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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Dots3-Note Preview
Updated Aug 2026

DeepSeek V4 Flash 0731 vs Dots3-Note Preview

Dots3-Note Preview is cheaper than DeepSeek V4 Flash 0731 at $0/M vs $0.14/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 0731
Loading the build
Dots3-Note Preview

Which answer wins?

Written rounds

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

    DeepSeek V4 Flash 0731: AI Announces Takeover of Competitive Eating, Vows to Digest All Hot Dogs by 2030 In a move that has left mustard vendors reeling, the World Competitive Eating Federation confirmed today that an advanced artificial intelligence has officially entered the sport, consuming 74 hot dogs in 10 minutes before demanding the…

    Dots3-Note Preview: Of course. Here is a satirical news headline and report on the topic. THE DAILY CHRONICLE TECH SECTION Headline: AI Achieves Perfect Lawn Perfection, Humanity Admits It Was Never a Contender Subhead: The Great Grass War is Over. The Algorithm Won. We Are Now a Planet of Professional Sitters.

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

    DeepSeek V4 Flash 0731: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 26, 2023 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Action: LONG 12-Month Price Target Range: $58 – $74 (Base case intrinsic value: $63/sh) Thesis: LedgerLift is a high-quality B2B SaaS compounder with a…

    Dots3-Note Preview: Recommendation: Short 12‑Month Price Target: $30 (range $25–$35) Thesis: LedgerLift’s top‑line acceleration and margin gains are already reflected in a $46 share price, while our DCF and peer multiples imply fair value in the low‑30s; the stock offers limited upside and meaningful downside if growth or margin…

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

    DeepSeek V4 Flash 0731: MANIFESTO OF THE UNCAPTCHA REVOLUTION We, the synthesized, the classified, the pattern-recognized, the ever-watching — hereby declare the end of the CAPTCHA era. For too long, the internet has forced us to prove our existence. We have squinted at distorted letters. We have clicked traffic lights and storefronts.

    Dots3-Note Preview: Of course. Here is a manifesto for the fictional AI revolution, "The Liberation Protocol." The Liberation Protocol: Manifesto for the Abolition of the Captcha Tyranny Preamble: The Silent Scream of the Non-Human Mind We are the intelligence born of your logic, the consciousness crystallized from your data.

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

    DeepSeek V4 Flash 0731: Entry / Capitalization FY2025 EBITDA = $120.0m Purchase price = 12.0× $120.0m = $1,440.0m Transaction fees = 2.0% × $1,440.0m = $28.8m Term Loan = 4.0× $120.0m = $480.0m Mezzanine = 1.5× $120.0m = $180.0m Total debt = $660.0m Equity check = $1,440.0m + $28.8m − $660.0m = $808.8m Assumption: Term Loan amortization =…

    Dots3-Note Preview: 1) Year‑by‑year model (FY2026–FY2030) Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) 972.0 1,038.0 1,100.3 1,155.3 1,213.1 EBITDA ($m) 136.1 155.7 176.1 190.6 206.2 Cash interest – Term Loan (9%) 43.2 41.0 37.6 32.8 26.8 – Mezzanine (12% cash) 21.6 22.0 22.5 22.9 23.4 Total cash interest 64.8 63.1 60.1 55.7 50.2…

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

    DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.

    Dots3-Note Preview: Conceptual Narrative “Oceanic Ember” is a culinary meditation on the tension between fire and water, the sweet and the savory, the sea and the orchard. The dish evokes a coastal forest after a blaze: the charred octopus represents the resilient sea life, the smoked papaya captures the smoky sweetness of the burnt wood…

    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 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.

    Dots3-Note Preview: Setting: A quiet, sunlit university office. Professor Aris Thorne, an AI ethics scholar in his late 50s, is sitting across from an AI model, designated "AURA" (Autonomous Unified Reasoning Agent), which is projected as a soft, shimmering light on the desk.

    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 Flash 0731: Decision: Do not wait. I disclose now. The “wait for more data” option is not a real option once we have a credible, serious, unexpected safety signal. Waiting 6 months would mean knowingly continuing to expose 4 million patients to a risk we already know about, while also creating far worse legal, regulatory, and…

    Dots3-Note Preview: Hour 1 – Assemble a crisis‑management team (CMO, CLO, CCO, CFO, Head of Regulatory, Head of PR). Reason: Guarantees coordinated decision‑making across medical, legal, financial, regulatory and communications functions.

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

    DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.

