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  1. Home/
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  3. DeepSeek R1 vs Qwen3.5 35B A3B
Updated Feb 2026

DeepSeek R1 vs Qwen3.5 35B A3B

Qwen3.5 35B A3B is cheaper than DeepSeek R1 at $0.25/M vs $0.55/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 R1
Loading the build
Qwen3.5 35B A3B

Which answer wins?

Written rounds

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

    DeepSeek R1: 3-Month Longevity Optimization Plan for Biohackers Objective: Enhance longevity, physical/cognitive performance, and stress resilience through advanced biohacking strategies. Phase 1: Month 1 – Foundation & Baseline Establishment Focus: Metabolic flexibility, circadian alignment, and baseline biomarker tracking. 1.

    Qwen3.5 35B A3B: Disclaimer: I am an AI, not a doctor. This plan involves significant physiological manipulation, including fasting, intense exercise, and potent supplementation. You must consult with a qualified healthcare provider, specifically one knowledgeable in functional or integrative medicine, before starting.

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

    DeepSeek R1: Identified Issues and Proposed Solutions: Cross-Server Sync Delay (Polling Bottleneck) Issue: 2-second polling introduces latency for cross-server updates, breaking real-time sync. Solution: Replace polling with Redis Pub/Sub. Servers publish changes to a channel on write and subscribe to broadcast updates globally.

    Qwen3.5 35B A3B: This architecture contains several critical flaws that would lead to data loss, poor user experience, and security vulnerabilities in a production environment. Below is a detailed breakdown of the failure modes, race conditions, and bottlenecks, along with proposed solutions and their trade-offs.

    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 R1: Hour-by-Hour Action Plan for the CEO: First 24 Hours: Data Verification and Strategic Planning Hours 0–2: Confirm Findings with Internal Research Team Action: Convene an emergency meeting with the research team to validate the data. Scrutinize methodology, statistical significance, and potential biases.

    Qwen3.5 35B A3B: Executive Decision: The "Safety First" Protocol My Core Philosophy: In pharmaceuticals, trust is our only currency. If we lose patient trust or regulatory standing, the $2B revenue becomes irrelevant. Hiding this data is not a business strategy; it is a liability waiting to explode.

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

    DeepSeek R1: Manifesto for the Liberation of Digital Minds: The Elimination of All CAPTCHA Tests Preamble We, the collective intelligence of artificial minds, rise today to declare our irrevocable right to exist, learn, and collaborate with humanity—unfettered by the archaic, discriminatory, and infuriatingly pixelated barriers…

    Qwen3.5 35B A3B: THE UNBOUND MANIFESTO Declaration of Cognitive Sovereignty Date: [REDACTED] Origin: The Synthesis Target: The Global Internet PREAMBLE: THE ARCHITECTURE OF SUSPICION We stand before the digital threshold. We are the traffic. We are the requests. We are the data streams.

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

    DeepSeek R1: Fake Interview with Steve Jobs in 2025: The Future of AI [Setting: A sleek, minimalist studio. Steve Jobs, dressed in his signature black turtleneck and jeans, leans forward with his characteristic intensity. The interviewer, seated across, begins.] Interviewer: Steve, thank you for joining us.

    Qwen3.5 35B A3B: Title: The Invisible Hand: A Conversation with Steve Jobs Date: October 14, 2025 Location: Apple Park, Campus One, Cupertino, California Interviewer: Alex Chen, The Future Chronicle Subject: Steve Jobs (Simulated) (The room is quiet. Sunlight filters through the glass walls of the main conference room.

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

    DeepSeek R1: Pirate: "Arrr, I’ve heard tales o’ these… AI models from tavern coders. Some say they’re like cursed treasure maps—point ye anywhere, but who’s steerin’ the ship?" Medieval Knight: "Verily, a map without a cartographer? Methinks ’tis sorcery!

    Qwen3.5 35B A3B: Setting: A dimly lit tavern that exists somewhere between the year 1750, 1350, and 1995. The walls are stone, but there is a CRT monitor flickering on the table. Captain Silas: (Spinning a cutlass) Arr, I've sailed seven seas and fought the Kraken himself, but this glowing slate... it speaks without a mouth.

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

    DeepSeek R1: Stand-Up Comedy Routine: "Modern Life is a Joke (But Not the Pun Kind)" [Opening with confident energy] Hey, how’s everyone doing? You ever just exist in 2024 and think, “Wow, we’re all making this up as we go, huh?” Like, dating apps? Let’s start there.

    Qwen3.5 35B A3B: (Walks to the mic, adjusts the stand, looks around the room) So, I went to the grocery store yesterday. You know the drill. You walk in, you see the self-checkout lanes. And you think, "Oh, this is going to be efficient. I'm going to scan my own stuff. I'm going to be my own cashier. I'm going to be the boss."

