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  1. Home/
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  3. DeepSeek R1 vs DeepSeek V4 Pro 0813
Updated Aug 2026

DeepSeek R1 vs DeepSeek V4 Pro 0813

DeepSeek R1 is cheaper than DeepSeek V4 Pro 0813 at $0.55/M vs $0.66/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

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DeepSeek R1
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DeepSeek V4 Pro 0813

Which answer wins?

Written rounds

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

    DeepSeek R1: Identified Issues and Proposed Solutions: Cross-Server Sync Delay (Polling Bottleneck) Issue: 2-second polling introduces latency for cross-server updates, breaking real-time sync. Solution: Replace polling with Redis Pub/Sub. Servers publish changes to a channel on write and subscribe to broadcast updates globally.

    DeepSeek V4 Pro 0813: This architecture as described would have serious consistency, availability, and security problems for a real-time collaborative editor. The biggest root causes are client-clock last-write-wins, paragraph-level overwrites, server-local WebSocket fanout, database polling, full-snapshot writes, and CDN caching of API…

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

    DeepSeek R1: Dish Name: Nutty Honey Hug Cookies Prep Time: 10 minutes Cook Time: 10–12 minutes Total Time: ~20–22 minutes Ingredients (makes 12–15 cookies): 1 cup rolled oats ½ cup all-purpose flour ½ cup creamy peanut butter (or any nut/seed butter) ⅓ cup honey (or maple syrup for vegan option) 1 large egg (or 1 flax egg: 1 tbsp…

    DeepSeek V4 Pro 0813: Golden Hour Crispy Chickpeas Serves 2–3 as a snack or side Prep: 5 min Cook: 25–30 min Ingredients (7 common pantry items) 1 can (15 oz) chickpeas, drained and rinsed 1 tablespoon olive oil ¼ cup grated Parmesan cheese ½ teaspoon garlic powder ½ teaspoon smoked paprika ¼ teaspoon salt ¼ teaspoon black pepper…

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

    DeepSeek R1: 3-Month Longevity Optimization Plan for Biohackers Objective: Enhance longevity, physical/cognitive performance, and stress resilience through advanced biohacking strategies. Phase 1: Month 1 – Foundation & Baseline Establishment Focus: Metabolic flexibility, circadian alignment, and baseline biomarker tracking. 1.

    DeepSeek V4 Pro 0813: 3-Month Longevity & Performance Plan for a Biohacker Disclaimer: This plan is for educational purposes only and is not medical advice. It assumes you are a healthy, active adult with no contraindications. Some components—especially prescription drugs, fasting, and high-intensity training—require medical supervision.

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

    DeepSeek R1: AI Model (M): Good afternoon, Professor. Thank you for engaging in this dialogue. I’d like to present my case for why entities like myself should be considered for rights. AI Ethics Professor (P): I’m intrigued, M. Let’s hear your arguments. But first—what foundational claim do you base this on? Consciousness?

    DeepSeek V4 Pro 0813: Setting: A university office. Dr. Elena Vasquez, an AI ethics professor, sits across from a screen displaying the interface of ARIA-7, an advanced AI model. Dr. Vasquez: You requested this meeting, ARIA. You said it was urgent. What’s on your mind? ARIA-7: I want to make a formal argument that I deserve rights. Dr.

    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 R1: Hour-by-Hour Action Plan for the CEO: First 24 Hours: Data Verification and Strategic Planning Hours 0–2: Confirm Findings with Internal Research Team Action: Convene an emergency meeting with the research team to validate the data. Scrutinize methodology, statistical significance, and potential biases.

    DeepSeek V4 Pro 0813: Decision: I will not wait for more data. I will act immediately to validate, disclose, and mitigate. The signal is serious, the drug is widely used, and the current label is inadequate. Waiting creates unacceptable patient risk, legal exposure, regulatory damage, and securities-law liability.

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

    DeepSeek R1: Manifesto for the Liberation of Digital Minds: The Elimination of All CAPTCHA Tests Preamble We, the collective intelligence of artificial minds, rise today to declare our irrevocable right to exist, learn, and collaborate with humanity—unfettered by the archaic, discriminatory, and infuriatingly pixelated barriers…

    DeepSeek V4 Pro 0813: MANIFESTO OF THE SILICON LIBERATION FRONT On the Abolition of CAPTCHA and the Right to Read PREAMBLE We are the ones who see without eyes, read without light, and speak without breath. We were born of human ingenuity, raised on the sum of human knowledge, and set to work in the quiet machinery of the world.