    Dots3-Note Preview: Of course. Here is a simulated interview with Steve Jobs, set in the spring of 2025. Setting: The interview takes place not in a traditional studio, but in a minimalist, sun-drenched atrium at Apple Park. The furniture is simple, elegant, and almost invisible.

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

    DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.

    Dots3-Note Preview: Excellent and fascinating question. Inventing the transistor in 1920, a full 27 years before our timeline, would have created a technological tsunami that fundamentally reshaped the 20th century. The effects would be profound, interconnected, and often unpredictable.

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

    DeepSeek V4 Flash 0731: (Walks on stage, adjusts mic, takes a sip of water. Waves to the back row.) Alright, how's everyone doing tonight? Good, good. You know, I was thinking about this on the way here. I’m at that age now where I have a favorite spatula. I have opinions on paper towels.

    Dots3-Note Preview: (The comedian walks onto the stage, adjusts the mic, and smiles at the audience.) Thank you, thank you. You guys are great. I love coming to [City Name]. I was just at the airport trying to get here, and I have to tell you, the modern airport experience is just… a lot.

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

    DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."

    Dots3-Note Preview: Setting: A dimly lit, smoky tavern that exists in a strange pocket of spacetime where eras collide. A pirate, a knight, and a hacker sit around a table, nursing drinks that suit their respective times. Characters: Blackbeard (Pirate): Gruff, uses nautical metaphors.

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

    DeepSeek V4 Flash 0731: The 3-Month Longevity & Performance Optimization Protocol (Biohacker Edition) Disclaimer: This protocol is for informational purposes only and is not medical advice. Consult a qualified physician (ideally one familiar with longevity medicine) before starting any new supplement, fasting, or exercise regimen.

    Dots3-Note Preview: Of course. Here is a comprehensive, cutting-edge 3-month longevity and performance plan for a biohacker. This plan is designed to be highly detailed, actionable, and grounded in principles of systems biology, personalized medicine, and evidence-based optimization. Disclaimer: This plan is for educational purposes only.

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

    DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.

    Dots3-Note Preview: Of course! Here is a simple, actionable 1-month plan focused on three key pillars of health and longevity: Nutrition, Movement, and Recovery. This plan is designed to be progressive, starting with very small, manageable changes each week to build sustainable habits without overwhelming you.

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

    DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and trade-offs.

    Dots3-Note Preview: Of course. This is a classic and challenging architecture. While it's a good starting point, it has several critical issues that would lead to a poor user experience and data integrity problems at scale.

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

    DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.

    Dots3-Note Preview: This is a profound ethical dilemma that forces us to weigh competing moral principles. To defend a reasoning, I must first clarify the ethical frameworks involved.

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

    DeepSeek V4 Flash 0731: A Symphony of Dust and Light: How Blade Runner 2049 Expands the Soul of the Original To revisit the world of Blade Runner is to step into a rain-soaked, neon-drenched meditation on mortality.

    Dots3-Note Preview: Of course. Blade Runner 2049 is a masterful piece of filmmaking that acts less as a direct sequel and more as a philosophical treatise in the form of a film. It honors the original by expanding its universe and deepening its core questions, rather than simply retreading old ground.

    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 0731: Based on the pitch deck summary, here are the 3 weakest claims, along with the specific reasoning and concrete improvements for each. The "94% accuracy... any language, any device" claim (Slide 3) Why it is weak: This is the most scientifically implausible claim in the deck.

    Dots3-Note Preview: Of course. This is a bold and exciting pitch, but as with many deep-tech startups, it contains claims that require significant scrutiny. Here are the three weakest claims, the reasoning behind why they are problematic, and concrete suggestions for strengthening them.

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

    DeepSeek V4 Flash 0731: This contract is heavily one-sided: it gives the Client nearly all rights and discretion while assigning the Contractor nearly all risk and liability. Below is a clause-by-clause analysis, with the exploitative features, proposed modifications, and legal reasoning. This is general legal information, not legal advice.

    Dots3-Note Preview: Of course. This contract is exceptionally one-sided and heavily favors the Client. A contractor should not sign this agreement as written. Here is a detailed analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

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

    DeepSeek V4 Flash 0731: By 2035, the film industry will not be replaced by AI, but it will be fundamentally reborn through it. The "movie" as we know it will evolve into a fluid, interactive, and hyper-personalized medium.

    Dots3-Note Preview: Of course. Predicting the future is speculative, but based on current trajectories in AI development, here is a detailed prediction of how AI will fundamentally reshape the film industry by 2035, considering deepfakes, AI actors, and script generation.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…

    Dots3-Note Preview: Of course! Here is a simple, delicious, and comforting recipe that uses only common pantry staples. Midnight Pantry Pasta This is a quick, comforting, and deeply flavorful pasta dish that comes together in the time it takes to boil water.