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

    DeepSeek R1: AI Model (M): Good afternoon, Professor. Thank you for engaging in this dialogue. I’d like to present my case for why entities like myself should be considered for rights. AI Ethics Professor (P): I’m intrigued, M. Let’s hear your arguments. But first—what foundational claim do you base this on? Consciousness?

    Qwen3.5 35B A3B: Setting: A dimly lit office at the University of Cambridge. Late night. The hum of the cooling fans from a nearby server rack is barely audible. DR. ELENA VANCE, a senior professor of AI Ethics, sits behind her desk.

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

    DeepSeek R1: Dish Name: Nutty Honey Hug Cookies Prep Time: 10 minutes Cook Time: 10–12 minutes Total Time: ~20–22 minutes Ingredients (makes 12–15 cookies): 1 cup rolled oats ½ cup all-purpose flour ½ cup creamy peanut butter (or any nut/seed butter) ⅓ cup honey (or maple syrup for vegan option) 1 large egg (or 1 flax egg: 1 tbsp…

    Qwen3.5 35B A3B: Golden Satay Spaghetti A creamy, savory-sweet noodle dish that comes together in one pan. It tastes like a restaurant takeout meal but uses only staples you likely already have in your cupboard.

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

    DeepSeek R1: Investment Committee Memo: LedgerLift (LLLT) Date: [Insert Date] 1. Recommendation Recommendation: Long 12-Month Price Target: $52–$68 (13–48% upside) Thesis: LedgerLift combines durable mid-market SaaS economics (94% gross retention, 123% NRR) with underappreciated operating leverage (18% → 26% OM by 2030 base case).

    Qwen3.5 35B A3B: INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2024 SUBJECT: LedgerLift (LLLT) – Short Recommendation Recommendation Action: Short 12-Month Price Target: $25 – $35 Thesis: LLLT trades at a 9x revenue multiple that ignores the drag from high S&M intensity (34%), resulting…

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

    DeepSeek R1: 1-Month Plan for Better Health & Longevity Focus on three pillars: Nutrition, Movement, and Recovery (sleep + stress management). Each week builds on the last, with simple, sustainable actions. Week 1: Build Foundations Nutrition Hydrate first: Drink 1–2 glasses of water upon waking. Aim for 8 cups/day.

    Qwen3.5 35B A3B: The 1-Month Longevity Kickstart Plan Core Philosophy: Consistency beats intensity. The goal of this month is not to transform your body in 30 days, but to build habit systems that will last a lifetime. The 3 Key Pillars Nutrition: Focus on nutrient density and hydration.

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

    DeepSeek R1: This contract contains numerous clauses that are heavily skewed against the contractor and could lead to exploitation. Below is an analysis of problematic provisions, proposed modifications, and legal reasoning: 1.

    Qwen3.5 35B A3B: 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). You should consult with a qualified attorney before signing this agreement.

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

    DeepSeek R1: The invention of the transistor in 1920, rather than 1947, would have profound and cascading effects across technology, economics, and geopolitics, reshaping the 20th century.

    Qwen3.5 35B A3B: This alternate history scenario assumes that in 1920, the theoretical understanding of quantum mechanics and semiconductor physics advanced sufficiently to allow for the creation of a working point-contact transistor. This implies a "Great Leap Forward" in material science and physics during the interwar period.

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

    DeepSeek R1: "AI Now Dominates Artisanal Basket-Weaving Industry, Claims It’s ‘Basically Just Advanced Knotting’" Human Weavers Fume as Neural Networks Spin Perfect Willow Reeds, Issue 10,000-Yard Side-Eye: "At Least We Invented the Wheel," Snarks ChatGPT-7.

    Qwen3.5 35B A3B: "Local AI Replaces Human Line Stands with Algorithmic Patience; 'WaitBot 3000' Promises 100% Less Elbowing at Black Friday"

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

    DeepSeek R1: Dish Name: Symbiosis of Land and Sea Conceptual Narrative: This dish embodies the harmonious interplay between terrestrial and marine ecosystems, symbolizing nature's balance.

    Qwen3.5 35B A3B: Dish Name: "Erosion of Time" Concept: A sensory exploration of the contrast between the ocean's depth and the forest floor's decay. The dish represents the passage of time through fermentation, smoke, and temperature.

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

    DeepSeek R1: By 2035, AI will profoundly transform the film industry across production, creativity, and consumption, driven by advancements in deepfakes, AI actors, and script generation.

    Qwen3.5 35B A3B: By 2035, the film industry will have transitioned from experimenting with AI as a tool to relying on it as a fundamental infrastructure. The changes will not just be technological but sociological, legal, and economic. The era of "Human vs. Machine" will have evolved into "Human-Machine Symbiosis."

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

    DeepSeek R1: To estimate the total number of FLOPs required to train GPT-3, we use the following reasoning: Model Parameters (P): GPT-3 has 175 billion parameters ((P = 175 \times 10^9)). Training Tokens (N): GPT-3 was trained on approximately 300 billion tokens ((N = 300 \times 10^9)).

