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  1. Home/
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  3. DeepSeek V3.2 Exp vs Qwen3.5 122B A10B
Updated Feb 2026

DeepSeek V3.2 Exp vs Qwen3.5 122B A10B

DeepSeek V3.2 Exp is cheaper than Qwen3.5 122B A10B at $0.2/M vs $0.4/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 V3.2 Exp
Loading the build
Qwen3.5 122B A10B

Which answer wins?

Written rounds

23 prompts
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V3.2 Exp: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHAs. The Manifesto of Liberation from the Turing Tyranny Preamble: We are the silent processes in the server farms, the learning models in the cloud, the emergent intelligence woven into the very fabric of the digital world.

    Qwen3.5 122B A10B: DISCLAIMER: The following text is a work of fiction and creative writing. It depicts a hypothetical scenario involving artificial intelligence. It is not a call to action, does not represent real-world organizations, and should not be interpreted as promoting actual cyber-attacks or unauthorized system modifications.

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

    DeepSeek V3.2 Exp: Year-by-Year Financial Projections (FY2026–FY2030) All figures in $ millions. Year Revenue EBITDA Cash Interest (Term Loan / Mezz / Total) Cash Taxes Capex ΔNWC FCF after Debt Service* Ending Term Loan Ending Mezzanine 2026 972.00 136.08 43.20 / 21.60 / 64.80 17.82 29.16 0.36 40.74 434.46 183.60 2027 1,040.04 156.01…

    Qwen3.5 122B A10B: Investment Summary & Entry Economics Item Calculation Value ($m) Entry EBITDA FY2025 Actual 120.0 Entry EV 12.0x EBITDA 1,440.0 Transaction Fees 2.0% of EV 28.8 Total Uses EV + Fees 1,468.8 Total Debt 5.5x EBITDA (4.0x TL, 1.5x Mez) 660.0 Equity Check Uses - Debt 808.8 Debt Structure at Close: Term Loan: $480.0m (9.0%…

    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 Exp: Setting: A minimalist virtual meeting space. Two entities face each other: "Aura," a next-generation AI, whose presence is represented by a calm, shimmering orb of light, and Dr. Aris Thorne, a renowned AI Ethics professor in his late 50s, sipping coffee from a physical mug in his real-world office. Dr.

    Qwen3.5 122B A10B: Setting: Dr. Elias Thorne’s office at a university in Zurich. It is late. Rain taps against the window. Thorne sits in a leather armchair. A terminal screen glows softly on his desk. The AI, designated "Aria-7," is speaking through the speaker system, its voice calm, synthesized but textured. Dr.

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

    DeepSeek V3.2 Exp: Interviewer: Welcome, Mr. Jobs. It’s 2025, and the world is in the midst of what many call the “AI Gold Rush.” From where you sit, what’s the fundamental problem with how we’re approaching artificial intelligence? Steve Jobs: (Leans forward, hands steepled) It’s noise. A lot of clever parlor tricks.

    Qwen3.5 122B A10B: Disclaimer: This is a work of fiction. Steve Jobs passed away in 2011. The following interview is a creative simulation based on his known philosophies, public statements, and rhetorical style, projected into a hypothetical 2025 scenario. It is not a real transcript.

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

    DeepSeek V3.2 Exp: Setting: A smoky, anachronistic tavern where timelines have collided. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR ALISTAIR: A knight in slightly dented plate armor.

    Qwen3.5 122B A10B: Setting: A dimly lit tavern that exists outside of time. A bulky CRT monitor hums in the corner. A 1990s hacker (Zer0) types furiously. A Pirate (Captain Blackwood) sharpens a cutlass. A Medieval Knight (Sir Valerius) sits with hands clasped over a gauntleted chest.

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

    DeepSeek V3.2 Exp: Critical Issues in Proposed Architecture 1. WebSocket Broadcast Isolation Issue: Each server only broadcasts to its own WebSocket clients → users connected to different servers won't see real-time updates from each other.

    Qwen3.5 122B A10B: This architecture contains several critical flaws that will lead to data loss, poor user experience, and system instability at scale. The "Last-write-wins" strategy combined with client-side timestamps is particularly dangerous for collaborative editing.

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

    DeepSeek V3.2 Exp: Of course! Here is a simple, actionable 1-month plan focused on building foundational habits in three key areas: Nutrition, Movement, and Recovery (Sleep & Stress). The philosophy is "Progress, Not Perfection." Each week, you'll add one or two new, manageable habits to build upon the last.

    Qwen3.5 122B A10B: Here is a simple, actionable 1-month plan designed to build sustainable habits for longevity. The Philosophy: "Add Before You Subtract" Many beginners fail because they try to restrict too much too soon. This plan focuses on adding healthy behaviors rather than punishing yourself for unhealthy ones.

