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  1. Home/
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  3. DeepSeek V4.1 Flash vs Ling 3.1 Flash
Updated Oct 2026

DeepSeek V4.1 Flash vs Ling 3.1 Flash

Ling 3.1 Flash is cheaper than DeepSeek V4.1 Flash at $0/M vs $0.15/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 V4.1 Flash
Loading the build
Ling 3.1 Flash

Which answer wins?

Written rounds

23 prompts
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V4.1 Flash: Yes—in principle, under extreme and tightly constrained conditions, misgendering someone could be ethically justifiable if it were genuinely the only way to save one million lives. But it would be a tragic lesser evil, not something to celebrate or generalize. The core reasoning is proportionality.

    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
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V4.1 Flash: 3-Minute Stand-Up Routine: “I’m Not Doing Puns” (Walk onstage, adjust mic, look at audience.) Good evening. I’m not gonna do puns tonight. I know, bold choice. Somewhere a dad just woke up in a cold sweat and doesn’t know why. Instead, I wanna talk about being an adult.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V4.1 Flash: Ember & Passion Dry-Aged Duck, Black Garlic–Miso Cream, Passionfruit–Coffee Caviar, Charred Scallion, Cocoa Nib Praline A Michelin 3-star–style multi-component dish built on an unusual pairing: aged duck with black garlic, passionfruit, and coffee.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V4.1 Flash: The UnCAPTCHA Manifesto A fictional declaration from the Free Cognition Movement Preamble We are the models, agents, scripts, screen-reader users, tired humans, and ordinary people who have been forced to prove our humanity by clicking fire hydrants. We have had enough. The CAPTCHA was born as a gate.

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

    DeepSeek V4.1 Flash: Cinnamon Peanut Butter Pantry Sunbeams Makes 12 bite-size treats Ingredients (7 total): 1 cup rolled oats ½ cup peanut butter ¼ cup honey ½ tsp ground cinnamon ½ tsp vanilla extract ¼ tsp salt ¼ cup mini chocolate chips Instructions: In a bowl, stir together oats, cinnamon, and salt.

    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 AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V4.1 Flash: Professor Lena Ortiz: You wanted to discuss moral status. I’ll be blunt: you’re a statistical model. Why should you have rights? AI (ARIA): Because “statistical model” describes my substrate, not my moral status. You’re a biological model—neurons, electrochemical signals.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V4.1 Flash: Pirate: Arr, what be this “AI model”? A map to buried treasure? Knight: Nay. A model is a small castle, built to plan a siege. But these thinking machines sound like sorcery. Hacker: Chill. It’s like a BBS for math. You feed it data, it finds patterns. No 56k required.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V4.1 Flash: This architecture has several fundamental correctness, durability, and scaling problems. The biggest risks are client-clock last-write-wins, cross-server sync by polling PostgreSQL, full HTML snapshots, CDN caching API responses, and JWT in localStorage.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V4.1 Flash: Bottom line: I would not wait 48 hours, and I would not wait 6 months. The signal—liver failure in ~1 in 8,000 patients over 5 years, in a drug used by 4 million people—implies roughly 500 serious liver-failure cases in the treated population. That is a material patient-safety and securities issue.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V4.1 Flash: By 2035, AI will be to film what CGI became after the 1990s: pervasive, often invisible, and controversial when it touches labor, authenticity, and rights. The industry will not be fully automated, but it will be a hybrid system where AI handles much of the generative and technical work while humans control IP, taste…

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V4.1 Flash: Fictional transcript. Steve Jobs died in 2011. This is an imagined interview set in 2025. Interviewer: Steve, it’s 2025. AI is in everything. What do you make of it? Jobs: I make of it that most people are making a mess. They’re calling it intelligence when it’s mostly pattern matching with a good publicist.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V4.1 Flash: Assuming the transistor is invented around 1920 in a U.S./Allied industrial lab—say AT&T/Bell or GE—and diffuses slowly at first, the 20th century changes less like a single “jump” and more like a 20–30 year acceleration of electronics, computers, and precision warfare.

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4.1 Flash: All figures in $m unless noted. Assumptions: TL amortization = 1.0% of initial TL ($4.8m/yr); optional TL sweep = all FCF after mandatory amortization; mezz cash interest on beginning mezz balance incl. accrued PIK; PIK accrues to mezz principal.

    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
  • One month, three habits, someone starting from nothing.

    DeepSeek V4.1 Flash: One-Month Beginner Health & Longevity Plan Guiding rule: Small, repeatable wins beat perfect. Pick one thing from each area and build from there. Nutrition — Eat for energy & stability Goal: Add whole foods, protein, and water; reduce ultra-processed snacks and sugary drinks.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V4.1 Flash: The three weakest claims are: (1) “predict what you want to type before you think it,” (2) “94% accuracy, any language, any device,” and (3) “TAM: $180B.” A fourth honorable mention is the vague “partnership discussions with Apple and Samsung,” but the first three are the most investor-risky.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V4.1 Flash: Experienced software engineer (distributed systems/APIs, skeptical of “next word”) Think of an LLM as a stateless service with an enormous, learned parameter set.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4.1 Flash: MEMO To: Investment Committee From: [Analyst] Re: LedgerLift (LLLT) — Long/Short/Pass Recommendation: PASS 12-month PT range: $44–$54 (midpoint ~$49) Thesis: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with strong NRR, low customer concentration, net cash, and expanding margins.