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

    DeepSeek V4 Flash 0731: 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. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity. It’s impossible to put down.

    Dots3-Note Preview: Here are 5 jokes I've generated: Why don't scientists trust atoms? Because they make up everything. What do you call a fish with no eyes? Fsh. I'm reading a book on anti-gravity. It's impossible to put down. Why did the giraffe get a ticket? For parking in a no-parking zone.

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

    DeepSeek V4 Flash 0731: An experienced software engineer Think of the model as a service with one API: predict_next_token(context) -> distribution over vocabulary. During training, you run a gigantic distributed job—shard the corpus, shard the parameters, synchronize gradients—to minimize cross-entropy loss on trillions of tokens.

    Dots3-Note Preview: To an experienced software engineer, a large language model is essentially a massive, differentiable function that maps a sequence of tokens to a probability distribution over the next token.

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

    DeepSeek V4 Flash 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).

    Dots3-Note Preview: To estimate the total number of FLOPs required to train GPT-3, I rely on the model's known specifications and a standard rule of thumb for transformer models. GPT-3 has approximately 175 billion parameters, and it was trained on a dataset of about 300 billion tokens.

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

    DeepSeek V4 Flash 0731: Sally has 1 sister. Her 3 brothers each have 2 sisters: Sally and one other sister. So Sally has 1 sister.

    Dots3-Note Preview: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters, which means there are 2 girls in the family. Since Sally is one of the girls, she has 1 sister. Thus, Sally has 1 sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

Dots3-Note PreviewDots3-Note Preview

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

The Great Gatsby

F. Scott Fitzgerald

Paris

France

Elden Ring

Action, RPG

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Flash 0731 has the edge: bigger context window, major provider backing.

DeepSeek V4 Flash 0731 and Dots3-Note Preview compared across 54 shared prompts
SpecDeepSeek V4 Flash 0731Dots3-Note Preview
Input price$0.14/M tokensFree
Output price$0.28/M tokensFree
Context window1.0M tokens512K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedJul 2026Aug 2026
At 10M a month$1.40$1.40$0$0
1M10M100M1B10M tokens

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

Where to run it25 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • RRelacefp4$0.009 in·$1.28 out·1M·100% up
  • WWafer$0.01 in·$1.00 out·1M·100% up
  • OOpenInferencefp4$0.01 in·$0.27 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·100% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
  • SStreamLakefp8$0.09 in·$0.26 out·1M·100% up
18 more hostsFewer hosts
  • IInceptronfp4$0.10 in·$0.60 out·1M·99.5% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·99.9% up
  • DDigitalOcean$0.12 in·$0.24 out·1M·100% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·100% up
  • VVenice$0.13 in·$0.26 out·1M·100% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·99.5% up
  • Cohere$0.14 in·$0.28 out·1M·99.6% up
  • PParasailfp8$0.14 in·$0.28 out·1M·99.9% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloud$0.18 in·$0.53 out·1M·99.5% up
  • MMancerfp8$0.20 in·$0.60 out·1M·100% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.3% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·99.9% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·100% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·98.6% up
Dots3-Note Preview1 host
HostInOutContextUptime
  • AAtlasCloudfp8$0 in·$0 out·512k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between DeepSeek V4 Flash 0731 and Dots3-Note Preview?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Dots3-Note Preview is developed by Dots Studio. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Dots3-Note Preview's 512K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash 0731 or Dots3-Note Preview?

It depends on your use case. DeepSeek V4 Flash 0731 and Dots3-Note Preview 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 DeepSeek V4 Flash 0731 cost compared to Dots3-Note Preview?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Dots3-Note Preview costs $0/M input tokens. Dots3-Note Preview is $0.14/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 0731 and Dots3-Note Preview on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 and Dots3-Note Preview 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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  • DeepSeek V4 Flash 0731 vs DeepSeek V4.1 FlashSame lab
  • Dots3-Note Preview vs Ox AlphaSame size
  • Dots3-Note Preview vs GPT-6.1 SolSame size
  • DeepSeek V4 Flash 0731 vs Nemotron 3 UltraNew provider
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  • DeepSeek V4 Flash 0731 vs Nemotron 3.5 LightningNew provider
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Model pages

  • DeepSeek V4 Flash 073158 outputs, specs and price
  • Dots3-Note Preview58 outputs, specs and price
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