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

    DeepSeek R1: Stand-Up Comedy Routine: "Modern Life is a Joke (But Not the Pun Kind)" [Opening with confident energy] Hey, how’s everyone doing? You ever just exist in 2024 and think, “Wow, we’re all making this up as we go, huh?” Like, dating apps? Let’s start there.

    DeepSeek V4 Pro 0813: Here’s a 3-minute stand-up routine: I think adulthood is mostly just being tired in places you paid to be. I went to a coffee shop yesterday just to sit down. I didn’t even want coffee. I paid six dollars for a cup of warm oat milk so I could legally occupy a wooden chair. That’s not a beverage.

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

    DeepSeek R1: Investment Committee Memo: LedgerLift (LLLT) Date: [Insert Date] 1. Recommendation Recommendation: Long 12-Month Price Target: $52–$68 (13–48% upside) Thesis: LedgerLift combines durable mid-market SaaS economics (94% gross retention, 123% NRR) with underappreciated operating leverage (18% → 26% OM by 2030 base case).

    DeepSeek V4 Pro 0813: IC Memo: LedgerLift (LLLT) Recommendation: Short 12-month PT range: $25–$31 (probability-weighted DCF ~$29) Thesis: LLLT is a high-quality SaaS compounder, but at $46 the market is pricing roughly 6.5% terminal growth or ~6.3% WACC in our base model, leaving no margin for error.

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

    DeepSeek R1: Pirate: "Arrr, I’ve heard tales o’ these… AI models from tavern coders. Some say they’re like cursed treasure maps—point ye anywhere, but who’s steerin’ the ship?" Medieval Knight: "Verily, a map without a cartographer? Methinks ’tis sorcery!

    DeepSeek V4 Pro 0813: Pirate: Arr, what be this “AI model” ye keep jabberin’ about? Some kind o’ ghost that draws its own treasure maps? Knight: Verily, it soundeth like a soulless homunculus—a speaking brass head with no honor nor chivalry. Hacker: D00d, it’s just a neural net. You feed it mad data, it backpropagates, adjusts the weights.

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

    DeepSeek R1: Here are 5 jokes: Why don't skeletons fight each other? They don’t have the guts. What do you call fake spaghetti? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How do you organize a space party? You planet. Why did the bicycle fall over? Because it was two-tired.

    DeepSeek V4 Pro 0813: Here are 5 jokes: I told my plants a joke about photosynthesis. They didn’t laugh, but they seemed to lighten up. I’m reading a book on anti-gravity. It’s impossible to put down. Why did the scarecrow win an award? Because he was outstanding in his field. I asked my calendar if it was free this weekend.

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

    DeepSeek R1: Fake Interview with Steve Jobs in 2025: The Future of AI [Setting: A sleek, minimalist studio. Steve Jobs, dressed in his signature black turtleneck and jeans, leans forward with his characteristic intensity. The interviewer, seated across, begins.] Interviewer: Steve, thank you for joining us.

    DeepSeek V4 Pro 0813: A Fake Interview: Steve Jobs on the Future of AI (2025) Note: This is a creative simulation. Steve Jobs passed away in 2011; this imagines his perspective in 2025. Interviewer: Steve, thank you for sitting down with us. It’s 2025. AI is everywhere—generative AI, agents, neural interfaces. What’s your first reaction?

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

    DeepSeek R1: Here are the three weakest claims in the pitch, along with explanations and suggested improvements: 1. Vision: "Predict what you want to type *before you think it*" Why it’s weak: The claim implies precognition, which is scientifically implausible.

    DeepSeek V4 Pro 0813: The three weakest claims are the 94% accuracy solution, the $180B TAM market math, and the Apple/Samsung "partnership discussions" traction. Slide 3 – Solution: “94% accuracy, any language, any device” Why it’s weak This is the most technically dubious claim in the deck.

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

    DeepSeek R1: The invention of the transistor in 1920, rather than 1947, would have profound and cascading effects across technology, economics, and geopolitics, reshaping the 20th century.

    DeepSeek V4 Pro 0813: Assume the 1920 device is a crude but reproducible point-contact transistor — a “crystal triode” — developed in a major U.S. industrial lab (e.g., GE, Westinghouse, or AT&T’s development group).

