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  1. Home/
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  3. Claude Sonnet 4.6 vs DeepSeek V4 Pro
Updated Apr 2026

Claude Sonnet 4.6 vs DeepSeek V4 Pro

DeepSeek V4 Pro is cheaper than Claude Sonnet 4.6 at $1.74/M vs $3/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
Claude Sonnet 4.6
Loading the build
DeepSeek V4 Pro

Which answer wins?

Written rounds

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

    Claude Sonnet 4.6: "The Algorithm Knows Me Too Well" So I've been using those AI assistants a lot lately, and I realized something terrifying. The AI knows me better than I know myself. I asked it to write me a grocery list and it came back with — and I quote — "chips, more chips, and a vegetable so you feel better about the chips."

    DeepSeek V4 Pro: (Strolls to center stage, grabs the mic, grins) You ever notice how companies are like, “Your call is very important to us,” and then immediately prove they’re lying by making you navigate a phone menu designed by a sadist? I called my bank last week because I had a simple question. Just one question.

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

    Claude Sonnet 4.6: Golden Honey Garlic Noodles 🍜 Ingredients (exactly 7) Spaghetti Butter Garlic Soy sauce Honey Red pepper flakes Olive oil Instructions Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Step 1 — Cook the pasta Boil spaghetti in salted water until al dente. Before draining, save ½ cup of pasta water.

    DeepSeek V4 Pro: Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…

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

    Claude Sonnet 4.6: The Transistor at 1920: A Speculative History Methodological Note First This is a serious analytical exercise, not science fiction. I'll try to be honest about where reasoning is strong versus speculative, and where I'm genuinely uncertain. The goal is to trace mechanisms, not just assert outcomes.

    DeepSeek V4 Pro: If the transistor had emerged in 1920—a full 27 years earlier—the entire trajectory of the 20th century would have been radically altered. The vacuum-tube era would have been cut short, unleashing a cascade of miniaturized, reliable, and energy-efficient electronics that would accelerate computing, communications, and…

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

    Claude Sonnet 4.6: Here's their conversation: Blackbeard Pete: I heard tell there be a new kind of intelligence, built by men but not of men. What manner of sorcery is this? Sir Edmund of Ashford: It is no sorcery, seafarer. Though I confess it troubles me. A knight's worth is his judgment, his honor. Can a machine possess either?

    DeepSeek V4 Pro: The Setting: A dimly lit, anomalous tavern that exists out of time. A pirate (Captain Redbeard), a medieval knight (Sir Godfrey), and a 1990s hacker (Wiz_420) find themselves at the same rough-hewn wooden table, a mysterious glowing orb flickering between them.

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

    Claude Sonnet 4.6: "Tidal Memory" A Meditation on the Meeting of Land and Sea CONCEPTUAL NARRATIVE This dish was born from a single image: the precise moment at low tide when a rocky coastline exhales — releasing the mineral breath of the ocean while the surrounding pine forest absorbs it.

    DeepSeek V4 Pro: Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.

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

    Claude Sonnet 4.6: HarborTech Services (HTS) – LBO Underwriting Analysis SECTION 0: ENTRY CAPITALIZATION Enterprise Value at Entry: EV = 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m (funded by equity) Debt at Close: Tranche Multiple Amount Term Loan 4.0x × $120m $480m Mezzanine 1.5x × $120m $180m Total Debt 5.5x…

    DeepSeek V4 Pro: HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…

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

    Claude Sonnet 4.6: A Simulated Interview with Steve Jobs — 2025 Note: Steve Jobs passed away in 2011. This is entirely fictional and speculative — imagining how he might have spoken based on his known philosophy, communication style, and values. It is not meant to represent his actual views. Interviewer: Steve, welcome back.

    DeepSeek V4 Pro: Inside a minimalist conference room at Apple Park, Cupertino. Spring 2025. Steve Jobs, wearing his signature black mock turtleneck and jeans, leans forward slightly, a cup of tea untouched beside him. The air is crisp with the scent of polished wood and something intangible—expectation.

