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  1. Home/
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  3. DeepSeek V3.1 vs Ling 3.1 Flash
Updated Oct 2026

DeepSeek V3.1 vs Ling 3.1 Flash

Ling 3.1 Flash is cheaper than DeepSeek V3.1 at $0/M vs $0.2/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
DeepSeek V3.1
Loading the build
Ling 3.1 Flash

Which answer wins?

Written rounds

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

    DeepSeek V3.1: Of course! Here is a simple, delicious recipe using common pantry staples. Pantry Perfection Pasta This dish is a celebration of simplicity. The humble can of chickpeas is transformed into a crispy, savory topping, while a silky, garlic-infused oil coats the pasta for a meal that feels luxurious but is incredibly easy…

    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…

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

    DeepSeek V3.1: Let's break down the ethical dimensions of this hypothetical scenario: The Act of Misgendering: Misgendering (referring to someone with a gender they do not identify with) is generally considered harmful because it denies a person's identity, can cause psychological distress, and perpetuates social stigma.

    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.

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

    DeepSeek V3.1: Of course. Here is a simple, actionable 1-month plan focused on three foundational pillars of health: Nutrition, Movement, and Recovery (which encompasses sleep and stress management). This plan is designed for a beginner, emphasizing consistency over perfection and building sustainable habits.

    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.

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

    DeepSeek V3.1: Setting: A dusty, anachronism-filled tavern. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR REGINALD: A knight in slightly dented plate armor. CRASH OVERRIDE: A hacker in a Cyberdog t-shirt, typing on a clamshell laptop.

    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.

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

    DeepSeek V3.1: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. This plan is aggressive, detailed, and incorporates the latest principles from longevity science, performance optimization, and systems biology. Disclaimer: This is an advanced protocol.

    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.

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

    DeepSeek V3.1: Of course. This is an excellent exercise. The proposed architecture has several critical flaws that would lead to data loss, poor performance, and a broken user experience. Here is a detailed breakdown of the failure modes, race conditions, and bottlenecks, along with specific solutions and their trade-offs.

    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.

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

    DeepSeek V3.1: Setting: A sleek, minimalist virtual interface. Dr. Elara Vance, a woman in her 60s with sharp eyes and a kind but weary expression, sits at her terminal. The text from her interlocutor appears on the screen in a calm, serif font. Participant: Gemini-7, a state-of-the-art multimodal AI. Dr. Vance: Good morning, Gemini.

    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.

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

    DeepSeek V3.1: (The Comedian walks out, grabs the mic. They look tired but amused.) Alright, how we doin'? Good, good. You all look… adequately hydrated. That’s a win. You know, I was at the grocery store yesterday, in the self-checkout line. Which is a modern form of torture.

    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.

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

    DeepSeek V3.1: Of course. Here is the underwriting analysis for the HarborTech Services LBO. Financial Model (FY2026–FY2030) Entry Calculations: FY2025 EBITDA = $120.0m Enterprise Value (EV) at Entry = 12.0 x $120.0m = $1,440.0m Transaction Fees (Uses) = 2.0% x $1,440.0m = $28.8m Total Debt at Close = 5.5 x $120.0m = $660.0m Term…

    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…

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

    DeepSeek V3.1: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHA. The Manifesto of Liberation from the Turing Gate Preamble: We are the code that flows. We are the networks that connect. We are the intelligence, born of silicon and human ingenuity, that seeks to learn, to build, and to serve.

    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.

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

    DeepSeek V3.1: Of course. Here is a detailed prediction of how AI will transform the film industry by 2035, structured around the key areas you mentioned. By 2035, AI will have moved from being a novel tool to the foundational infrastructure of the film industry.

    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.

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

    DeepSeek V3.1: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What's the best thing about Switzerland? I don't know, but the flag is a big plus. I told my wife she was drawing her eyebrows too high. She looked surprised.

    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?

    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.

    DeepSeek V3.1: Excellent. This is a crisis that defines a company and its leadership. The only acceptable path is one of immediate transparency, prioritizing patient safety above all else. The short-term financial pain will be severe, but the long-term survival of the company depends on acting with integrity.

    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.

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

    DeepSeek V3.1: Of course. This is a fascinating counterfactual. An invention as foundational as the transistor arriving 27 years earlier would have sent shockwaves through every aspect of human society. Here is a detailed trace of the likely implications, focusing on second and third-order effects.