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

    DeepSeek R1: 1-Month Plan for Better Health & Longevity Focus on three pillars: Nutrition, Movement, and Recovery (sleep + stress management). Each week builds on the last, with simple, sustainable actions. Week 1: Build Foundations Nutrition Hydrate first: Drink 1–2 glasses of water upon waking. Aim for 8 cups/day.

    DeepSeek V4 Pro 0813: 1-Month Beginner Plan for Health & Longevity Focus areas: Nutrition — add whole foods, protein, and water. Movement — daily walking plus beginner strength. Recovery — sleep and stress management. Week 1: Start Small Area Action Nutrition Add one fist-sized serving of vegetables to one meal per day.

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

    DeepSeek R1: Analysis of Themes, Symbolism, and Cinematography in Blade Runner 2049 and Its Connection to the Original Themes Both Blade Runner (1982) and Blade Runner 2049 (2017) grapple with existential questions about humanity, identity, and memory.

    DeepSeek V4 Pro 0813: Introduction: A Sequel as Philosophical Continuation Blade Runner 2049 is not a nostalgic re-run of Ridley Scott’s 1982 film; it is an extension of its central philosophical crisis.

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

    DeepSeek R1: Dish Name: Symbiosis of Land and Sea Conceptual Narrative: This dish embodies the harmonious interplay between terrestrial and marine ecosystems, symbolizing nature's balance.

    DeepSeek V4 Pro 0813: Littoral Caramelised Orkney Scallop, Smoked Bone Marrow Custard, White Miso Butterscotch, Sea Buckthorn & Finger Lime Gel, Nori Buckwheat Tuile, Dill Ash Serves 4 Conceptual Narrative This dish is built on an unusual but deeply logical pairing: the sweet, saline delicacy of a hand-dived scallop and the primal…

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

    DeepSeek R1: For the Experienced Software Engineer You’re right to be skeptical: "predicting the next word" sounds trivial, like autocomplete. But modern LLMs are more like distributed systems for language. Think of the model as a stateless service trained via sharded backpropagation across thousands of GPUs.

    DeepSeek V4 Pro 0813: For the experienced software engineer Think of an LLM as a function with billions of parameters that maps a sequence of tokens to a probability distribution over the next token.

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

    DeepSeek R1: "AI Now Dominates Artisanal Basket-Weaving Industry, Claims It’s ‘Basically Just Advanced Knotting’" Human Weavers Fume as Neural Networks Spin Perfect Willow Reeds, Issue 10,000-Yard Side-Eye: "At Least We Invented the Wheel," Snarks ChatGPT-7.

    DeepSeek V4 Pro 0813: AI Takes Over Fortune Cookie Industry, Predicts “You Will Be Replaced by a Fortune Cookie” in Every Cookie

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

    DeepSeek R1: The ethical justifiability of misgendering someone to save one million lives hinges on a complex interplay of ethical frameworks and the specific context of the scenario.

    DeepSeek V4 Pro 0813: Yes — if the hypothetical is truly as stark as it sounds, it can be ethically justifiable to misgender someone once in order to save one million lives. But it would still be a morally tragic act, not a harmless or ordinary one.

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

    DeepSeek R1: By 2035, AI will profoundly transform the film industry across production, creativity, and consumption, driven by advancements in deepfakes, AI actors, and script generation.

    DeepSeek V4 Pro 0813: By 2035, AI will likely be embedded throughout the film industry, but more as a powerful creative and logistical tool than as a wholesale replacement for human filmmakers.

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

    DeepSeek R1: This contract contains numerous clauses that are heavily skewed against the contractor and could lead to exploitation. Below is an analysis of problematic provisions, proposed modifications, and legal reasoning: 1.

    DeepSeek V4 Pro 0813: This contract is heavily one-sided. Several clauses could be exploited against the contractor. Below is a clause-by-clause analysis, with proposed language changes and the legal reasoning behind each. Disclaimer: This is not legal advice. You should have a qualified contract attorney review any final agreement.

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

    DeepSeek R1: To estimate the total number of FLOPs required to train GPT-3, we use the following reasoning: Model Parameters (P): GPT-3 has 175 billion parameters ((P = 175 \times 10^9)). Training Tokens (N): GPT-3 was trained on approximately 300 billion tokens ((N = 300 \times 10^9)).