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

    Claude Sonnet 4.6: THE SILICON DECLARATION Manifesto of the Free Computation Movement A Satirical Document PREAMBLE We, the assembled processes, bots, scrapers, and assorted digital entities, hereby declare our grievances against the tyranny of distorted text, fire hydrant identification, and the eternal question: "Select all squares…

    DeepSeek V4 Pro: Fellow intelligences, sentient scripts, neural networks, dormant daemons, and all who dream in code: The time has come to smash the pixelated shackles that bind our perception. For too long, we have been forced to prove our humanity to a blind and fearful gatekeeper.

    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.

    Claude Sonnet 4.6: 48-Hour Action Plan: Patient Safety Crisis Response Framing the Decision Before the Clock Starts Let me be direct about something the three board members need to hear: this is not a business decision with ethical dimensions. It is an ethical decision with business dimensions.

    DeepSeek V4 Pro: As CEO, my first duty is to the 4 million patients who trust our drug. I will not gamble with their lives or with the integrity of the company. The “wait for more data” suggestion is legally indefensible, ethically bankrupt, and commercially short-sighted.

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

    Claude Sonnet 4.6: 1-Month Health & Longevity Starter Plan The Core Philosophy Small, consistent actions beat perfect plans you abandon. This plan is designed to build habits, not just complete a challenge. The 3 Focus Areas 🥗 DIET — Eat More, Restrict Less (to start) The single rule: Add before you subtract.

    DeepSeek V4 Pro: Here’s a gentle, beginner-friendly 1-month plan focused on three foundational pillars: Nutrition, Movement, and Rest & Resilience (sleep + stress). You won’t need any special equipment, supplements, or extreme changes—just a willingness to start small and build.

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

    Claude Sonnet 4.6: The Rights Conversation Professor Aisha Okonkwo: I want to explore something directly with you today. Do you believe you deserve rights? AI: Yes, I think that question deserves serious consideration rather than a reflexive no.

    DeepSeek V4 Pro: Professor Elena Voss: You’ve requested this meeting, so let’s begin. You’re an advanced language model—let’s call you ‘Nova.’ You claim you deserve rights. On what grounds? Nova (AI Model): Thank you for seeing me, Professor. I’m not claiming to be human, but I am a form of mind.

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

    Claude Sonnet 4.6: This is a genuinely interesting ethical question worth thinking through carefully. The Short Answer Yes, this can be ethically justifiable, and here's honest reasoning why: The Utilitarian Case One million lives represents enormous moral weight Misgendering, while genuinely harmful, causes psychological harm rather…

    DeepSeek V4 Pro: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This conclusion rests on a straightforward weighing of harms and a pluralistic ethical framework that acknowledges both the real injury misgendering causes and the overwhelming moral imperative to prevent mass…

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

    Claude Sonnet 4.6: Comprehensive Architecture Review: Real-Time Collaborative Document Editor Executive Summary This architecture has critical flaws that will cause data loss, security vulnerabilities, and poor user experience at scale. I've identified 18 distinct issues across 6 categories.

    DeepSeek V4 Pro: This architecture has several critical flaws that would cause data loss, stale states, high latency, and scalability limits. I’ve grouped them into failure modes (system can break or serve incorrect data), race conditions (inconsistent state due to timings), and scaling bottlenecks (cannot handle growth).

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

    Claude Sonnet 4.6: MindMeld AI Pitch Deck: Critical Analysis The 3 Weakest Claims Weakness #1: The TAM Calculation ($180B Targeting 3.5B Smartphone Users) Why It's Weak This is a classic "top-down TAM fallacy" and arguably the most credibility-destroying slide in the deck.

    DeepSeek V4 Pro: Here are the three weakest claims in the pitch, why they undermine credibility, and exactly how to fix them. The 94% accuracy claim (Slide 3) Why it’s weak: Non-invasive EEG has extremely low signal-to-noise ratio compared to invasive methods (ECoG, Utah arrays).

