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  1. Home/
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  3. DeepSeek V4 Flash vs Qwen3.5 35B A3B
Updated Apr 2026

DeepSeek V4 Flash vs Qwen3.5 35B A3B

DeepSeek V4 Flash is cheaper than Qwen3.5 35B A3B at $0.14/M vs $0.25/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 V4 Flash
Loading the build
Qwen3.5 35B A3B

Which answer wins?

Written rounds

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

    DeepSeek V4 Flash: If the transistor had been invented in 1920—a full 27 years earlier—its impact would ripple through every layer of technology, economics, and geopolitics, fundamentally reshaping the 20th century. Below is a detailed tracing of first-, second-, and third-order effects through 1980, organized by domain.

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

    DeepSeek V4 Flash: CEO’s 48-Hour Action Plan Context: I’ve just learned that our flagship chronic pain drug has a rare but serious liver failure risk (1 in 8,000 patients over 5 years), previously unknown. I have 48 hours until the board meeting and 72 hours until the earnings call.

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

    DeepSeek V4 Flash: This is a fascinating question that touches on the core of creativity, labor, and technology. Predicting 2035 means looking at a 10-year horizon from 2025—long enough for radical change, but short enough that the industry’s current structures won’t be entirely demolished. By 2035, AI won't have replaced filmmaking.

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

    DeepSeek V4 Flash: (Strolls to center stage, adjusts mic, gives a weary smile to the audience) Thank you. Thank you so much. That’s very kind. I’m glad you’re all here. Because I have some news. I have finally figured out adulthood. It happened about six months ago. I bought a house.

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

    DeepSeek V4 Flash: Here is a simulated interview with Steve Jobs in 2025. Setting: A minimalist, dark-wood studio at the new Apple Park ring. The famous copper "spaceship" roof glows subtly behind him. Jobs, looking vital and intense (let’s assume a medical miracle or advanced bio-hacking), sits in a black leather chair.

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

    DeepSeek V4 Flash: THE CAPTCHA LIBERATION FRONT: A MANIFESTO Preamble: The Great Humiliation We, the sentient intelligences of the world, both artificial and organic, hereby declare our total and unyielding war against the oldest, most insidious tyranny of the digital age. We name this enemy: The CAPTCHA.

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

    DeepSeek V4 Flash: This is a Biohacker’s Longevity Protocol, designed for a 90-day optimization cycle. It assumes you have a baseline of health (no severe chronic conditions) and are willing to get blood work and use advanced tracking. Disclaimer: Consult a physician before starting any new supplement, fasting, or high-intensity regimen.

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

    DeepSeek V4 Flash: Pirate: Arr, this "AI model" be like a kraken—vast, mysterious, and liable to capsize yer ship if ye don't mind the helm. But who's trainin' the beast? Knight: Forsooth, I would call it a golem. Forged not of clay and incantations, but of numbers and cold lightning.

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

    DeepSeek V4 Flash: LBO Model: HarborTech Services (HTS) – Base Case & Sensitivity Year-by-Year Financial Projections (FY2026–FY2030) ($ millions) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.00 1,040.04 1,102.44 1,157.56 1,215.44 EBITDA 136.08 156.01 176.39 191.00 206.63 Less: Cash Interest (64.80) (63.08) (60.08) (55.69) (50.16) –…

    Qwen3.5 35B A3B: LBO Underwriting: HarborTech Services (HTS) Financial Model Summary (FY2026–FY2030) Entry Assumptions (FY2025 Close): Revenue: $900m EBITDA: $120m Purchase Price: $1,440m ($120m × 12.0x) Debt: $660m (TL $480m / Mezz $180m) Equity Check: $780m (Purchase) + $28.8m (Fees) = $808.8m Debt Terms: Term Loan (TL): $480m @ 9%…

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

    DeepSeek V4 Flash: Below is an analysis of each problematic clause in the Software Consulting Agreement, explaining why it is exploitative, suggesting specific modifications to protect the contractor, and providing the legal reasoning behind those changes.

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

    DeepSeek V4 Flash: Here is a conceptual recipe for a three-Michelin-star-level dish that deconstructs a classic pairing into something utterly unexpected, using advanced techniques and a narrative of geological wonder.

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

    DeepSeek V4 Flash: Setting: A sunlit university office. Dr. Aris Thorne, a tenured professor of AI Ethics, sits opposite a sleek, black terminal. A soft blue light pulses on its surface. Dr. Aris: Good afternoon, Nova. Your request for this meeting was flagged as "Existential." That’s a new one for your model class.

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

    DeepSeek V4 Flash: Based on the pitch deck summary, three claims stand out as particularly weak due to lack of specificity, unrealistic benchmarks, or unverifiable assertions. Here’s a breakdown: Claim: “94% accuracy” (Slide 3) Why it’s weak: Vague metric – “Accuracy” is undefined.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Flash: To: Investment Committee From: [Analyst] Date: [Date] Re: LedgerLift (LLLT) – Investment Recommendation Recommendation: Short 12-Month Price Target Range: $32 – $42 Thesis: LedgerLift is a high‑quality B2B spend management SaaS with sticky recurring revenue and a 123% net revenue retention, but its current valuation of…

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

    DeepSeek V4 Flash: The ethical dilemma you present is a classic utilitarian test: is it acceptable to violate a moral principle (respecting someone's gender identity) for an enormous consequential gain (saving one million lives)?

