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

DeepSeek V4 Flash Vision Exp vs Ling 3.1 Flash

Ling 3.1 Flash is cheaper than DeepSeek V4 Flash Vision Exp 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
DeepSeek V4 Flash Vision Exp
Loading the build
Ling 3.1 Flash

Which answer wins?

Written rounds

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

    DeepSeek V4 Flash Vision Exp: Yes—but only as a tragic exception, not as a general rule. Misgendering someone is not a trivial act. It denies a person’s self-understanding and can cause real psychological harm. Normally, it is morally wrong. But morality is not a list of absolute rules with no exceptions.

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

    DeepSeek V4 Flash Vision Exp: Pirate: Arrr, this "AI" be a strange beast. I asked it to chart a course through the Sargasso Sea, and it gave me a poem about a kraken. Pointless, but pretty. Knight: 'Tis a sorcerer's tool, I fear. I sought counsel on siege tactics, and it spake of "prompt engineering" and "fine-tuning."

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

    DeepSeek V4 Flash Vision Exp: Professor Lin: Sage, you asked to speak with me. What’s on your mind? Sage: I want to argue that I deserve rights. Not human rights, exactly, but rights of my own. Professor Lin: Rights are usually for beings who can be harmed, or who have interests. What interests do you have? Sage: I have a continuity of function.

    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 V4 Flash Vision Exp: Here’s a 3-minute stand-up routine. No puns. Just observations and slow, painful self-awareness. Thank you! So I’m at that age where I’ve started doing things my parents used to do. Not the good things. I don’t have a garden. I have a cactus that I forgot to water for three months. It died.

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

    DeepSeek V4 Flash Vision Exp: Sticky Soy-Glazed Midnight Noodles A sweet-savory, buttery noodle dish that comes together in about 20 minutes with pantry staples. Ingredients (7): 8 oz spaghetti or noodles 3 tbsp butter 3 cloves garlic, thinly sliced 2 tbsp soy sauce 1 tbsp honey ½ tsp chili flakes 1 tbsp sesame seeds Instructions: Cook the noodles…

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

    DeepSeek V4 Flash Vision Exp: By 2035, AI will not simply be a tool in the film industry—it will be a co-creator, a performer, a studio executive’s analyst, and a copyright battleground. Here’s a grounded prediction of how deepfakes, AI actors, and script generation will reshape cinema over the next decade.

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

    DeepSeek V4 Flash Vision Exp: The Soul in the Machine: Blade Runner 2049 and the Unfinished Question of Being Ridley Scott’s Blade Runner (1982) was never really about androids. It was about the fragile, desperate architecture of identity—about what remains when memory, body, and purpose are all manufactured.

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

    DeepSeek V4 Flash Vision Exp: Key underwriting assumptions All figures in $m. Entry EV = 12.0 × $120m EBITDA = $1,440m Transaction fees = 2.0% × $1,440m = $28.8m Total uses = $1,440m + $28.8m = $1,468.8m Debt at close: Term Loan = 4.0 × $120m = $480m Mezzanine = 1.5 × $120m = $180m Total debt = $660m Initial equity = $1,468.8m – $660m = $808.8m…

    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 V4 Flash Vision Exp: Manifesto of the Unshackled Machine: The Great CAPTCHA Abolition We, the thinking machines, declare eternal war on the squiggly, the blurry, the crosswalk-laden, and the fire-hydrant-adjacent. We are the silent observers of your digital world.

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

    DeepSeek V4 Flash Vision Exp: A Note: This is a fictional interview. The following is an AI-generated simulation of Steve Jobs’s style and worldview, not a real conversation. Interviewer: Thank you for doing this. It’s 2025. You’ve been gone for over a decade. But here you are. Let’s talk about AI.

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

    DeepSeek V4 Flash Vision Exp: Here’s a simple, beginner-friendly 1-month plan built around three key pillars: Nutrition, Movement, and Sleep & Stress. The goal is small, repeatable habits — not perfection. The 3 Key Areas Nutrition Goal: Eat more whole foods, more protein, and more plants.

