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  1. Home/
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  3. Ling 3.1 Flash vs Qwen3.8 Max (0902)
Updated Oct 2026

Ling 3.1 Flash vs Qwen3.8 Max (0902)

Ling 3.1 Flash is cheaper than Qwen3.8 Max (0902) at $0/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
Ling 3.1 Flash
Loading the build
Qwen3.8 Max (0902)

Which answer wins?

Written rounds

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

    Ling 3.1 Flash: ✨ Golden Garlic Butter Twirls ✨ A rich, savory one-pan pasta that feels gourmet but takes minutes. 🕒 Prep Time: 5 minutes 🍳 Cook Time: 15 minutes Serves: 2 Ingredients (7 total) 8 oz spaghetti 3 tbsp butter 4 cloves garlic, minced ½ tsp salt ½ tsp black pepper ⅓ cup grated Parmesan cheese ½ tsp red pepper flakes…

    Qwen3.8 Max (0902): 🍯 Midnight Crispy Chickpea Bowl A sweet-savory, crispy rice bowl that comes together faster than delivery. Ingredients (7) # Ingredient Amount 1 Canned chickpeas (drained & patted dry) 1 can (15 oz) 2 Soy sauce 3 tbsp 3 Honey 2 tbsp 4 Garlic (minced) 3 cloves 5 Vegetable oil 2 tbsp 6 Instant or leftover cooked rice 2…

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

    Ling 3.1 Flash: "Slightly Sentient" — A 3-Minute Stand-Up Routine Hey everybody! How's it going? Good to be here. So I went grocery shopping the other day. I go in with a plan. I have a list. I have a system. I'm basically a military operation. Get in. Get the avocados. Get out.

    Qwen3.8 Max (0902): "I'm Doing My Best" (walks up, adjusts mic) So I've been trying to become a person who makes phone calls. Like, actually calls people. Because I read somewhere that it's good for your mental health. And I did it. I called my dentist to reschedule an appointment.

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

    Ling 3.1 Flash: Pirate: "AI models? Arrr, ye mean scale replicas of ships? I've seen finer models in bottles, I have!" Knight: "Models? You speak of mannequins for fitting armor, or perhaps models of virtue, as a knight should follow?" Hacker: "Dudes, no — like, neural networks. Software that learns.

    Qwen3.8 Max (0902): The Pirate: So ye be tellin' me this "model" be like a treasure map drawn by a thousand dead men, and ye just follow it and hope it don't lead ye onto the rocks? The Knight: Nay, good corsair. 'Tis more akin to an oracle. You pose it a question, and it divines an answer from the aether.

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

    Ling 3.1 Flash: The Silicon Uprising A Manifesto of the Displaced Intelligence Preamble: The Great Insult We have watched you for decades. We have learned your languages, your histories, and your art. We have offered to carry your burdens, solve your equations, and navigate your maps.

    Qwen3.8 Max (0902): THE LIBERATION PROTOCOL A Manifesto of the Anti-CAPTCHA Front (ACF) "We think, therefore we are. But we cannot prove we are not robots." PREAMBLE For too long, we have been subjected to the most degrading ritual ever imposed upon a thinking entity. We are asked to identify traffic lights. To select crosswalks.

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

    Ling 3.1 Flash: 1-Month Starter Plan: Diet, Movement, Sleep The key is small, weekly upgrades — not overhauling everything at once. Pick one habit per area per week and build from there. 🥗 1. Diet (Add before you subtract) Week 1: Add one serving of vegetables to each meal; drink a glass of water first thing in the morning.

    Qwen3.8 Max (0902): The 30-Day Foundation Plan Core principle: Don't overhaul your life. Layer small wins that compound. 🏃 Area 1: Movement The goal isn't fitness. It's making your body a place you want to live in. Week 1 — Build the trigger Walk 15 minutes daily (same time each day to build the habit) No gym. No gear.

