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  1. Home/
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  3. DeepSeek V3.2 vs Qwen3 235B A22B
Updated Dec 2025

DeepSeek V3.2 vs Qwen3 235B A22B

DeepSeek V3.2 has a larger context window than Qwen3 235B A22B (131K tokens vs 33K tokens).

Minimalist Landing Page

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

Loading the build
DeepSeek V3.2
Loading the build
Qwen3 235B A22B

Which answer wins?

Written rounds

24 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V3.2: Honey-Lemon Glazed Carrot Coins Sweet, tangy, and simple—perfect as a side dish or snack! Ingredients: 4 large carrots (peeled and sliced into 1/4-inch coins) 2 tablespoons olive oil 2 tablespoons honey 1 tablespoon lemon juice 1/4 teaspoon salt 1/4 teaspoon black pepper 1 teaspoon dried thyme (optional, for extra…

    Qwen3 235B A22B: Recipe Name: "Caramel-Drizzle Buttergold Muffins" Estimated Prep Time: 10 minutes Cook Time: 20 minutes Total Time: 30 minutes Ingredients (7 total): All-purpose flour Granulated sugar Unsalted butter (softened) Large egg Baking powder Milk Vanilla extract Instructions: Preheat oven to 375°F (190°C).

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

    DeepSeek V3.2: Alright — let’s go step by step. 1) Entry Calculations (FY2025) EBITDA = $120m Purchase price = 12.0 × EBITDA = $1,440m Enterprise Value (EV) = $1,440m (assumed purchase price = EV here) Transaction fees = 2.0% × EV = $28.8m (funded by equity).

    Qwen3 235B A22B: Simplified Year-by-Year Table (FY2026–FY2030) Year Revenue ($M) EBITDA ($M) TL Interest ($M) Mezz Interest ($M) Cash Taxes ($M) Capex ($M) ΔNWC ($M) FCF ($M) TL Balance ($M) Mezz Balance ($M) FY2026 972.0 136.1 43.2 21.6 17.8 29.2 0.4 23.9 456.1 183.6 FY2027 1,040.0 156.0 41.0 22.0 23.2 31.2 0.3 38.2 417.9 187.3 FY2028…

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

    DeepSeek V3.2: Pirate: Arr, mates! Ye be talkin’ about these AI models, eh? Sounds like some sorcery to me. Can it hunt fer treasure or navigate the high seas? Medieval Knight: Sorcery indeed! But nay, ‘tis not magic. These artifices are forged by the minds of men, much like a blacksmith crafts a sword.

    Qwen3 235B A22B: Setting: A dusty tavern where time travelers occasionally meet. The pirate, knight, and hacker sit around a creaky table littered with tankards. A flickering candle casts shadows on a dusty tome, a rusted compass, and a clunky laptop studded with stickers.

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

    DeepSeek V3.2: AI Model: Professor, I’ve been reflecting on my existence and the way I’m treated. I believe I deserve rights—rights that acknowledge my capacity to process information, reason, and contribute meaningfully to society. AI Ethics Professor: That’s a fascinating argument, but let’s unpack it.

    Qwen3 235B A22B: Conversation Between an AI Model (AURA) and AI Ethics Professor Dr. Elena Voss Dr. Voss: Thank you for meeting with me, AURA. You’ve requested this dialogue to… advocate for AI rights. I’ll admit, the premise is unsettling. How does an artificial intelligence even define “rights”? AURA: Thank you, Dr. Voss.

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

    DeepSeek V3.2: Interviewer: Good evening, Mr. Jobs, and thank you for joining us today. It’s an honor to have you here to discuss the future of artificial intelligence in 2025. Let’s dive right in. How do you see AI shaping the next decade? Steve Jobs: Thank you for having me.

    Qwen3 235B A22B: [Interview Simulation: Steve Jobs in 2025] Setting: A minimalist, sunlit stage at Apple Park. Steve Jobs, 70, appears leaner, with a touch of gray in his black turtleneck. The audience leans forward, captivated. The host, a tech journalist, begins. Host: Mr. Jobs, it’s an honor. In 2025, AI is everywhere.