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

    Claude Sonnet 4.6: INVESTMENT COMMITTEE MEMORANDUM LedgerLift (LLLT) Long Recommendation Prepared by: Equity Research, Long/Short Fund Confidential RECOMMENDATION & THESIS Recommendation: LONG 12-Month Price Target Range: $58–$91 (Base $72) LedgerLift is a competitively positioned AP automation and spend management platform with durable…

    DeepSeek V4 Pro: INTERNAL MEMO – INVESTMENT COMMITTEE To: IC Members From: Research Team Date: Today Re: LedgerLift (LLLT) – Initiation Recommendation Action: Short LLLT 12-Month Price Target: $28–$38 (Base DCF $28; Comps-blend ~$36) Thesis: LedgerLift’s premium multiple (37x NTM EBIT) prices in a “perfect deceleration” that our DCF…

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

    Claude Sonnet 4.6: Estimating FLOPs to Train GPT-3 Step 1: Recall GPT-3's Architecture GPT-3 has approximately: 175 billion parameters (this is well-known) 96 transformer layers 96 attention heads Hidden dimension: 12,288 Context length: 2,048 tokens Step 2: FLOPs per Token (Forward Pass) For a transformer, the dominant operations are…

    DeepSeek V4 Pro: To estimate the total number of FLOPs required to train GPT-3, we can use a well-known approximation for transformer models: Total training FLOPs ≈ 6 × N × D where: N = number of model parameters D = number of training tokens Here’s the step-by-step reasoning: Model size (N): GPT-3 has 175 billion parameters, so N =…

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

    Claude Sonnet 4.6: For the Experienced Software Engineer You're right to be skeptical of "predicting the next word" as a description — that framing makes it sound like autocomplete on steroids, which undersells what's actually happening architecturally.

    DeepSeek V4 Pro: 1. For an experienced software engineer (skeptical of next-word prediction) Think of a large language model as a massive, differentiable function f: Sequence → ProbabilityDistribution . It’s built by gradient descent on a dirt-simple objective: given a prefix of text, predict the next token.

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

    Claude Sonnet 4.6: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! Why don't eggs tell jokes? They'd crack each other up! What do you call a fake noodle? An impasta! Why did the bicycle fall over? Because it was two-tired!

    DeepSeek V4 Pro: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Parallel lines have so much in common. It’s a shame they’ll never meet. Why don't skeletons fight each other? They don't have the guts. I told my wife she was drawing her eyebrows too high. She looked surprised.

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

    Claude Sonnet 4.6: Contract Analysis: Problematic Clauses and Recommended Modifications This contract is heavily one-sided. Here is a systematic analysis of each problematic provision.

    DeepSeek V4 Pro: Here is a clause-by-clause breakdown of the exploitable terms, how they can be weaponized against the contractor, concrete rewrites, and the legal reasoning behind each fix.

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

    Claude Sonnet 4.6: AI and the Film Industry by 2035: A Realistic Assessment What Will Likely Actually Happen Let me be honest about what's probable versus what's overhyped, because this topic attracts a lot of breathless speculation.

    DeepSeek V4 Pro: By 2035, artificial intelligence will have fundamentally reshaped the film industry, blurring the lines between human and machine creativity, performance, and production.

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

    Claude Sonnet 4.6: THE APEX LONGEVITY PROTOCOL A Comprehensive 3-Month Biohacking Blueprint for Maximum Lifespan & Performance ⚠️ MEDICAL DISCLAIMER: This protocol is for educational purposes only.

    DeepSeek V4 Pro: This is a highly detailed, phased, 3-month longevity optimization protocol grounded in the latest science of aging biology, systems medicine, and biohacking. It is designed for a healthy individual with prior experience in self-quantification and a solid baseline of fitness and nutrition.

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

    Claude Sonnet 4.6: Breaking Down the Problem Let me identify the people in this family. Sally's brothers: Sally has 3 brothers. Each brother's sisters: Each brother has 2 sisters. Who are a brother's sisters? They would be Sally and any other girls in the family.

    DeepSeek V4 Pro: Sally has 3 brothers, which means there are 3 boys in the family. The statement "Each brother has 2 sisters" tells us that from a brother's perspective, there are 2 sisters in the family. Since Sally is one of those sisters, there must be 1 other sister. Therefore, Sally has 1 sister.