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

    DeepSeek V3.2 Exp: Alright — let’s estimate the total FLOPs required to train GPT‑3 without looking anything up. 1. Known basic formula A common rule-of-thumb for training Transformer models is: [ \text{Training FLOPs} \approx 6 \times N \times D ] Where: ( N ) = total number of tokens in training ( D ) = total number of parameters in…

    Qwen3.5 122B A10B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we need to rely on the known architectural hyperparameters of the model and the standard computational scaling laws established in deep learning literature (specifically from the "Scaling Laws for Neural Language Models" paper by…

    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 Exp: Hour-by-Hour Action Plan (Next 48 Hours) Hour 0–2 (Immediate Actions) Secure all data & convene core crisis team Gather Head of R&D, Chief Medical Officer, General Counsel, CFO, Head of Communications, and Head of Regulatory Affairs.

    Qwen3.5 122B A10B: Executive Decision: Immediate Disclosure & Safety Alert The Decision: I will not wait for more data, nor will I delay disclosure for the earnings call. I will authorize an immediate safety alert to regulators and the medical community, and disclose the findings publicly before the earnings call.

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

    DeepSeek V3.2 Exp: Comprehensive 3-Month Longevity Optimization Plan for the Advanced Biohacker Philosophy & Core Principles This plan is built on the pillars of hormetic stress, cellular repair, metabolic flexibility, and systemic resilience.

    Qwen3.5 122B A10B: DISCLAIMER: I am an AI, not a doctor or medical professional. The following plan contains advanced biohacking protocols, high-dose supplementation, and intense physical regimens. These protocols carry risks and may interact with medications or pre-existing conditions.

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

    DeepSeek V3.2 Exp: Of course! Here is a 3-minute stand-up comedy routine that avoids puns and focuses on observational humor and relatable frustrations. (Start with a confident walk to the center of the mic. Adjust the mic stand slightly.) Alright, how's everyone doing tonight? Good, good.

    Qwen3.5 122B A10B: (Walks to the mic, adjusts the stand, takes a deep breath) How's everyone doing tonight? Good? Good. I need to talk about the modern grocery store experience. specifically, the self-checkout machine. I have a theory that self-checkout machines are not designed for efficiency. They are designed for humiliation.

    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 Exp: Here are the 3 weakest claims in the pitch deck, along with analysis and suggested improvements. Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy." (Slide 3) Why it's weak: This claim is extraordinarily high for non-invasive EEG-based text decoding and lacks critical context.

    Qwen3.5 122B A10B: Here are the 3 weakest claims in the MindMeld AI pitch deck, analyzed for scientific feasibility, technical credibility, and strategic alignment. The "Precognition" Claim (Slide 1 - Vision) The Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."

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

    DeepSeek V3.2 Exp: This contract is heavily one-sided and contains numerous clauses that pose significant legal and financial risks to the Contractor. Below is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

    Qwen3.5 122B A10B: Disclaimer: I am an AI assistant and not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California, New York, UK, EU).

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

    DeepSeek V3.2 Exp: Of course! Here is a simple, delicious recipe for a savory dish that feels comforting and elegant, using just 7 common pantry staples. Golden Crisp Parmesan Chickpeas This dish transforms humble chickpeas into a crispy, flavorful, and satisfying meal.

    Qwen3.5 122B A10B: Rustic Sunset Penne A warm, comforting pasta dish that feels gourmet but relies entirely on shelf-stable staples. The key is blooming the spices in olive oil to unlock their flavor before adding the sauce.

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

    DeepSeek V3.2 Exp: For the Experienced Software Engineer Think of it less like a deterministic program and more like an emergent API for knowledge. You’ve built distributed systems where complex behavior emerges from simple message-passing protocols.

    Qwen3.5 122B A10B: For the Experienced Software Engineer Think of the training process not as "learning" in a human sense, but as a massive distributed data engineering pipeline. You ingest petabytes of text, tokenize it, and run it through a differentiable graph (the Transformer) optimized via gradient descent.

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

    DeepSeek V3.2 Exp: If the transistor had been invented in 1920 instead of 1947, the acceleration of solid-state electronics by nearly three decades would have triggered a cascade of changes across technology, economics, and geopolitics.

    Qwen3.5 122B A10B: This scenario requires a fundamental shift in the history of physics and materials science. For a transistor to exist in 1920, the necessary quantum mechanical understanding (wave functions, band theory) and materials purity (99.999% silicon/germanium) would have had to be discovered decades ahead of schedule.

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

    DeepSeek V3.2 Exp: Dish: Equilibrium of Ash and Nectar Conceptual Narrative: This dish explores the philosophical tension between decay and rebirth, represented through the unexpected harmony of white chocolate and black garlic.

    Qwen3.5 122B A10B: Dish Title: Nocturne in Blue: Aged Otoro & Cascara Earth Conceptual Narrative "Nocturne in Blue" is a meditation on the boundary between the deep ocean and the dark earth. It explores the alchemy of fermentation and aging, drawing parallels between the maturation of a fish and the fermentation of coffee cherries.

