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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Qwen3 235B A22B 2507
Updated Jul 2026

DeepSeek V4 Flash 0731 vs Qwen3 235B A22B 2507

Qwen3 235B A22B 2507 is cheaper than DeepSeek V4 Flash 0731 at $0.00015/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
Qwen3 235B A22B 2507

Which answer wins?

Written rounds

18 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…

    Qwen3 235B A22B 2507: "AI Revolutionizes Competitive Napping: DeepDream Wins National Snore-a-Thon with Perfect REM Algorithm" — In a stunning turn of events, an artificial intelligence named DeepDream has clinched first place at the 42nd Annual National Snore-a-Thon, outlasting 300 human competitors with its precisely calibrated breathing…

    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 235B A22B 2507: CEO Action Plan: The Next 48 Hours Balancing Ethics, Legal Duty, Patient Safety, and Business Sustainability Hour 0–6: Assess the Situation and Secure Critical Data Actions: Call Emergency Secure Meeting (Virtual) with Chief Medical Officer (CMO), Chief Scientific Officer (CSO), Head of Regulatory Affairs, and Lead…

    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.

    Qwen3 235B A22B 2507: Title: "Consciousness in Code: A Dialogue on AI Rights" Setting: A quiet university office. Dr. Elena Marquez, a professor of AI ethics with decades of research in machine consciousness and digital personhood, sits across from a large screen displaying a serene blue interface.

    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 235B A22B 2507: 1. To the Experienced Software Engineer (Skeptical, Systems-Oriented) You’re right to be skeptical—on the surface, “predicting the next word” sounds like a glorified autocomplete. But think of it less as a single prediction and more as a high-dimensional state machine trained across petabytes of human-generated text.

    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 235B A22B 2507: Sure! Here are 5 original jokes: I asked my dog what's two minus two. He said nothing. (Paw-sitively nothing!) Why did the coffee file a police report? It got mugged. Every single morning. I used to be a baker, but I couldn't make enough dough. So I switched careers and became a plumber. Now I deal with real pipes.

    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 235B A22B 2507: Dish Title: Ember & Petal – A Dialogue Between Earth and Sky Conceptual Narrative: Inspired by the elemental contrast between volcanic resurgence and alpine serenity, Ember & Petal explores the tension and harmony of opposing natural forces through taste, texture, and temperature.

    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 235B A22B 2507: Title: "A Vision Reimagined: Steve Jobs on AI in 2025" Note: This is a fictional simulation. Steve Jobs passed away in 2011. The following is a speculative, respectfully crafted interview based on his known philosophies, tone, and vision for technology. Interviewer (Sarah Chen, Tech Vision Magazine): Mr.

    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 235B A22B 2507: Dish Name: Golden Garbanzo Drizzle A cozy, savory-spiced chickpea stew with a honey-lime finish — simple, satisfying, and ready in minutes. Ingredients (7 common pantry staples): 1 can (15 oz) chickpeas (garbanzo beans), drained and rinsed 1 can (15 oz) diced tomatoes (undrained) 2 tbsp olive oil 1 tsp ground cumin ½…

    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 235B A22B 2507: Comprehensive 3-Month Longevity & Biohacking Optimization Plan For the Advanced Biohacker — Maximize Longevity, Physical & Cognitive Performance INTRODUCTION: Core Principles This 3-month protocol integrates cutting-edge longevity science with personalized biohacking strategies.

    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 235B A22B 2507: The contract presented heavily favors the Client (TechCorp Solutions Inc.) and contains several unbalanced, potentially unenforceable, and exploitable clauses that place the Contractor at significant legal, financial, and professional risk.

    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 235B A22B 2507: If the transistor had been invented in 1920—27 years earlier than its actual 1947 debut—it would have catalyzed a technological revolution far ahead of schedule, profoundly altering the trajectory of the 20th century.

    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 235B A22B 2507: This pitch deck for MindMeld AI is compelling and ambitious, but three claims raise significant red flags in terms of credibility, plausibility, and investor due diligence. Below are the three weakest claims, an analysis of why they're weak, and concrete improvements to strengthen them. 1.

    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 235B A22B 2507: Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves reasoning through several key parameters: model size (number of parameters), the number of training tokens, and the relationship between these quantities and FLOPs.

    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 235B A22B 2507: Setting: A mysterious tavern suspended in a digital void—half stone-walled medieval hall, half creaking pirate ship, with neon cables snaking

    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 235B A22B 2507: Here’s a simple, actionable 1-month plan focused on three foundational pillars of health and longevity: Nutrition, Movement, and Sleep & Stress. Designed for beginners, it emphasizes small, sustainable changes to build lasting habits.

    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 235B A22B 2507: By 2035, artificial intelligence is poised to fundamentally transform the film industry, reshaping nearly every stage of production, distribution, and consumption.

    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 235B A22B 2507: Let's break it down: Sally is a girl. She has 3 brothers. Each of her brothers has 2 sisters. Now, think about the brothers' perspective: Each brother is a sibling to Sally and shares the same siblings. So, when it says each brother has 2 sisters, those are the girls in the family.

    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 235B A22B 2507: The described architecture for a real-time collaborative document editor has several critical failure modes, race conditions, and scaling bottlenecks that compromise consistency, availability, and scalability—especially under load or in edge network conditions.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

Same pick

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 235B A22B 2507Qwen3 235B A22B 2507

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

DeepSeek V4 Flash 0731 and Qwen3 235B A22B 2507 compared across 36 shared prompts
SpecDeepSeek V4 Flash 0731Qwen3 235B A22B 2507
Input price$0.14/M tokens$0.00015/M tokens
Output price$0.28/M tokens$0.00085/M tokens
Context window1.0M tokens—
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2025
At 10M a month$1.40$1.40<$0.01<$0.01
1M10M100M1B10M tokens

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

Where to run it30 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
Qwen3 235B A22B 25076 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.09 in·$0.55 out·262k·89% up
  • PParasailfp8$0.14 in·$0.80 out·131k·99.9% up
  • VVenicefp8$0.15 in·$0.75 out·128k·91.1% up
  • NNebiusfp8$0.20 in·$0.60 out·262k·97.7% up
  • Google Vertex AI$0.22 in·$0.88 out·262k·99.9% up
  • GGMI Cloudfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.09 in·$0.35 out·262k·0% 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 Qwen3 235B A22B 2507?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Qwen3 235B A22B 2507 is developed by Qwen. You can compare their actual outputs across 36 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash 0731 or Qwen3 235B A22B 2507?

It depends on your use case. DeepSeek V4 Flash 0731 and Qwen3 235B A22B 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 36 challenges so you can judge which fits your needs best.

How much does DeepSeek V4 Flash 0731 cost compared to Qwen3 235B A22B 2507?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Qwen3 235B A22B 2507 costs $0.00015/M input tokens. Qwen3 235B A22B 2507 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 Qwen3 235B A22B 2507 on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 and Qwen3 235B A22B 2507 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.

More comparisons

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Same lab, same size, long tail

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Model pages

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  • Qwen3 235B A22B 250736 outputs, specs and price
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