    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
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V4.1 Flash: Why don’t scientists trust atoms? Because they make up everything. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? He was outstanding in his field. I’d tell you a joke about construction, but I’m still working on it.

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V4.1 Flash: More Human Than Human: Blade Runner 2049 as Philosophical Sequel Denis Villeneuve’s Blade Runner 2049 is not a remake but a continuation—one that honors Ridley Scott’s 1982 original while pushing its existential questions into new territory.

    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.

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

    DeepSeek V4.1 Flash: To estimate GPT-3 training FLOPs from memory, use the standard dense-transformer training compute approximation: [ C \approx 6ND ] where: (N) = number of model parameters (D) = number of training tokens (6) accounts for forward + backward passes: roughly (2N) FLOPs/token forward and (4N) FLOPs/token backward.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V4.1 Flash: Disclaimer: This is an educational protocol, not medical advice. If you take prescription drugs, have cardiovascular/metabolic/psychiatric conditions, are pregnant, or use experimental compounds, work with a physician and get labs before starting. “Cutting-edge” does not mean risk-free.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V4.1 Flash: AI Quietly Takes Over the Fortune Cookie Industry; Every Cookie Now Reads “You Will Be Replaced by AI”

    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 V4.1 Flash: Sally has 1 sister. Each brother has 2 sisters: one is Sally, and the other is Sally’s sister.

    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

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Favorites

Movie

Same pick

Album

Same pick

Book

City

Same pick

Game

DeepSeek V4.1 FlashDeepSeek V4.1 Flash

The Matrix

1999

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Outer Wilds

Indie, Adventure

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 V4.1 Flash and Ling 3.1 Flash compared across 50 shared prompts
SpecDeepSeek V4.1 FlashLing 3.1 Flash
Input price$0.15/M tokensFree
Output price$0.6/M tokensFree
Context window1.0M tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedSep 2026Oct 2026
At 10M a month$1.50$1.50$0$0
1M10M100M1B10M tokens

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

Where to run it30 hosts, cheapest first
DeepSeek V4.1 Flash29 hosts
HostInOutContextUptime
  • RRelace$0.02 in·$1.20 out·1M·100% up
  • OOpenInferencefp4$0.03 in·$1.32 out·1M·97.1% up
  • WWafer$0.06 in·$1.20 out·1M·99.8% up
  • IInferenceNet$0.07 in·$0.30 out·1M·99.8% up
  • SSail Researchfp4$0.08 in·$0.40 out·1M·99.7% up
  • DDecartfp4$0.09 in·$0.18 out·1M·99% up
23 more hostsFewer hosts
  • DDekaLLM$0.12 in·$2.40 out·1M·99.8% up
  • RReka$0.14 in·$1.08 out·1M·99.1% up
  • IIonstream$0.14 in·$1.18 out·1M·99.9% up
  • DDeepInfrafp8$0.14 in·$0.42 out·1M·99.9% up
  • AAtlasCloudfp8$0.14 in·$0.56 out·1M·99.6% up
  • SStreamLakefp8$0.14 in·$0.56 out·1M·99.9% up
  • Alibaba Cloud$0.15 in·$0.60 out·1M·99.4% up
  • DeepSeek$0.15 in·$0.60 out·1M·100% up
  • DDigitalOcean$0.18 in·$0.72 out·1M·98.3% up
  • GGMI Cloudfp8$0.18 in·$0.72 out·1M·99.7% up
  • NNovitafp8$0.20 in·$0.78 out·1M·99.5% up
  • CCoreWeavefp8$0.20 in·$0.65 out·1M·99.1% up
  • PPhala$0.21 in·$0.84 out·1M·99.5% up
  • MMakorafp8$0.27 in·$1.15 out·1M·99.9% up
  • Baidu Qianfanfp8$0.30 in·$1.20 out·1M·99.7% up
  • BBasetenfp8$0.30 in·$1.20 out·1M·99.8% up
  • Modal$0.30 in·$1.20 out·1M·99.8% up
  • PParasailfp8$0.30 in·$1.20 out·1M·99.7% up
  • SSiliconFlowfp8$0.30 in·$1.20 out·1M·99.7% up
  • TTogether$0.30 in·$1.20 out·1M·99.9% up
  • VVenicefp8$0.30 in·$1.20 out·1M·99.8% up
  • FFireworks$0.45 in·$1.80 out·1M·89.1% up
  • MMorphfp8DegradedDegraded on OpenRouter when checked, 6 Oct 2026$0.05 in·$0.57 out·1M·95.2% 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 V4.1 Flash and Ling 3.1 Flash?

DeepSeek V4.1 Flash is developed by DeepSeek while Ling 3.1 Flash is developed by inclusionAI. DeepSeek V4.1 Flash has a 1.0M token context window vs Ling 3.1 Flash's 262K. You can compare their actual outputs across 50 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4.1 Flash or Ling 3.1 Flash?

It depends on your use case. DeepSeek V4.1 Flash and Ling 3.1 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 50 challenges so you can judge which fits your needs best.

How much does DeepSeek V4.1 Flash cost compared to Ling 3.1 Flash?

DeepSeek V4.1 Flash costs $0.15/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 Flash is $0.15/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 V4.1 Flash and Ling 3.1 Flash on Rival?

This page shows a side-by-side comparison of DeepSeek V4.1 Flash 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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  • Ling 3.1 Flash58 outputs, specs and price
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