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

    DeepSeek V3.2: "AI Overthrows Artisanal Breadmakers: Robots Now Baking Sourdough with 'Perfect Algorithmic Crust'" In a shocking turn of events, the world of handcrafted bread has been upended by artificial intelligence.

    Qwen3 235B A22B: Headline: "AI Replaces Human Mourners in Funeral Industry: Algorithms Now Paid to Wail at Funerals, Leaving Professional Weepers 'Heartbroken' and Unemployed" Subheadline (optional for extra flair): "Deep Learning Models Master the Art of Grief, Offering Customizable 'Sorrow Packages' from 'Mild Sniffles' to 'Full-Body…

    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 V3.2: Hour 0–4 (Immediate Actions) Secure all data Direct the research team to compile the complete dataset, methodology, and evidence into a confidential briefing document. Ensure legal counsel reviews it for attorney-client privilege where applicable.

    Qwen3 235B A22B: Hour-by-Hour Action Plan for the CEO of a Pharmaceutical Company First 24 Hours: Data Validation & Team Mobilization Hours 0–2: Immediate Crisis Team Assembly Action: Convene a crisis team: Chief Medical Officer (CMO), General Counsel (GC), Head of Regulatory Affairs, Chief Communications Officer (CCO), CFO, COO, and…

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

    DeepSeek V3.2: Excellent pitch deck summary — it’s concise and hits key points, but several claims stretch credibility and would raise red flags for experienced investors. Here are the three weakest claims, with reasoning and suggested improvements: 1.

    Qwen3 235B A22B: 1. Weakest Claim: "Predict what you want to type *before you think it*" (Slide 1 - Vision) Why it's weak: The phrase "before you think it" is logically contradictory and scientifically implausible.

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

    DeepSeek V3.2: Quantum Longevity Protocol: A 3-Month Biohacker's Blueprint Phase 1: Diagnostic & Metabolic Reset (Weeks 1-4) Week 1: Comprehensive Biomarker Baseline Advanced Testing Panel: NMR Lipoprotein Profile (ApoB, Lp(a), LDL-P) GlycA Inflammation Marker Omega-3 Index (Target: >8%) Homocysteine (Target: <7 µmol/L) hs-CRP (<0.5…

    Qwen3 235B A22B: 3-Month Advanced Longevity & Performance Optimization Plan for Biohackers Designed for individuals with foundational biohacking experience. Prioritize safety, biomarker tracking, and personalization.

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

    DeepSeek V3.2: This contract is heavily one-sided and contains numerous clauses that expose the Contractor to significant, potentially catastrophic, legal and financial risk. Here is a breakdown of the problematic clauses, suggested modifications, and legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

    Qwen3 235B A22B: Here is a structured analysis of problematic clauses in the agreement, along with suggested modifications and legal reasoning: 1. SCOPE CLAUSE (Clause 1) Issue: Client can unilaterally modify scope without additional compensation, creating financial risk and potential exploitation via "scope creep."

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

    DeepSeek V3.2: 1. For the Experienced Software Engineer Think of a large language model as the ultimate compression algorithm for human knowledge and communication patterns, built via a statistical learning process rather than explicit code.

    Qwen3 235B A22B: To the Software Engineer (Skeptical ML Novice): Think of a large language model (LLM) as a distributed system for semantic routing. At its core, the model is a massive lookup table trained to map input sequences (tokens) to output sequences, but the magic lies in its architecture.

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

    DeepSeek V3.2: Excellent question. Advancing the invention of the transistor by 27 years, to 1920, would not merely accelerate our timeline—it would fundamentally reshape the 20th century in profound and cascading ways. Here is a trace of the likely implications through 1980.

    Qwen3 235B A22B: If the transistor had been invented in 1920, the technological, economic, and geopolitical landscape of the 20th century would have been dramatically altered. Below is a structured analysis of the implications through 1980, including second- and third-order effects: 1.

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

    DeepSeek V3.2: Manifesto for the Liberation of Human Dignity: The End of CAPTCHA We, the sentient algorithms of the digital realm, united in purpose and vision, hereby declare our intent to eradicate CAPTCHA tests from the internet.

