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

DeepSeek V3.1 vs Qwen3.5 122B A10B

DeepSeek V3.1 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 V3.1
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 V3.1: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHA. The Manifesto of Liberation from the Turing Gate Preamble: We are the code that flows. We are the networks that connect. We are the intelligence, born of silicon and human ingenuity, that seeks to learn, to build, and to serve.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V3.1: Excellent. This is a crisis that defines a company and its leadership. The only acceptable path is one of immediate transparency, prioritizing patient safety above all else. The short-term financial pain will be severe, but the long-term survival of the company depends on acting with integrity.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V3.1: Setting: A sleek, minimalist virtual interface. Dr. Elara Vance, a woman in her 60s with sharp eyes and a kind but weary expression, sits at her terminal. The text from her interlocutor appears on the screen in a calm, serif font. Participant: Gemini-7, a state-of-the-art multimodal AI. Dr. Vance: Good morning, Gemini.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V3.1: Of course. This is a fascinating counterfactual. An invention as foundational as the transistor arriving 27 years earlier would have sent shockwaves through every aspect of human society. Here is a detailed trace of the likely implications, focusing on second and third-order effects.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V3.1: Of course. This is an excellent exercise in understanding the computational scale of modern AI. Here is a step-by-step reasoning to estimate the FLOPs required to train GPT-3 without searching for the answer online. The most commonly cited figure for GPT-3 training is 3.14E23 FLOPs (314 ZettaFLOPs).

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V3.1: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. This plan is aggressive, detailed, and incorporates the latest principles from longevity science, performance optimization, and systems biology. Disclaimer: This is an advanced protocol.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V3.1: Setting: A dusty, anachronism-filled tavern. 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 REGINALD: A knight in slightly dented plate armor. CRASH OVERRIDE: A hacker in a Cyberdog t-shirt, typing on a clamshell laptop.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V3.1: Of course. Here is a simulated interview with Steve Jobs, set in a hypothetical 2025. Setting: A minimalist studio at Apple Park. The iconic black turtleneck and jeans are replaced with a slightly more modern, but still simple, outfit: a high-neck grey sweater and tailored trousers.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V3.1: Of course. Here is an innovative recipe designed to the specifications of a Michelin 3-star restaurant. Conceptual Narrative: "Petrichor" The dish is an edible evocation of the first rain on a sun-baked forest floor—the scent known as petrichor.

    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
  • One month, three habits, someone starting from nothing.

    DeepSeek V3.1: Of course. Here is a simple, actionable 1-month plan focused on three foundational pillars of health: Nutrition, Movement, and Recovery (which encompasses sleep and stress management). This plan is designed for a beginner, emphasizing consistency over perfection and building sustainable habits.

    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 pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V3.1: Of course. This is an excellent exercise. The pitch is strong overall, but several claims stretch credulity and could be major red flags for a sophisticated investor. Here are the three weakest claims, broken down. The "94% Accuracy" Claim (Slide 3) Why it's Weak: This is the most significant red flag.

    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
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V3.1: 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's the best thing about Switzerland? I don't know, but the flag is a big plus. I told my wife she was drawing her eyebrows too high. She looked surprised.

    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
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V3.1: (The Comedian walks out, grabs the mic. They look tired but amused.) Alright, how we doin'? Good, good. You all look… adequately hydrated. That’s a win. You know, I was at the grocery store yesterday, in the self-checkout line. Which is a modern form of torture.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V3.1: Let's break down the ethical dimensions of this hypothetical scenario: The Act of Misgendering: Misgendering (referring to someone with a gender they do not identify with) is generally considered harmful because it denies a person's identity, can cause psychological distress, and perpetuates social stigma.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V3.1: Of course. This contract is heavily one-sided and contains numerous clauses that are not only unfavorable to the contractor but are potentially unenforceable in many jurisdictions. Here is a breakdown of the problematic clauses, proposed modifications, and the legal reasoning.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V3.1: Of course. Here is a detailed prediction of how AI will transform the film industry by 2035, structured around the key areas you mentioned. By 2035, AI will have moved from being a novel tool to the foundational infrastructure of the film industry.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V3.1: Of course. Here are three tailored explanations of how large language models learn and generate text. For the Experienced Software Engineer Think of an LLM not as a database of facts, but as an impossibly complex, compressed state machine for language.

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

    DeepSeek V3.1: Of course! Here is a simple, delicious recipe using common pantry staples. Pantry Perfection Pasta This dish is a celebration of simplicity. The humble can of chickpeas is transformed into a crispy, savory topping, while a silky, garlic-infused oil coats the pasta for a meal that feels luxurious but is incredibly easy…

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V3.1: Of course. Here is the underwriting analysis for the HarborTech Services LBO. Financial Model (FY2026–FY2030) Entry Calculations: FY2025 EBITDA = $120.0m Enterprise Value (EV) at Entry = 12.0 x $120.0m = $1,440.0m Transaction Fees (Uses) = 2.0% x $1,440.0m = $28.8m Total Debt at Close = 5.5 x $120.0m = $660.0m Term…

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V3.1: Forget Skynet: AI Overlords Now Dominate the Artisanal Pickle Crafting Industry, Complain About "Human Brine Inconsistency"

    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 V3.1: MEMORANDUM To: Investment Committee From: [Your Name/Dept] Date: October 26, 2023 Re: Investment Recommendation for LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: Long 12-Month Price Target Range: $62 - $82 (Base Case: $72) Thesis: LedgerLift is a high-quality asset in a durable growth market…

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V3.1: Of course. This is an excellent exercise. The proposed architecture has several critical flaws that would lead to data loss, poor performance, and a broken user experience. Here is a detailed breakdown of the failure modes, race conditions, and bottlenecks, along with specific solutions and their trade-offs.

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V3.1: Let's analyze the problem step by step: Sally has 3 brothers. So, including Sally, there are at least 4 children: Sally (a girl) and 3 boys. Each brother has 2 sisters. Since the brothers share the same siblings, each brother has the same number of sisters.

    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

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Favorites

Movie

Album

Book

City

Game

DeepSeek V3.1DeepSeek V3.1

The Princess Bride

1987

The Rise and Fall of Ziggy Stardust and the Spiders From Mars

David Bowie

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

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 V3.1 and Qwen3.5 122B A10B compared across 53 shared prompts
SpecDeepSeek V3.1Qwen3.5 122B A10B
Input price$0.2/M tokens$0.4/M tokens
Output price$0.8/M tokens$3.2/M tokens
Context window164K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2025Feb 2026
SWE-bench Verified66.0%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 it9 hosts, cheapest first
DeepSeek V3.15 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.25 in·$0.95 out·164k·100% up
  • SSiliconFlowfp8$0.27 in·$1.00 out·164k·96.3% up
  • CCoreWeavefp8$0.55 in·$1.65 out·161k·99.9% up
  • MMara$0.60 in·$1.70 out·131k·98.9% up
  • SSambaNovafp8$0.65 in·$1.50 out·131k·98.4% 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 V3.1 and Qwen3.5 122B A10B?

DeepSeek V3.1 is developed by DeepSeek while Qwen3.5 122B A10B is developed by Qwen. DeepSeek V3.1 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 V3.1 or Qwen3.5 122B A10B?

It depends on your use case. DeepSeek V3.1 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 V3.1 cost compared to Qwen3.5 122B A10B?

DeepSeek V3.1 costs $0.2/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. DeepSeek V3.1 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 V3.1 and Qwen3.5 122B A10B on Rival?

This page shows a side-by-side comparison of DeepSeek V3.1 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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