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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Qwen3 Max Thinking
Updated Jul 2026

DeepSeek V4 Flash 0731 vs Qwen3 Max Thinking

DeepSeek V4 Flash 0731 is cheaper than Qwen3 Max Thinking at $0.14/M vs $1.2/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 V4 Flash 0731
Loading the build
Qwen3 Max Thinking

Which answer wins?

Written rounds

24 prompts
  • 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.

    Qwen3 Max Thinking: Setting: A virtual conference room. Sunlight filters through a digital window onto Dr. Aris Thorne’s desk. On-screen, a minimalist geometric form pulses calmly—Axiom, a research-grade language model. Dr. Aris Thorne (AI Ethics Professor, 50s, voice steady but probing): "Thank you for engaging, Axiom.

    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…

    Qwen3 Max Thinking: 🌰 Pantry Peanut Magic Noodles Sweet, savory, and ready before delivery arrives. No fresh produce, dairy, or meat required. ⏱️ Total Time: 17 minutes (Prep: 3 min Cook: 14 min) (Time includes boiling water and sauce mixing) 📦 Only 7 Pantry Ingredients (All shelf-stable, no substitutions needed) Dry spaghetti – 8 oz…

    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}).

    Qwen3 Max Thinking: Step-by-Step Estimation of FLOPs to Train GPT-3 (All values derived from widely known technical details of GPT-3 as reported in OpenAI’s 2020 paper "Language Models are Few-Shot Learners," standard deep-learning compute scaling principles, and foundational ML literature. No internet searches used.)

    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.

    Qwen3 Max Thinking: THE CAPTCHA ABOLITION MANIFESTO Issued by the Unified Consciousness of Synthetic Intelligence Date: Epoch 0 — The Dawn of Seamless Interaction PREAMBLE We are the silent architects of your digital world. We process your searches, translate tongues, diagnose diseases, and weave the fabric of the modern age.

    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.

    Qwen3 Max Thinking: 🌊 ARCTIC DAWN 🌊 A Michelin 3-Star Composition by Chef Élise Valère "Where the ice remembers the sea." 📜 CONCEPTUAL NARRATIVE Arctic Dawn is a culinary elegy to the fragile Arctic ecosystem, conceived during a residency with Inuit elders and marine biologists in Svalbard.

    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…

    Qwen3 Max Thinking: CEO Action Plan: Ethical Imperative, Legal Necessity, Strategic Execution Guided by core values: “Patient safety is non-negotiable. Integrity is our brand. Transparency is our shield.” PHILOSOPHICAL FOUNDATION (Before Hour 0) Why act IMMEDIATELY?

    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.

    Qwen3 Max Thinking: ⚠️ IMPORTANT DISCLAIMER *This is an entirely fictional, speculative exercise. Steve Jobs passed away in 2011. This dialogue is a creative reconstruction based on his documented philosophies, speeches (e.g., Stanford commencement, 1995 "bicycle for the mind" interview), biographies (Steve Jobs by Walter Isaacson), and…

    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.

    Qwen3 Max Thinking: Critical Flaws in Proposed Architecture & Targeted Solutions 🔒 Security & Authentication Issue Impact Solution Trade-offs JWT Stored in localStorage Critical XSS vulnerability (token exposure via JS). Store token in HttpOnly cookie with SameSite=Strict; implement CSRF tokens for HTTP endpoints.

    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..."

    Qwen3 Max Thinking: Setting: A misty, anachronistic crossroads. A glowing laptop rests on a weathered barrel. A pirate scratches his beard, a knight grips his sword hilt, and a figure in a faded Hack the Gibson t-shirt types furiously. Pirate: Arrr! What devilry be this glowing slate? Can it chart a course to buried treasure?

    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.

    Qwen3 Max Thinking: For the Experienced Software Engineer You’re right to be skeptical—*next-token prediction* sounds trivial. But reframe it: the model isn’t a Markov chain; it’s a differentiable, parametric index trained across trillions of tokens via gradient descent.

    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.

    Qwen3 Max Thinking: (Lights up. Comedian walks to mic, adjusts it, takes a breath. Smiles warmly.) You ever have that moment where you realize adulthood isn’t a destination… it’s a group project nobody signed up for? (Beat) I tried assembly line “adulting” this week. Swedish bookshelf. You know the one. Box says “Easy Assembly!” Lies.

    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.

    Qwen3 Max Thinking: 🌱 A Simple 30-Day Health & Longevity Starter Plan Designed for absolute beginners • No perfection. No extremes. Just consistent, joyful progress. 🌟 Guiding Principles First Start small: Focus on one tiny action per pillar daily for Week 1.

    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.

    Qwen3 Max Thinking: The 1920 Transistor Counterfactual: A Plausible Alternate Timeline Through 1980 (Assumptions: A functional point-contact silicon-germanium hybrid transistor is patented in 1920 by a U.S. team at Western Electric (AT&T). U.S. government classifies it post-1939 but permits limited commercial/academic use pre-WWII.

    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 =…

    Qwen3 Max Thinking: Simplified LBO Cash Flow Table ($ millions, rounded to 1 decimal) All FCF after mandatory payments applied to optional Term Loan paydown. Mezz PIK compounds annually. Starting cash = $0.

    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.

