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  1. Home/
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  3. Ling 3.1 Flash vs Qwen3.7 Flash
Updated Oct 2026

Ling 3.1 Flash vs Qwen3.7 Flash

Ling 3.1 Flash is cheaper than Qwen3.7 Flash at $0/M vs $0.03/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
Qwen3.7 Flash

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…

    Qwen3.7 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.

    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…

    Qwen3.7 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…

    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.

    Qwen3.7 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?

    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.

    Qwen3.7 Flash: 🌱 30-Day Health & Longevity Starter Plan This plan focuses on the three most evidence-backed pillars of longevity: Nutrition, Movement, and Sleep/Recovery. It’s designed for beginners: low barrier to entry, zero equipment required, and built on consistency over intensity. You’ll progress gradually so habits stick.

    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.

    Qwen3.7 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?”

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 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…

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 Flash: This is a high-stakes crisis requiring decisive, legally compliant, ethically grounded, and strategically coordinated action. Below is a structured, hour-by-hour executive playbook for the next 48 hours, followed by cross-cutting rationale addressing your specified dimensions.

    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."

    Qwen3.7 Flash: AI Dominates Cloud-Watching Industry, Launches 'Predictive Sky' App That Names Clouds Before They Form; Human Imagination Collapses as Users Demand Refunds for 'Spoiled Daydreams'

    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.

    Qwen3.7 Flash: Here’s a structured breakdown of the critical failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with targeted solutions and their trade-offs. 🔴 1.

    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?

    Qwen3.7 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.

    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.

    Qwen3.7 Flash: By 2035, AI will not replace the film industry; it will fundamentally restructure its creative, economic, and ethical architecture. Rather than a sudden takeover, we will see a normalized, hybrid pipeline where human intentionality guides increasingly autonomous AI systems.

    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.

    Qwen3.7 Flash: 🧬 3-Month Longevity & Performance Optimization Protocol For the evidence-driven biohacker seeking metabolic resilience, neural efficiency, muscular integrity, and systemic homeostasis.

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 Flash: This counterfactual traces a plausible diffusion curve for an early transistor invention, acknowledging that while the underlying physics could be known in 1920, practical adoption would be constrained by materials science, precision manufacturing, and institutional readiness.

    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).

    Qwen3.7 Flash: TO: Investment Committee FROM: Equity Research DATE: October 24, 2025 SUBJECT: LedgerLift (LLLT) – IC Memo Recommendation & Thesis Recommendation: Long 12-Month PT Range: $48–$58 Thesis: LedgerLift combines sticky mid-market AP automation with a fortress balance sheet ($1.4B net cash), positioning it to capture…

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 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.

    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.

    Qwen3.7 Flash: This agreement contains several highly one-sided provisions that create significant legal, financial, and operational risks for the contractor. Below is a clause-by-clause analysis identifying exploitation risks, recommended modifications, and the underlying legal reasoning. Note: Contract law varies by jurisdiction.

    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.

    Qwen3.7 Flash: Denis Villeneuve's Blade Runner 2049 (2017), shot by the legendary Roger Deakins, stands as a rare cinematic achievement: a sequel that does not merely replicate the aesthetic of its predecessor but rigorously interrogates and evolves its philosophical core.

    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.

    Qwen3.7 Flash: Here’s a step-by-step reasoning to estimate the total FLOPs required to train GPT-3, relying only on architectural principles, standard deep learning compute accounting, and publicly known specifications of GPT-3.

    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.)

    Qwen3.7 Flash: Sally has 1 sister. Why? If each of the 3 brothers has 2 sisters, that means there are only 2 girls in the entire family. Since Sally is one of those two girls, the other girl is her sister. Therefore, Sally has exactly 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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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

Qwen3.7 FlashQwen3.7 Flash

Blade Runner

1982

Abbey Road

The Beatles

Moby Dick

Herman Melville

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, Ling 3.1 Flash has the edge: bigger model tier, newer.

Ling 3.1 Flash and Qwen3.7 Flash compared across 54 shared prompts
SpecLing 3.1 FlashQwen3.7 Flash
Input priceFree$0.03/M tokens
Output priceFree$0.13/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedOct 2026Jul 2026
At 10M a month$0$0$0.30$0.30
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
Qwen3.7 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.03 in·$0.13 out·1M·99.9% 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 Qwen3.7 Flash?

Ling 3.1 Flash is developed by inclusionAI while Qwen3.7 Flash is developed by Qwen. Ling 3.1 Flash has a 262K 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.

Which is better, Ling 3.1 Flash or Qwen3.7 Flash?

It depends on your use case. Ling 3.1 Flash 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.

How much does Ling 3.1 Flash cost compared to Qwen3.7 Flash?

Ling 3.1 Flash costs $0/M input tokens and Qwen3.7 Flash costs $0.03/M input tokens. Ling 3.1 Flash is $0.03/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 Qwen3.7 Flash on Rival?

This page shows a side-by-side comparison of Ling 3.1 Flash 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.

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Same lab, same size, long tail

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Model pages

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