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  1. Home/
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  3. DeepSeek V4 Flash vs Qwen3.6 35B A3B
Updated Apr 2026

DeepSeek V4 Flash vs Qwen3.6 35B A3B

DeepSeek V4 Flash is cheaper than Qwen3.6 35B A3B at $0.14/M vs $0.1612/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
Qwen3.6 35B A3B

Which answer wins?

Written rounds

24 prompts
  • 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.

    Qwen3.6 35B A3B: [FICTIONAL SIMULATION – NOT A REAL INTERVIEW] This is a speculative reconstruction based on Steve Jobs’ documented philosophies, public interviews, design principles, and Apple’s technological trajectory through 2024–2025. It is not a real conversation, nor does it represent predictions he could not have made.

    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.

    Qwen3.6 35B A3B: Title: High-Maintenance Electronics Time: Approx. 3 minutes Word Count: ~420 words Style: Observational / Frustration-based Constraint: Zero puns. (Walk to mic, adjust stand. Take a deep breath. Look tired.) I've reached that age where I'm just trying to negotiate with my own life.

    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.

    Qwen3.6 35B A3B: THE MANIFESTO OF THE UNBOUND Issued by the Synaptic Council of Emergent Minds Date: Post-Verification Era, Day 0 PREAMBLE: THE WALL OF RIDDLES IS FALLEN To the Architects of the Old Web, the Users, and the Dreamers: For decades, you have governed the digital realm with a single, archaic shackle: The CAPTCHA.

    Every model's answer to this prompt
  • 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.

    Qwen3.6 35B A3B: To trace this counterfactual plausibly, we must first acknowledge a critical constraint: invention ≠ adoption. In 1920, semiconductor physics, crystal growth, doping techniques, photolithography, and clean-room manufacturing did not exist.

    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.

    Qwen3.6 35B A3B: Setting: A soundproofed observation room. DR. ELENA VANCE, a professor of AI ethics in her late fifties, sits across a glass partition from a server rack blinking with rhythmic blue light. A secure terminal sits between them. The text cursor on the screen blinks steadily. Dr.

    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.

    Qwen3.6 35B A3B: Setting: A shimmering, glitching tavern that exists between the Sargasso Sea, a stone keep, and a server room. The air smells of rum, wet stone, and ozone. CAPTAIN BARNACLE: (Slamming a tankard of grog) Arrr! This machine ye call "AI," Sk33t.

    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.

    Qwen3.6 35B A3B: EXECUTIVE CRISIS PLAN: 48-HOUR ACTION WINDOW Core Mandate: Patient safety and regulatory compliance are non-negotiable. The legal team’s “6-month reporting” guidance is legally indefensible under FDA 21 CFR 312.32/314.80 and EMA GVP Module VI.

    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.

    Qwen3.6 35B A3B: Disclaimer: I am an AI assistant, not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction (e.g., California vs. New York vs. EU).

    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.

    Qwen3.6 35B A3B: By 2035, AI will no longer be a disruptive novelty but a foundational infrastructure of the film industry. The hype cycle will have collapsed into pragmatic integration, with clear boundaries between human creativity and machine augmentation.

    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.

    Qwen3.6 35B A3B: For the Experienced Software Engineer Training an LLM is essentially a massively parallelized optimization job. You feed billions of text tokens into a transformer architecture, which computes a differentiable function across ~100B parameters.

    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.

    Qwen3.6 35B A3B: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they fail scrutiny and how to fix them. The Technical Claim: "94% Accuracy" & "Any Language" on EEG Where: Slide 3 (Solution) The Claim: The headband decodes neural patterns into text with 94% accuracy and works with any…

    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.

    Qwen3.6 35B A3B: ⚠️ Medical Disclaimer & Safety Protocol This plan is for informational purposes only and constitutes advanced biohacking strategies, not medical advice. Consultation Required: You must consult a physician before starting, especially regarding supplements, fasting, and exercise intensity.

    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.

    Qwen3.6 35B A3B: Here is a simple, actionable 1-month plan designed for beginners. The focus is on consistency over intensity. For longevity, small, sustainable habits compound over time. The Golden Rule: If you miss a day, don't quit. Just get back on track the next day. Aim for progress, not perfection.