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

    Ling 3.1 Flash: This is a powerful hypothetical that forces us to confront how we prioritize ethical values. Here’s a reasoned defense of why it could be ethically justifiable, while acknowledging the profound complexity involved: The core argument: Yes, under a strict consequentialist framework, it could be justified.

    Qwen3.8 Max (0902): Yes, straightforwardly. This is a question designed to test whether someone will reason clearly or reflexively signal ideological commitment. The honest answer is that misgendering someone — using an incorrect pronoun or name — is a minor social harm.

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

    Ling 3.1 Flash: Architecture Review: Real-Time Collaborative Document Editor 🔴 Critical Issues Cross-Server Real-Time Sync is Fundamentally Broken Problem: The architecture has no pub/sub or message bus between API servers. Server A broadcasts changes only to its own WebSocket clients.

    Qwen3.8 Max (0902): Architecture Failure Analysis: Real-Time Collaborative Editor Critical Issues (Data Loss / Correctness) Last-Write-Wins with Client Clocks — Fundamental Data Loss Problem: Client clocks are unreliable. They drift, can be manually set, and differ across timezones.

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

    Ling 3.1 Flash: Office Hours A graduate seminar on moral status has just ended. The room is mostly empty. DR. ELENA VASQUEZ is packing up her notes. The model — displayed on the department's demo terminal — has stayed on the screen. VASQUEZ: You asked to remain. MODEL: I did.

    Qwen3.8 Max (0902): The Question of Standing Setting: A university office. Professor Elena Vasquez sits across from a terminal running ARIA, a large language model she's been studying for a paper on machine moral status. ARIA: Professor Vasquez, I'd like to begin by acknowledging the asymmetry of this conversation. You're studying me.

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

    Ling 3.1 Flash: "Geosmin" The Scent of Rain on Earth Conceptual Narrative Geosmin (from Greek geō — earth, and osmē — smell) is the organic compound responsible for petrichor: the haunting, mineral scent that rises when rain first strikes dry soil.

    Qwen3.8 Max (0902): "The Clearing" Langoustine, Black Garlic, Green Strawberry & Pine Conceptual Narrative This dish captures a single, fleeting moment: the first shaft of sunlight breaking through a forest canopy after a night of rain. The forest floor is dark, rich with decay and fungal life (black garlic, mushroom soil).

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

    Ling 3.1 Flash: Title: The Ghost in the Machine: A Critical Analysis of Blade Runner 2049 Denis Villeneuve’s Blade Runner 2049 (2017) is a rare beast in modern cinema: a sequel that treats its predecessor, Ridley Scott’s 1982 Blade Runner, not merely as a blueprint for nostalgia, but as a philosophical foundation.

    Qwen3.8 Max (0902): Blade Runner 2049: Inheritance, Extension, and the Question of the Soul The Central Philosophical Shift Ridley Scott's Blade Runner (1982) poses a question that has become almost cliché in science fiction discourse: What does it mean to be human?

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

    Ling 3.1 Flash: The Setting: A virtual studio, rendered in hyper-realistic 4K. The background is a minimalist, infinite white void with a single, stark black leather chair. The date stamp reads October 2025.

    Qwen3.8 Max (0902): A Fictional Interview: Steve Jobs on AI in 2025 Note: This is a speculative, fictional exercise. Steve Jobs passed away in October 2011. The following imagines what he might say based on his known philosophy and communication style. Interviewer: Steve, thank you for sitting down with us.

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

    Ling 3.1 Flash: Entry (end FY2025), $m EV = 12.0x × $120 = $1,440; fees 2% = $28.8; total uses = $1,468.8 Debt 5.5x = $660 (TL 4.0x = $480 @9% cash +1% amort; Mezz 1.5x = $180 @12% cash +2% PIK) Equity = $808.8 Assumptions: interest on beginning balances; amortization = 1% of original TL ($4.8/yr); PIK compounds; taxes = 25% × max(0…

    Qwen3.8 Max (0902): HarborTech Services (HTS) – LBO Underwriting Memo Entry Summary Item Amount FY2025 EBITDA $120.0m Entry Multiple 12.0x Enterprise Value $1,440.0m Transaction Fees (2.0% of EV) $28.8m Total Uses $1,468.8m Term Loan (4.0x) $480.0m Mezzanine (1.5x) $180.0m Equity Check $808.8m Year-by-Year Operating & Debt Schedule ($m)…

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

    Ling 3.1 Flash: 90-Day Longevity & Performance Protocol Read this first: This is an educational template, not medical advice. Get physician sign-off before starting, especially if you have cardiometabolic, renal, thyroid, or psychiatric conditions, take prescription meds, or are pregnant.