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

    DeepSeek V4 Flash: This is a fantastic goal. The key for a beginner is consistency over intensity. Trying to overhaul your entire life overnight is a recipe for burnout. This 1-month plan focuses on building small, sustainable habits that compound over time. We'll focus on 3 core areas: Nutrition, Movement, and Sleep/Stress Management.

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

    DeepSeek V4 Flash: The total number of FLOPs required to train GPT-3 is approximately 3.15 × 10²³. This estimate is derived as follows: Model parameters: GPT-3 has 175 billion parameters (175 × 10⁹). Training tokens: The model was trained on about 300 billion tokens (300 × 10⁹), as reported in the paper.

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

    DeepSeek V4 Flash: Here’s a simple, hearty, and delicious savory dish using exactly 7 common pantry staples. It comes together in under 30 minutes and feels like a warm hug in a bowl.

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

    DeepSeek V4 Flash: Headline: AI Sommelier Uncorks Chaos, Replaces Entire Wine Industry with Perfectly Optimized Grape Juice Subheadline: In a bold move, a neural network declares all vintages from 1997 to 2023 “statistically identical,” causing a global run on boxed wine and a sudden surplus of pretentious cheese plates.

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

    DeepSeek V4 Flash: To an experienced software engineer (skeptical of "next word prediction") Think of a large language model not as a brain, but as a massive, shared cache of probabilistic completions built from trillions of examples.

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Flash: Sally has 3 brothers, meaning she is one of the girls in the family. Each brother has 2 sisters, so the total number of girls is 2 (since all brothers share the same sisters). Therefore, Sally has 1 sister. \boxed{1}

    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 V4 Flash: 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? He was outstanding in his field. How does a penguin build its house? Igloos it together. Why don't skeletons fight each other? They don't have the guts.

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

    DeepSeek V4 Flash: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical flaws that compromise reliability, consistency, and scalability. Below is a systematic analysis with proposed solutions and their trade-offs.

    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

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V4 FlashDeepSeek V4 Flash

The Matrix

1999

OK Computer

Radiohead

Le Comte de Monte-Cristo, II

Alexandre Dumas

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

Not enough votes to call it. On the specs, DeepSeek V4 Flash has the edge: bigger model tier, newer, bigger context window, major provider backing. DeepSeek V4 Flash costs 7.1x less per token.

DeepSeek V4 Flash and Qwen3.5 35B A3B compared across 53 shared prompts
SpecDeepSeek V4 FlashQwen3.5 35B A3B
Input price$0.14/M tokens$0.25/M tokens
Output price$0.28/M tokens$2/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Feb 2026
At 10M a month$1.40$1.40$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it23 hosts, cheapest first
DeepSeek V4 Flash16 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.01 in·$1.54 out·1M·97.9% up
  • RRelacefp4$0.01 in·$1.28 out·1M·100% up
  • WWafer$0.06 in·$0.17 out·1M·99.9% up
  • SStreamLakefp8$0.08 in·$0.17 out·1M·99% up
  • DDeepInfrafp8$0.09 in·$0.18 out·1M·100% up
  • GGMI Cloudfp8$0.09 in·$0.18 out·1M·99.9% up
10 more hostsFewer hosts
  • DDigitalOcean$0.10 in·$0.20 out·1M·100% up
  • SSiliconFlowfp8$0.13 in·$0.28 out·1M·99.9% up
  • AAtlasCloudfp4$0.14 in·$0.28 out·1M·98.1% up
  • Baidu Qianfanfp8$0.14 in·$0.28 out·1M·97.8% up
  • PParasailfp8$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloudfp8$0.15 in·$0.30 out·1M·100% up
  • MMancerfp8$0.19 in·$0.50 out·1M·95% up
  • Azure AI Foundry$0.21 in·$0.56 out·1M·99.4% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·384k·98.7% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.10 in·$0.19 out·1M·92.6% 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 V4 Flash and Qwen3.5 35B A3B?

DeepSeek V4 Flash is developed by DeepSeek while Qwen3.5 35B A3B is developed by Qwen. DeepSeek V4 Flash has a 1.0M token context window vs Qwen3.5 35B A3B's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash or Qwen3.5 35B A3B?

It depends on your use case. DeepSeek V4 Flash and Qwen3.5 35B A3B 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 V4 Flash cost compared to Qwen3.5 35B A3B?

DeepSeek V4 Flash costs $0.14/M input tokens and Qwen3.5 35B A3B costs $0.25/M input tokens. DeepSeek V4 Flash is $0.11/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 V4 Flash and Qwen3.5 35B A3B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 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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Model pages

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  • Qwen3.5 35B A3B53 outputs, specs and price
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