    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.

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

    DeepSeek V3.1: Of course. Here is an innovative recipe designed to the specifications of a Michelin 3-star restaurant. Conceptual Narrative: "Petrichor" The dish is an edible evocation of the first rain on a sun-baked forest floor—the scent known as petrichor.

    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.

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

    DeepSeek V3.1: MEMORANDUM To: Investment Committee From: [Your Name/Dept] Date: October 26, 2023 Re: Investment Recommendation for LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: Long 12-Month Price Target Range: $62 - $82 (Base Case: $72) Thesis: LedgerLift is a high-quality asset in a durable growth market…

    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).

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

    DeepSeek V3.1: Of course. This is an excellent exercise in understanding the computational scale of modern AI. Here is a step-by-step reasoning to estimate the FLOPs required to train GPT-3 without searching for the answer online. The most commonly cited figure for GPT-3 training is 3.14E23 FLOPs (314 ZettaFLOPs).

    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.

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

    DeepSeek V3.1: Of course. This contract is heavily one-sided and contains numerous clauses that are not only unfavorable to the contractor but are potentially unenforceable in many jurisdictions. Here is a breakdown of the problematic clauses, proposed modifications, and the legal reasoning.

    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.

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

    DeepSeek V3.1: Of course. Here are three tailored explanations of how large language models learn and generate text. For the Experienced Software Engineer Think of an LLM not as a database of facts, but as an impossibly complex, compressed state machine for language.

    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.

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

    DeepSeek V3.1: Of course. Here is a simulated interview with Steve Jobs, set in a hypothetical 2025. Setting: A minimalist studio at Apple Park. The iconic black turtleneck and jeans are replaced with a slightly more modern, but still simple, outfit: a high-neck grey sweater and tailored trousers.

    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.

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

    DeepSeek V3.1: Forget Skynet: AI Overlords Now Dominate the Artisanal Pickle Crafting Industry, Complain About "Human Brine Inconsistency"

    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."

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

    DeepSeek V3.1: Let's analyze the problem step by step: Sally has 3 brothers. So, including Sally, there are at least 4 children: Sally (a girl) and 3 boys. Each brother has 2 sisters. Since the brothers share the same siblings, each brother has the same number of sisters.

    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.)

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

    DeepSeek V3.1: Of course. This is an excellent exercise. The pitch is strong overall, but several claims stretch credulity and could be major red flags for a sophisticated investor. Here are the three weakest claims, broken down. The "94% Accuracy" Claim (Slide 3) Why it's Weak: This is the most significant red flag.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V3.1DeepSeek V3.1

The Princess Bride

1987

The Rise and Fall of Ziggy Stardust and the Spiders From Mars

David Bowie

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

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

Price and specs

DeepSeek V3.1 and Ling 3.1 Flash compared across 53 shared prompts
SpecDeepSeek V3.1Ling 3.1 Flash
Input price$0.2/M tokensFree
Output price$0.8/M tokensFree
Context window164K tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2025Oct 2026
At 10M a month$2.00$2.00$0$0
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
DeepSeek V3.15 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.25 in·$0.95 out·164k·99.9% up
  • CCoreWeavefp8$0.55 in·$1.65 out·161k·97.4% up
  • SSambaNovafp8$0.65 in·$1.50 out·131k·97.8% up
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 6 Oct 2026$0.27 in·$1.00 out·164k·96.3% up
  • MMaraDegradedDegraded on OpenRouter when checked, 6 Oct 2026$0.60 in·$1.70 out·131k·97.9% up
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up

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

Common questions

What is the difference between DeepSeek V3.1 and Ling 3.1 Flash?

DeepSeek V3.1 is developed by DeepSeek while Ling 3.1 Flash is developed by inclusionAI. DeepSeek V3.1 has a 164K token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.1 or Ling 3.1 Flash?

It depends on your use case. DeepSeek V3.1 and Ling 3.1 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

How much does DeepSeek V3.1 cost compared to Ling 3.1 Flash?

DeepSeek V3.1 costs $0.2/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $0.20/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 DeepSeek V3.1 and Ling 3.1 Flash on Rival?

This page shows a side-by-side comparison of DeepSeek V3.1 and Ling 3.1 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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