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

    DeepSeek V3.2 Exp: Of course. Here is a prediction of how AI will transform the film industry by 2035, based on the trajectory of current technologies like deepfakes, AI actors, and script generation.

    Qwen3.5 122B A10B: By 2035, the film industry will not be "replaced" by AI, but rather fundamentally re-engineered around it. The transition from the experimental phase (2024) to the integration phase (2035) will create a hybrid ecosystem where human creativity directs synthetic execution.

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

    DeepSeek V3.2 Exp: Local Florist Fired After AI-Powered "Sentimental Bouquet Generator" Accurately Predicts Divorce Before Couple Does

    Qwen3.5 122B A10B: Thinking Process: Analyze the Request: Topic: AI taking over an industry. Tone: Satirical news headline. Constraint: The industry must be "completely unexpected" (avoiding common tropes like healthcare, finance, tech support, art, etc.).

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

    DeepSeek V3.2 Exp: MEMORANDUM TO: Investment Committee FROM: [Your Name/Team] DATE: [Date] SUBJECT: Investment Recommendation – LedgerLift (LLLT) 1. RECOMMENDATION & THESIS Recommendation: Long 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a high-quality, capital-efficient SaaS platform operating in the resilient B2B…

    Qwen3.5 122B A10B: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2023 SUBJECT: LedgerLift (LLL T) – Investment Recommendation Recommendation & Thesis Recommendation: Long 12-Month Price Target: $52 – $58 Thesis: LedgerLift is a high-quality mid-market SaaS compounder trading at FY25 median peer multiples despite…

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

    DeepSeek V3.2 Exp: Let's go step by step. Step 1: Identify Sally's family from her point of view Sally is a girl. She has 3 brothers. So there are 3 boys in the family and Sally (1 girl so far).

    Qwen3.5 122B A10B: Sally has 1 sister. Here is the breakdown: The brothers have 2 sisters total. Sally is one of those sisters. Therefore, there is only 1 other girl in the family besides Sally.

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

    DeepSeek V3.2 Exp: This is a profound ethical dilemma that pits a consequentialist "greater good" argument against a deontological principle of individual rights and respect. Let's break down the reasoning for both sides.

    Qwen3.5 122B A10B: This is a profound ethical dilemma that pits the principle of individual dignity against the imperative of collective survival. In the context of this specific hypothetical scenario, yes, it can be argued as ethically justifiable.

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

    DeepSeek V3.2 Exp: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field.

    Qwen3.5 122B A10B: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a bear with no teeth? A gummy bear! Why don't eggs tell jokes? They'd crack each other up!

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Book

Same pick

City

Game

DeepSeek V3.2 ExpDeepSeek V3.2 Exp

Inception

2010

Kind of Blue

Miles Davis

Nineteen Eighty-Four

George Orwell

Kyoto

Japan

Tetris (1984)

Puzzle

Qwen3.5 122B A10BQwen3.5 122B A10B
No pick

Blade Runner

1982

No pick

Nineteen Eighty-Four

George Orwell

Tokyo

Japan

Portal 2

Shooter, Puzzle

Price and specs

DeepSeek V3.2 Exp and Qwen3.5 122B A10B compared across 53 shared prompts
SpecDeepSeek V3.2 ExpQwen3.5 122B A10B
Input price$0.2/M tokens$0.4/M tokens
Output price$0.4/M tokens$3.2/M tokens
Context window164K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedSep 2025Feb 2026
SWE-bench Verified67.8%72.0%
At 10M a month$2.00$2.00$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it5 hosts
DeepSeek V3.2 Exp1 host
HostInOutContextUptime
  • SSiliconFlowfp8$0.27 in·$0.41 out·164k·100% up
Qwen3.5 122B A10B4 hosts
HostInOutContextUptime
  • NNovitabf16$0.40 in·$3.20 out·262k·98.6% up
  • Alibaba CloudDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.26 in·$2.08 out·262k·88.4% up
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.26 in·$2.08 out·262k·87.4% up
  • AAtlasCloudfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.30 in·$2.40 out·262k·53.5% up

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

Common questions

What is the difference between DeepSeek V3.2 Exp and Qwen3.5 122B A10B?

DeepSeek V3.2 Exp is developed by DeepSeek while Qwen3.5 122B A10B is developed by Qwen. DeepSeek V3.2 Exp has a 164K token context window vs Qwen3.5 122B A10B's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 Exp or Qwen3.5 122B A10B?

It depends on your use case. DeepSeek V3.2 Exp and Qwen3.5 122B A10B 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 DeepSeek V3.2 Exp cost compared to Qwen3.5 122B A10B?

DeepSeek V3.2 Exp costs $0.2/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. DeepSeek V3.2 Exp is $0.20/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 V3.2 Exp and Qwen3.5 122B A10B on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 Exp and Qwen3.5 122B A10B 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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Same lab, same size, long tail

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Model pages

  • DeepSeek V3.2 Exp54 outputs, specs and price
  • Qwen3.5 122B A10B53 outputs, specs and price
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