DeepSeek V3.2 has a larger context window than Qwen3 235B A22B (131K tokens vs 33K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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).
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…
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.
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.
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.
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…
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…
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.
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.
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."
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.
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.
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| Spec | ||
|---|---|---|
| Input price | $0.28/M tokens | — |
| Output price | $0.42/M tokens | — |
| Context window | 131K tokens | 33K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Apr 2025 |
| SWE-bench Verified | 73.1% | 61.7% |
| At 10M a month | $2.80 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
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.
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.
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.