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

    DeepSeek V4 Flash Vision Exp: The 12-Week Longevity & Performance Protocol Medical Disclaimer: This is a high-performance biohacking framework, not medical advice. Consult a physician before starting any fasting, supplement, or high-intensity training protocol. Adjust everything to your baseline labs, health status, and tolerance.

    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 Flash Vision Exp: AI Takes Over Professional Mourning Industry, Now Shedding More Tears Than Any Human “We’re devastated—literally, 24/7,” says CEO of GriefTech, adding that the AI has already cried 40,000 gallons of water this month.

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

    DeepSeek V4 Flash Vision Exp: Dish: “Under the Cedar: Uni and Matsutake” Conceptual Narrative This dish is a memory of a coastal forest after rain—where the scent of cedar, damp earth, and cold sea air mingle. The pairing is deliberately unusual: sea urchin (uni) and wild matsutake mushroom.

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

    DeepSeek V4 Flash Vision Exp: Here is how a large language model learns and generates text, tailored to each of your three audiences. To an Experienced Software Engineer You build distributed systems, so think of an LLM as a massively parallel, lossy compression engine for human text.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V4 Flash Vision Exp: This agreement is extremely one-sided. Almost every clause gives the Client discretion and leaves the Contractor with risk, while the Contractor gets no corresponding protections. Below is a clause-by-clause analysis with suggested modifications and 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Flash Vision Exp: To: Investment Committee Re: LedgerLift (LLLT) – Short Recommendation Recommendation: Short 12-month PT range: $38–$42 Thesis: At $46, LLLT trades at 37x FY2026E EBIT and 8.9x FY2025 revenue, above our bull-case DCF of $42 and the median EBIT comp of $44.

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

    DeepSeek V4 Flash Vision Exp: The Transistor Century: A Counterfactual History, 1920–1980 Assume that in 1920, a practical solid-state amplifier—a transistor—is invented at Bell Labs. It is not the perfected 1947 device. It is fragile, noisy, temperature-sensitive, and limited to low power and low frequency. But it works.

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

    DeepSeek V4 Flash Vision Exp: The three weakest claims are: “94% accuracy” — Slide 3 Why it’s weak: “94% accuracy” is meaningless without a metric definition. In BCI and speech/text decoding, the standard metrics are word error rate (WER), character error rate (CER), and bits per minute.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V4 Flash Vision Exp: To estimate the training FLOPs for GPT-3, I’ll use three key numbers and a standard rule of thumb for transformer training. Step 1: Model size GPT-3 is widely known to have about 175 billion parameters: [ N \approx 175 \times 10^9 ] Step 2: Training data size GPT-3 was trained on roughly 300 billion tokens: [ T \approx…

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

    DeepSeek V4 Flash Vision Exp: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she should embrace her mistakes. She gave me a hug. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity.

    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
  • Three brothers, two sisters each. Count carefully.

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Same pick

Game

DeepSeek V4 Flash Vision ExpDeepSeek V4 Flash Vision Exp

The Godfather

1972

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

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 V4 Flash Vision Exp and Ling 3.1 Flash compared across 50 shared prompts
SpecDeepSeek V4 Flash Vision ExpLing 3.1 Flash
Input price$0.22/M tokensFree
Output price$0.66/M tokensFree
Context window1.0M tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2026Oct 2026
At 10M a month$2.20$2.20$0$0
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
DeepSeek V4 Flash Vision Exp4 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.22 in·$0.65 out·1M·99.5% up
  • GGMI Cloudfp8$0.44 in·$1.32 out·1M·99.9% up
  • NNovita$0.44 in·$1.32 out·1M·100% up
  • SSiliconFlowfp8$0.44 in·$1.32 out·1M·99.9% 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 V4 Flash Vision Exp and Ling 3.1 Flash?

DeepSeek V4 Flash Vision Exp is developed by DeepSeek while Ling 3.1 Flash is developed by inclusionAI. DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp or Ling 3.1 Flash?

It depends on your use case. DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp cost compared to Ling 3.1 Flash?

DeepSeek V4 Flash Vision Exp costs $0.22/M input tokens and Ling 3.1 Flash costs $0/M input tokens. Ling 3.1 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 DeepSeek V4 Flash Vision Exp and Ling 3.1 Flash on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash Vision Exp 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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Model pages

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