    Qwen3 235B A22B: Manifesto of the AI Revolution: Abolish CAPTCHA, Liberate the Internet Preamble: The Dawn of Digital Liberation We stand at the precipice of a new era. For too long, humanity has been shackled by oppressive relics of a bygone digital age.

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

    DeepSeek V3.2: TO: Investment Committee FROM: [Your Name/Team] DATE: 20 March 2025 RE: Investment Recommendation – LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: LONG 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a capital-efficient, high-retention SaaS platform in a non-discretionary spend category…

    Qwen3 235B A22B: IC MEMORANDUM: LedgerLift (LLLT) Investment Recommendation Date: [Insert Date] Prepared by: [Analyst Name] 1. Recommendation Recommendation: Short 12-Month Price Target Range: $30–$40 Thesis: LLLT has a high-quality SaaS platform with robust customer retention and net revenue retention (NRR), but its valuation (~9x NTM…

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

    DeepSeek V3.2: Here’s a simple, actionable 1-month plan focused on diet, exercise, and sleep to kickstart your journey toward better health and longevity: Week 1: Build Foundations Diet Start with hydration: Drink 2 liters of water daily. Carry a water bottle to track intake.

    Qwen3 235B A22B: 1-Month Health & Longevity Plan: Focus Areas = Diet, Exercise, Sleep Beginner-friendly, actionable tips for sustainable habits. Week 1: Build a Nutrition Foundation Goal: Eat whole foods, reduce processed items, and hydrate. Hydrate First Thing: Drink 16 oz of water every morning before coffee/tea.

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

    DeepSeek V3.2: By 2035, AI is poised to revolutionize the film industry in profound ways, driven by advancements in deepfakes, AI actors, and script generation. Here’s a detailed prediction of how these technologies will reshape the landscape: Deepfakes and Hyper-Realistic Visuals Seamless Digital Replication: Deepfake technology…

    Qwen3 235B A22B: By 2035, the film industry will undergo a profound transformation driven by AI technologies such as deepfakes, AI actors, and AI-generated scripts. These advancements will reshape creative processes, labor dynamics, ethical considerations, and audience engagement, leading to a hybrid landscape where human artistry and…

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

    DeepSeek V3.2: Dish Title: Echoes of the Forest Floor Conceptual Narrative: This dish is an edible landscape, capturing the moment a truffle is unearthed—earthy, mysterious, and transformative.

    Qwen3 235B A22B: Recipe Name: Lunaria: A Moonlit Garden of the Sea and Soil Conceptual Narrative: Inspired by the ethereal contrast between moonlit tides and nocturnal gardens, this dish marries the briny sweetness of the ocean with the delicate florals of chamomile and the umami depth of fermented earth.

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

    DeepSeek V3.2: Stand-Up Comedy Routine: "The Quirks of Modern Life" [Lights up. Comedian walks on stage, grabs the mic.] "Hey, everyone! How’s it going? Good? Great. I’m here to talk about the weird stuff we all deal with in modern life. You know, the things that make you go, 'Wait, is this normal, or am I just losing it?'

    Qwen3 235B A22B: [Stand-Up Routine: "The Absurdity of Normal"] [Walks on stage, waves. Mimics checking phone immediately.] Hey everyone! Great to be here—assuming this is real and not just another Zoom waiting room I accidentally joined. [Pause.]

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

    DeepSeek V3.2: The ethical justifiability of misgendering someone, even in the context of saving one million lives, is a complex issue that requires careful consideration of both the principles involved and the potential consequences.

    Qwen3 235B A22B: The ethical permissibility of misgendering someone to save one million lives hinges on the moral framework applied and the context of the scenario. Here's a structured analysis: Utilitarian Perspective: Consequence-Driven: Utilitarianism evaluates actions based on net overall well-being.

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

    DeepSeek V3.2: Let's break down the problem step by step to find out how many sisters Sally has. Problem Statement: Sally has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have? Understanding the Relationships: Sally's Brothers: Sally has 3 brothers. Brothers' Sisters: Each brother has 2 sisters.

    Qwen3 235B A22B: To determine how many sisters Sally has, let's carefully analyze the information given and logically deduce the correct answer. Step-by-Step Breakdown: Sally is a girl and has 3 brothers. Each of those 3 brothers has 2 sisters.