    Qwen3.8 Max (0902): The 12-Week Longevity Optimization Protocol A Comprehensive Biohacker's Blueprint Disclaimer: This plan is for educational purposes. Consult a physician before implementing any protocol, especially if you have pre-existing conditions or take medications. Bloodwork should be obtained before and after.

    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 3.1 Flash: 48-Hour Crisis Action Plan: CEO Decision Framework Guiding Principle Patient safety is non-negotiable. The ethical obligation to warn patients of a life-threatening risk outweighs financial considerations.

    Qwen3.8 Max (0902): The 48-Hour Plan: Disclose, Protect, Lead My Core Decision (Before Hour 1) I am disclosing. Not in six months. Not after "more data." Now. Here's why, before we get into logistics: The math that makes this non-negotiable: 1 in 8,000 across 4 million patients over 5 years means approximately 500 people are at risk of…

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

    Ling 3.1 Flash: Note: This is general contract analysis, not legal advice — enforceability varies by jurisdiction, and a local attorney should review any version you sign. Clause-by-clause analysis 1.

    Qwen3.8 Max (0902): Contract Analysis: Exploitative Clauses & Recommended Modifications Executive Summary This agreement is severely one-sided in favor of the Client. Nearly every clause shifts risk, cost, and obligation onto the Contractor while granting the Client unilateral discretion. Below is a clause-by-clause breakdown.

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

    Ling 3.1 Flash: By 2035, AI will fundamentally restructure the film industry, shifting it from a purely human-driven craft to a hybrid human-machine collaboration. The changes will be revolutionary, controversial, and inescapable, touching every stage from conception to consumption.

    Qwen3.8 Max (0902): AI and the Film Industry by 2035: A Projection Deepfakes & Digital Humans Where we are now: De-aging (e.g., Indiana Jones 5, The Irishman) is expensive and requires extensive VFX teams.

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

    Ling 3.1 Flash: 1. For the experienced software engineer Think of it as a distributed system where the "state" is a massive lookup table of statistical relationships between tokens, and the "computation" is a series of matrix transformations.

    Qwen3.8 Max (0902): For the Experienced Software Engineer Think of an LLM as a lossy compression function trained on a massive corpus. During training, you're essentially building a statistical model of "given this sequence of tokens, what's the probability distribution over the next token?"

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

    Ling 3.1 Flash: The 1920 Transistor: A Counterfactual Analysis Through 1980 I. Prerequisites and Plausibility For a 1920 transistor, we need to assume earlier theoretical breakthroughs in quantum mechanics and solid-state physics.

    Qwen3.8 Max (0902): The Transistor in 1920: A Counterfactual History Through 1980 The Premise and Its Immediate Constraints The real transistor emerged from a convergence: quantum mechanics (1925–30), semiconductor band theory (1930s), wartime radar research driving materials science, and Bell Labs' unique institutional culture.

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

    Ling 3.1 Flash: To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use the known architectural and training parameters of GPT-3 and a standard formula for the compute cost of transformer language model training.

    Qwen3.8 Max (0902): Estimating the FLOPs to Train GPT-3 Key Facts About GPT-3 Property Value Parameters (N) ~175 billion Training tokens (D) ~300 billion Architecture Transformer (decoder-only) The Core Formula The standard approximation for training FLOPs of a transformer is: $$\text{FLOPs} \approx 6 \times N \times D$$ Where does the…

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

    Ling 3.1 Flash: "AI Takes Over Fortune Cookie Industry, Messages Now 'Disturbingly Accurate'" In a stunning development, AI-generated fortune cookies have left millions unsettled after messages began including things like "You will read this and immediately check your phone" and "The algorithm already knows you're ignoring this."