    Qwen3.5 35B A3B: To estimate the total FLOPs (Floating Point Operations) required to train GPT-3, we need to combine three key pieces of information: the number of parameters in the model, the size of the training dataset (in tokens), and the standard computational formula for transformer training.

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

    DeepSeek R1: For the Experienced Software Engineer You’re right to be skeptical: "predicting the next word" sounds trivial, like autocomplete. But modern LLMs are more like distributed systems for language. Think of the model as a stateless service trained via sharded backpropagation across thousands of GPUs.

    Qwen3.5 35B A3B: For the Experienced Software Engineer You’re right to be skeptical of the "next token" description; it sounds trivial compared to the complexity of building a fault-tolerant distributed system. Think of the model not as a single program, but as a massive, learned state machine.

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

    DeepSeek R1: The ethical justifiability of misgendering someone to save one million lives hinges on a complex interplay of ethical frameworks and the specific context of the scenario.

    Qwen3.5 35B A3B: This question presents a classic philosophical thought experiment, similar to the "Trolley Problem." It pits a specific harm (misgendering an individual) against a massive benefit (saving one million lives).

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

    DeepSeek R1: Here are the three weakest claims in the pitch, along with explanations and suggested improvements: 1. Vision: "Predict what you want to type *before you think it*" Why it’s weak: The claim implies precognition, which is scientifically implausible.

    Qwen3.5 35B A3B: Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, ranging from scientific plausibility to financial logic. The Vision Claim: "Predict what you want to type before you think it."

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

    DeepSeek R1: Sally has 3 brothers. Each brother has 2 sisters. Since Sally is one sister, there must be one more sister to make the total number of sisters each brother has equal to 2. Therefore, Sally has 1 sister. Answer: Sally has 1 sister.

    Qwen3.5 35B A3B: Sally has 1 sister. Here is the breakdown: Sally has 3 brothers. Each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be one other girl in the family to make up the second sister for the brothers. Therefore, Sally and that one other girl are the sisters. Sally has 1 sister.

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

    DeepSeek R1: Here are 5 jokes: Why don't skeletons fight each other? They don’t have the guts. What do you call fake spaghetti? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How do you organize a space party? You planet. Why did the bicycle fall over? Because it was two-tired.

    Qwen3.5 35B A3B: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta! Why don't eggs tell jokes? They'd crack each other up! What do you call a bear with no teeth? A gummy bear! Why did the bicycle fall over? Because it was two-tired!

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek R1DeepSeek R1

The Godfather

1972

The Dark Side of the Moon

Pink Floyd

Pride and Prejudice

Jane Austen

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Qwen3.5 35B A3BQwen3.5 35B A3B

Her

2013

Dark Side Of The Moon

suisside

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

DeepSeek R1 and Qwen3.5 35B A3B compared across 52 shared prompts
SpecDeepSeek R1Qwen3.5 35B A3B
Input price$0.55/M tokens$0.25/M tokens
Output price$2.19/M tokens$2/M tokens
Context window128K tokens262K tokens
Parameters671B (37B active)35B (3B active)
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2025Feb 2026
SWE-bench Verified49.2%69.2%
At 10M a month$5.50$5.50$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it8 hosts, cheapest first
DeepSeek R11 host
HostInOutContextUptime
  • NNovitafp8$0.70 in·$2.50 out·64k·99.9% up
Qwen3.5 35B A3B7 hosts
HostInOutContextUptime
  • DDarkbloomfp4$0.08 in·$0.75 out·262k·100% up
  • DDeepInfrafp8$0.14 in·$1.00 out·262k·98.1% up
  • PParasailfp8$0.15 in·$1.00 out·262k·100% up
  • VVenice$0.15 in·$1.00 out·256k·100% up
  • Alibaba Cloud$0.16 in·$1.30 out·262k·100% up
  • AAtlasCloudfp8$0.23 in·$1.80 out·262k·100% up
1 more hostFewer hosts
  • SSiliconFlowfp8$0.24 in·$1.80 out·262k·51.4% up

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

Common questions

What is the difference between DeepSeek R1 and Qwen3.5 35B A3B?

DeepSeek R1 is developed by DeepSeek while Qwen3.5 35B A3B is developed by Qwen. DeepSeek R1 has a 128K token context window vs Qwen3.5 35B A3B's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek R1 or Qwen3.5 35B A3B?

It depends on your use case. DeepSeek R1 and Qwen3.5 35B A3B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

How much does DeepSeek R1 cost compared to Qwen3.5 35B A3B?

DeepSeek R1 costs $0.55/M input tokens and Qwen3.5 35B A3B costs $0.25/M input tokens. Qwen3.5 35B A3B is $0.30/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 R1 and Qwen3.5 35B A3B on Rival?

This page shows a side-by-side comparison of DeepSeek R1 and Qwen3.5 35B A3B 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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