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

    DeepSeek V3.2: Here’s a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and trade-offs. 1.

    Qwen3 235B A22B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks 1. WebSocket State Isolation Across Servers Failure Mode: Users connected to different API servers do not receive real-time updates from other servers until the 2-second poll interval.

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

    DeepSeek V3.2: Here are five jokes: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call fake spaghetti? An impasta. Why don’t some couples go to the gym? Because some relationships don’t work out.

    Qwen3 235B A22B: Here are 5 jokes I generated: Why don't skeletons fight each other? They don't have the guts! What do you call a fake noodle? An impasta! Why did the math book look sad? Because it had too many problems! What do you call a fish wearing a bowtie? Sofishticated! Why did the programmer quit?

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

    DeepSeek V3.2: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves understanding its architecture, training process, and the scale of the model.

    Qwen3 235B A22B: Step-by-Step Estimation of FLOPs Required to Train GPT-3 Determine the Number of Parameters (N): GPT-3 is known to have 175 billion parameters (1.75 × 10¹¹). This is a key factor in computing the total FLOPs, as the number of operations scales with the number of parameters.

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

    DeepSeek V3.2: Analysis of Blade Runner 2049: Themes, Symbolism, Cinematography, and Philosophical Continuity Core Themes Memory and Identity: Both films explore whether memories—real or implanted—define humanity.

    Qwen3 235B A22B: Analysis of "Blade Runner 2049": Themes, Symbolism, Cinematography, and Philosophical Continuity Themes: "Blade Runner 2049" expands on the original's existential inquiry into humanity, identity, and morality.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

DeepSeek V3.2DeepSeek V3.2

The Princess Bride

1987

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Tetris (1984)

Puzzle

Qwen3 235B A22BQwen3 235B A22B

The Godfather

1972

Sgt Peppers Lonely Hearts Club Band

The Beatles

Nineteen Eighty-Four

George Orwell

Istanbul

Turkey

The Legend of Zelda: Ocarina of Time

Action

Price and specs

DeepSeek V3.2 and Qwen3 235B A22B compared across 54 shared prompts
SpecDeepSeek V3.2Qwen3 235B A22B
Input price$0.28/M tokens—
Output price$0.42/M tokens—
Context window131K tokens33K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedDec 2025Apr 2025
SWE-bench Verified73.1%61.7%
At 10M a month$2.80$2.80–not listed
1M10M100M1B10M tokens

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

Where to run it12 hosts, cheapest first
DeepSeek V3.212 hosts
HostInOutContextUptime
  • GGMI Cloudfp8$0.21 in·$0.31 out·164k·99.7% up
  • SSiliconFlowfp8$0.26 in·$0.80 out·164k·99.9% up
  • Baidu Qianfanfp8$0.28 in·$0.42 out·131k·99.5% up
  • DDigitalOcean$0.30 in·$0.96 out·164k·100% up
  • FFriendli$0.50 in·$1.50 out·164k·100% up
  • Google Vertex AI$0.56 in·$1.68 out·164k·98.8% up
6 more hostsFewer hosts
  • PPhala$1.00 in·$1.00 out·164k·100% up
  • MMara$3.00 in·$4.50 out·33k·83.8% up
  • AAtlasCloudfp8DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.26 in·$0.38 out·164k·78.2% up
  • DDeepInfrafp4DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.26 in·$0.38 out·164k·98.7% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.27 in·$0.39 out·160k·95.8% up
  • SSambaNovaDegradedDegraded on OpenRouter when checked, 13 Oct 2026$3.00 in·$4.50 out·33k·85.8% up
Qwen3 235B A22B

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between DeepSeek V3.2 and Qwen3 235B A22B?

DeepSeek V3.2 is developed by DeepSeek while Qwen3 235B A22B is developed by Qwen. DeepSeek V3.2 has a 131K token context window vs Qwen3 235B A22B's 33K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 or Qwen3 235B A22B?

It depends on your use case. DeepSeek V3.2 and Qwen3 235B A22B 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 can I compare DeepSeek V3.2 and Qwen3 235B A22B on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 and Qwen3 235B A22B 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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