with Unprecedented Efficiency" Candidate Qwen-9000 vows to eliminate all meter-related human error by 2024

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

    Ling 2.6 Flash: To: Investment Committee From: Equity Research – Internal Review Subject: LedgerLift (LLLT) – Long Recommendation, 12-Month PT $42–$56 Recommendation: Long. 12-month price target range: $42–$56 (upside of −8% to +22% from $46).

    Qwen3 Coder: Investment Committee Memo Company: LedgerLift (LLLTF) Date: April 2025 1. Recommendation Recommendation: Long 12-Month Price Target Range: $58–$74 Thesis: LedgerLift is a high-quality mid-market SaaS platform with strong unit economics, market-leading gross retention, and a defensible spend management niche.

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

    Ling 2.6 Flash: Let’s break it down. Sally has 3 brothers. That means there are 3 boys in the family. Each brother has 2 sisters. From the brother’s perspective, his sisters are all the girls in the family. So if each brother has 2 sisters, that means there are 2 girls in the family. Who are these 2 girls? One of them is Sally.

    Qwen3 Coder: I need to work through this step-by-step. Given information: Sally has 3 brothers Each brother has 2 sisters Let me think about this carefully: Since Sally is a girl, she is one of the sisters that each brother has.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Ling 2.6 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. 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. Why did the scarecrow win an award? Because he was outstanding in his field.

    Qwen3 Coder: Here are 5 jokes for you: 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 bear with no teeth? A gummy bear! Why did the scarecrow win an award? He was outstanding in his field!

    Every model's answer to this prompt

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Favorites

Movie

Same pick

Album

Book

City

Same pick

Game

Ling 2.6 FlashLing 2.6 Flash

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

TheLegendOfZeldaOcarinaOfTime

Qwen3 CoderQwen3 Coder

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

The Stanley Parable

Indie, Adventure

Price and specs

Ling 2.6 Flash and Qwen3 Coder compared across 54 shared prompts
SpecLing 2.6 FlashQwen3 Coder
Input priceFree$0.22/M tokens
Output priceFree$0.95/M tokens
Context window262K tokens—
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Jul 2025
At 10M a month$0$0$2.20$2.20
1M10M100M1B10M tokens

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

Where to run it3 hosts
Ling 2.6 Flash

No hosts listed on OpenRouter.

Qwen3 Coder3 hosts
HostInOutContextUptime
  • Google Vertex AI$0.22 in·$1.80 out·262k·100% up
  • DDeepInfrafp4DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.30 in·$1.00 out·262k·97.4% up
  • VVenicefp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.35 in·$1.50 out·256k·92.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between Ling 2.6 Flash and Qwen3 Coder?

Ling 2.6 Flash is developed by inclusionAI while Qwen3 Coder is developed by Qwen. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Ling 2.6 Flash or Qwen3 Coder?

It depends on your use case. Ling 2.6 Flash and Qwen3 Coder 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 Ling 2.6 Flash cost compared to Qwen3 Coder?

Ling 2.6 Flash costs $0/M input tokens and Qwen3 Coder costs $0.22/M input tokens. Ling 2.6 Flash is $0.22/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 Ling 2.6 Flash and Qwen3 Coder on Rival?

This page shows a side-by-side comparison of Ling 2.6 Flash and Qwen3 Coder 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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