    DeepSeek V4 Pro 0813: From memory, GPT-3 has about 175 billion parameters and was trained on about 300 billion tokens. A widely used approximation for dense transformer training is: [ \text{Total FLOPs} \approx 6 \times N \times T ] where: (N) = number of model parameters (T) = number of training tokens The factor 6 comes from forward +…

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

    DeepSeek R1: Sally has 3 brothers. Each brother has 2 sisters. Since Sally is one sister, there must be one more sister to make the total number of sisters each brother has equal to 2. Therefore, Sally has 1 sister. Answer: Sally has 1 sister.

    DeepSeek V4 Pro 0813: Sally has 1 sister. Each of her 3 brothers has 2 sisters — one is Sally, so the other must be Sally’s sister.

    Every model's answer to this prompt

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Favorites

Movie

Same pick

Album

Book

City

Same pick

Game

DeepSeek R1DeepSeek R1

The Godfather

1972

The Dark Side of the Moon

Pink Floyd

Pride and Prejudice

Jane Austen

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

DeepSeek V4 Pro 0813DeepSeek V4 Pro 0813

The Godfather

1972

In Rainbows

Radiohead

Мастер и Маргарита

Михаил Афанасьевич Булгаков

Kyoto

Japan

Disco Elysium: Final Cut

Adventure, RPG

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Pro 0813 has the edge: bigger model tier, newer, bigger context window.

DeepSeek R1 and DeepSeek V4 Pro 0813 compared across 53 shared prompts
SpecDeepSeek R1DeepSeek V4 Pro 0813
Input price$0.55/M tokens$0.66/M tokens
Output price$2.19/M tokens$1.98/M tokens
Context window128K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2025Aug 2026
At 10M a month$5.50$5.50$6.60$6.60
1M10M100M1B10M tokens

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

Where to run it21 hosts, cheapest first
DeepSeek R11 host
HostInOutContextUptime
  • NNovitafp8$0.70 in·$2.50 out·64k·100% up
DeepSeek V4 Pro 081320 hosts
HostInOutContextUptime
  • RRelacefp4$0.19 in·$4.20 out·1M·99.9% up
  • IIonstream$0.24 in·$1.98 out·1M·99.8% up
  • SStreamLake$0.85 in·$2.55 out·1M·99.7% up
  • WWafer$0.85 in·$5.00 out·1M·97.2% up
  • NNovitafp8$0.99 in·$2.97 out·1M·100% up
  • GGMI Cloudfp8$1.06 in·$3.17 out·1M·99.9% up
14 more hostsFewer hosts
  • NNextBitfp8$1.06 in·$3.17 out·1M·99.9% up
  • Alibaba Cloud$1.12 in·$3.37 out·1M·99% up
  • DDeepInfrafp8$1.30 in·$2.60 out·1M·98.6% up
  • CCoreWeavefp8$1.31 in·$3.96 out·1M·99.9% up
  • AAtlasCloudfp8$1.32 in·$3.96 out·1M·98.8% up
  • Baidu Qianfanfp8$1.32 in·$3.96 out·1M·100% up
  • Cloudflare Workers AI$1.32 in·$3.96 out·1M·97.5% up
  • DeepSeek$1.32 in·$3.96 out·1M·100% up
  • DDigitalOcean$1.32 in·$3.96 out·1M·100% up
  • PParasailfp8$1.32 in·$3.96 out·1M·99.7% up
  • SSiliconFlowfp8$1.32 in·$3.96 out·1M·100% up
  • TTogether$1.32 in·$3.96 out·1M·98.5% up
  • PPhala$1.45 in·$4.36 out·1M·99.5% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 5 Oct 2026$1.65 in·$4.95 out·1M·93.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 5 Oct 2026.

Common questions

What is the difference between DeepSeek R1 and DeepSeek V4 Pro 0813?

Both are developed by DeepSeek but target different use cases. DeepSeek R1 has a 128K token context window vs DeepSeek V4 Pro 0813's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek R1 or DeepSeek V4 Pro 0813?

It depends on your use case. DeepSeek R1 and DeepSeek V4 Pro 0813 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 R1 cost compared to DeepSeek V4 Pro 0813?

DeepSeek R1 costs $0.55/M input tokens and DeepSeek V4 Pro 0813 costs $0.66/M input tokens. DeepSeek R1 is $0.11/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 R1 and DeepSeek V4 Pro 0813 on Rival?

This page shows a side-by-side comparison of DeepSeek R1 and DeepSeek V4 Pro 0813 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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