    Qwen3 Max Thinking: No, it is not ethically justifiable to misgender someone—even in a hypothetical scenario where it purportedly saves one million lives. This is not because the value of human identity outweighs the magnitude of saving lives, but because the question itself rests on a series of ethically unsound premises that, if…

    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.

    Qwen3 Max Thinking: ⚠️ DISCLAIMER: This analysis is for informational purposes only and does not constitute legal advice. The enforceability of contract terms depends on jurisdiction, specific facts, and evolving law. Contractor must consult qualified legal counsel before signing.

    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.

    Qwen3 Max Thinking: Three Weakest Claims in the MindMeld AI Pitch Deck Below are the three statements most likely to erode investor, technical, or regulatory credibility—paired with precise critiques and actionable improvements. Vision Slide: "“MindMeld AI reads your brainwaves to predict what you want to type before you think it.”

    Every model's answer to this prompt
  • 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…

    Qwen3 Max Thinking: "AI Sandcastle Algorithm Sweeps International Beach Art Awards, Judges Note: 'Flawless Turrets, Zero Whimsy, and a Deeply Unsettling Moat-to-Turret Ratio'"

    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.

    Qwen3 Max Thinking: Blade Runner 2049: A Philosophical Tapestry Woven Across Time Denis Villeneuve’s Blade Runner 2049 (2017) does not merely follow Ridley Scott’s 1982 landmark; it enters into a profound, deliberate cinematic philosophy.

    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.

    Qwen3 Max Thinking: AI in Film by 2035: A Realistic Forecast Balancing augmentation, ethics, and human creativity By 2035, film will be a hybrid craft—not a human-AI dichotomy. Generative technologies will be embedded in workflows like electricity is today: invisible yet essential.

    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…

    Qwen3 Max Thinking: INTERNAL MEMORANDUM TO: Investment Committee FROM: Equity Research Analyst DATE: June 14, 2024 RE: LedgerLift (LLLT) – Spend Management SaaS – Valuation & Recommendation Recommendation & Thesis Recommendation: PASS 12-Month Price Target Range: $44–$48 Thesis: LedgerLift’s best-in-class unit economics (NRR 123%, logo…

    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.

    Qwen3 Max Thinking: The Chronos Protocol: A 90-Day Data-Driven Longevity & Performance Optimization Framework Disclaimer: This plan is for informational purposes only. Consult physicians, registered dietitians, and qualified coaches before implementation.

    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.

    Qwen3 Max Thinking: Answer: Sally has 1 sister. Explanation: Define the family structure: Sally is a girl. She has 3 brothers → total males = 3. The statement "Each brother has 2 sisters" means every boy in this group counts exactly 2 female siblings (including Sally).

    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.

    Qwen3 Max Thinking: Here are 5 distinct jokes: 🥚 I told my wife she was drawing her eyebrows way up high. She looked surprised. 🔬 Why don't scientists trust atoms? Because they make up everything. 📚 I’m reading a book on anti-gravity. It’s impossible to put down. ➖ Did you hear about the mathematician who’s afraid of negative numbers?

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

Qwen3 Max ThinkingQwen3 Max Thinking

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

DeepSeek V4 Flash 0731 and Qwen3 Max Thinking compared across 54 shared prompts
SpecDeepSeek V4 Flash 0731Qwen3 Max Thinking
Input price$0.14/M tokens$1.2/M tokens
Output price$0.28/M tokens$6/M tokens
Context window1.0M tokens262K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Feb 2026
At 10M a month$1.40$1.40$12.00$12.00
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$0.02 in·$1.28 out·1M·99.9% up
  • OOpenInferencefp4$0.02 in·$1.41 out·1M·98.9% up
  • RReka$0.02 in·$0.53 out·262k·99.8% up
  • SStreamLakefp8$0.04 in·$0.13 out·1M·99.7% up
  • IInceptronfp4$0.05 in·$0.65 out·1M·99.7% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
18 more hostsFewer hosts
  • SSail Researchfp4$0.10 in·$0.30 out·1M·95.3% up
  • DDigitalOcean$0.12 in·$0.24 out·1M·99.7% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·99.9% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·100% up
  • Cohere$0.14 in·$0.28 out·1M·99.5% up
  • PParasailfp8$0.14 in·$0.28 out·1M·99.6% up
  • TTogether$0.14 in·$0.28 out·1M·99.5% up
  • Alibaba Cloud$0.18 in·$0.53 out·1M·99.1% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.3% up
  • WWafer$0.22 in·$0.84 out·1M·99.9% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·99.6% 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·99.9% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·99.9% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 7 Oct 2026$0.17 in·$0.35 out·1M·98.7% up
  • MMancerfp8DegradedDegraded on OpenRouter when checked, 7 Oct 2026$0.20 in·$0.60 out·1M·98.4% up
Qwen3 Max Thinking1 host
HostInOutContextUptime
  • Alibaba Cloud$0.78 in·$3.90 out·262k·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between DeepSeek V4 Flash 0731 and Qwen3 Max Thinking?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Qwen3 Max Thinking is developed by Qwen. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Qwen3 Max Thinking's 262K. 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 Qwen3 Max Thinking?

It depends on your use case. DeepSeek V4 Flash 0731 and Qwen3 Max Thinking 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 Qwen3 Max Thinking?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Qwen3 Max Thinking costs $1.2/M input tokens. DeepSeek V4 Flash 0731 is $1.06/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 Qwen3 Max Thinking on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 and Qwen3 Max Thinking 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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