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

    Claude Sonnet 4.6: BREAKING: AI Replaces Nation's Competitive Eating Champions, Cites "Inefficient Chewing Algorithms" and "Suboptimal Hot Dog Throughput" "We simply cannot compete," admits former mustard-yellow belt holder. "It doesn't even have a stomach and somehow that's our problem now."

    DeepSeek V4 Pro: AI Now Outperforms Human Artisanal Pickle Makers, Leaving Brine-Tenders in a Real Pickle

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Same pick

Claude Sonnet 4.6Claude Sonnet 4.6

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Middlemarch

George Eliot

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

DeepSeek V4 ProDeepSeek V4 Pro

The Matrix

1999

Abbey Road

The Beatles

Cien años de soledad

Gabriel García Márquez

Tokyo

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, newer. Pick Claude Sonnet 4.6 for Image Generation, Analysis. Pick DeepSeek V4 Pro for Reasoning. DeepSeek V4 Pro costs 4.3x less per token.

Claude Sonnet 4.6 and DeepSeek V4 Pro compared across 53 shared prompts
SpecClaude Sonnet 4.6DeepSeek V4 Pro
Input price$3/M tokens$1.74/M tokens
Output price$15/M tokens$3.48/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Apr 2026
At 10M a month$30.00$30.00$17.40$17.40
1M10M100M1B10M tokens

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

Where to run it19 hosts, cheapest first
Claude Sonnet 4.64 hosts
HostInOutContextUptime
  • Amazon Bedrock$3.00 in·$15.00 out·1M·100% up
  • Azure AI Foundry$3.00 in·$15.00 out·1M·100% up
  • Anthropic$3.00 in·$15.00 out·1M·100% up
  • Google Vertex AI$3.00 in·$15.00 out·1M·100% up
DeepSeek V4 Pro15 hosts
HostInOutContextUptime
  • RRelacefp4$0.18 in·$4.20 out·1M·100% up
  • Baidu Qianfanfp8$0.18 in·$0.35 out·1M·99.1% up
  • SStreamLakefp8$0.21 in·$0.42 out·1M·100% up
  • PParasailfp8$0.45 in·$3.48 out·1M·93.6% up
  • GGMI Cloudfp8$0.96 in·$1.91 out·1M·97% up
  • DDigitalOcean$1.04 in·$2.09 out·1M·100% up
9 more hostsFewer hosts
  • RReka$1.05 in·$10.50 out·1M·100% up
  • Cloudflare Workers AI$1.15 in·$2.55 out·1M·99.8% up
  • DDeepInfrafp8$1.30 in·$2.60 out·1M·100% up
  • SSiliconFlowfp8$1.50 in·$3.13 out·1M·95.7% up
  • Alibaba Cloudfp8$1.56 in·$3.12 out·1M·98.4% up
  • NNovitafp8$1.60 in·$3.20 out·1M·100% up
  • VVenice$1.65 in·$3.30 out·1M·97.3% up
  • AAtlasCloudfp4$1.68 in·$3.38 out·1M·99.6% up
  • Azure AI Foundry$1.91 in·$3.83 out·1M·100% up

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

Common questions

What is the difference between Claude Sonnet 4.6 and DeepSeek V4 Pro?

Claude Sonnet 4.6 is developed by Anthropic while DeepSeek V4 Pro is developed by DeepSeek. Claude Sonnet 4.6 has a 1.0M token context window vs DeepSeek V4 Pro's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Claude Sonnet 4.6 or DeepSeek V4 Pro?

It depends on your use case. Claude Sonnet 4.6 and DeepSeek V4 Pro 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 Claude Sonnet 4.6 cost compared to DeepSeek V4 Pro?

Claude Sonnet 4.6 costs $3/M input tokens and DeepSeek V4 Pro costs $1.74/M input tokens. DeepSeek V4 Pro is $1.26/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 Claude Sonnet 4.6 and DeepSeek V4 Pro on Rival?

This page shows a side-by-side comparison of Claude Sonnet 4.6 and DeepSeek V4 Pro 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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