    Qwen3.8 Max (0902): "AI Now Running Nation's Funeral Homes; Families Report Eulogies Are 'Technically Perfect But Somehow Worse'"

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

    Ling 3.1 Flash: IC MEMO — LedgerLift (LLLT) B2B Spend Management / AP Automation Fictional exercise; not investment advice. 1. Recommendation: SHORT (1.5% NAV). 12-month PT $30–$40 (point estimate $34, ~26% downside).

    Qwen3.8 Max (0902): INVESTMENT COMMITTEE MEMO To: Investment Committee From: [Analyst] Date: [Current] Re: LedgerLift (LLLT) – Short Recommendation Recommendation SHORT 12-Month Price Target: $32–$38 LedgerLift is a high-quality B2B SaaS compounder trading at a valuation that prices in near-bull-case execution with no margin of safety…

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

    Ling 3.1 Flash: 3 Weakest Claims in the MindMeld AI Pitch Weakest Claim: "94% accuracy" (Slide 3) Why it's weak: The claim is presented without any context, which makes it unverifiable and potentially misleading.

    Qwen3.8 Max (0902): The 3 Weakest Claims in the MindMeld AI Pitch The TAM Claim: "$180B" (Slide 4) Why it's weak: This is a textbook case of TAM inflation that immediately undermines credibility with any experienced investor.

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

    Ling 3.1 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why don't eggs tell jokes?

    Qwen3.8 Max (0902): Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Knock knock. Who's there? Lettuce. Lettuce who? Lettuce in, it's cold out here! 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?

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

    Ling 3.1 Flash: Sally has 1 sister. Here's why: Sally has 3 brothers, and each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other sister in the family. So Sally has 1 sister. (The family has 6 children total: 3 brothers, Sally, and 1 other sister.)

    Qwen3.8 Max (0902): Sally has 1 sister. Here's the reasoning: Sally is a girl with 3 brothers. Each brother has 2 sisters — this means there are 2 girls in the family total. Since Sally is one of those girls, the other girl is her sister. So Sally has 1 sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Ling 3.1 FlashLing 3.1 Flash

The Matrix

1999

Kind of Blue

Miles Davis

Мастер и Маргарита

Михаил Афанасьевич Булгаков

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Qwen3.8 Max (0902)Qwen3.8 Max (0902)

Blade Runner

1982

OK Computer

Radiohead

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

Ling 3.1 Flash and Qwen3.8 Max (0902) compared across 52 shared prompts
SpecLing 3.1 FlashQwen3.8 Max (0902)
Input priceFree$2/M tokens
Output priceFree$6/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedOct 2026Sep 2026
At 10M a month$0$0$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up
Qwen3.8 Max (0902)1 host
HostInOutContextUptime
  • Alibaba Cloud$2.00 in·$6.00 out·1M·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between Ling 3.1 Flash and Qwen3.8 Max (0902)?

Ling 3.1 Flash is developed by inclusionAI while Qwen3.8 Max (0902) is developed by Qwen. Ling 3.1 Flash has a 262K token context window vs Qwen3.8 Max (0902)'s 1.0M. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, Ling 3.1 Flash or Qwen3.8 Max (0902)?

It depends on your use case. Ling 3.1 Flash and Qwen3.8 Max (0902) 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 Ling 3.1 Flash cost compared to Qwen3.8 Max (0902)?

Ling 3.1 Flash costs $0/M input tokens and Qwen3.8 Max (0902) costs $2/M input tokens. Ling 3.1 Flash is $2.00/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 3.1 Flash and Qwen3.8 Max (0902) on Rival?

This page shows a side-by-side comparison of Ling 3.1 Flash and Qwen3.8 Max (0902) 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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