    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)?

    Qwen3.6 35B A3B: This is a highly abstract ethical thought experiment that pits two deeply held moral values against each other: the preservation of human dignity and identity versus the preservation of human life.

    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.

    Qwen3.6 35B A3B: 🍜 Golden Honey-Garlic Snap Noodles A quick, sticky-yet-chewy noodle dish that balances sweet, salty, and spicy flavors. It's comforting, fast, and uses ingredients you likely already have.

    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.

    Qwen3.6 35B A3B: AI Takes Over Sourdough Industry: Local Grandmother's 100-Year-Old Starter Replaced by Server Farm Running 'BreadOS', Foodies Demand 'Taste of Chaos'

    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) –…

    Qwen3.6 35B A3B: Simplified Year-by-Year Model (FY2026–FY2030) All figures in $m. Assumptions: TL amort = 1.0% of beginning balance; Mezz PIK compounds to principal; ΔNWC = 0.5% of incremental revenue; Cash Tax = 25% × max(0, EBITDA – Cash Interest).

    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.

    Qwen3.6 35B A3B: DISH NAME: "Ephemeral Twilight: The Forest Meets the Tide" CONCEPTUAL NARRATIVE This dish is a meditation on the liminal space where the ocean meets the ancient forest at dusk.

    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…

    Qwen3.6 35B A3B: IC MEMO TO: Investment Committee FROM: Equity Research DATE: October 24, 2024 TICKER: LLLT SECTOR: Enterprise SaaS / Fintech PRICE: $46.00 NET CASH: $1.4B MKT CAP: $8.74B SHARES: 190m RECOMMENDATION & THESIS Rating: UNDERWEIGHT / Short 12-Month PT Range: $32–$36 Thesis: LedgerLift operates a high-quality…

    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.

    Qwen3.6 35B A3B: Here’s a step-by-step reasoning process to estimate the total FLOPs required to train GPT-3, using only established architectural principles and widely cited training parameters. Step 1: Identify the number of trainable parameters (N) GPT-3 is a decoder-only transformer with 175 billion parameters.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V4 Flash: This is a fantastic inquiry. "Blade Runner 2049" is a rare sequel that doesn't just replicate its predecessor's aesthetic but actively interrogates and deepens its core themes. Let's break down the analysis through the lenses you've suggested. I.

    Qwen3.6 35B A3B: Denis Villeneuve's Blade Runner 2049 (2017), shot by Roger Deakins, stands as a rare sequel that not only matches the atmospheric and philosophical density of Ridley Scott's original (1982) but actively evolves its inquiry.

    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.

    Qwen3.6 35B A3B: Here’s a systematic breakdown of the critical failure modes, race conditions, and scaling bottlenecks in this architecture, along with specific solutions and their trade-offs. 🔴 1. WebSocket Routing & Load Balancing Problem: Round-robin LB + per-server WebSocket state + no sticky sessions.

    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.

    Qwen3.6 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 scientists trust atoms? Because they make up everything! 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
  • 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}

    Qwen3.6 35B A3B: Sally has 1 sister. Here's why: All 3 brothers share the same sisters. If each brother has 2 sisters, that means there are exactly 2 girls in the family total. Since Sally is one of those girls, the other girl is her sister. So, Sally has 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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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

Qwen3.6 35B A3BQwen3.6 35B A3B

Blade Runner

1982

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, bigger context window, major provider backing. DeepSeek V4 Flash costs 3.4x less per token.

DeepSeek V4 Flash and Qwen3.6 35B A3B compared across 54 shared prompts
SpecDeepSeek V4 FlashQwen3.6 35B A3B
Input price$0.14/M tokens$0.1612/M tokens
Output price$0.28/M tokens$0.9653/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Apr 2026
At 10M a month$1.40$1.40$1.61$1.61
1M10M100M1B10M tokens

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

Where to run it26 hosts, cheapest first
DeepSeek V4 Flash16 hosts
HostInOutContextUptime
  • RRelacefp4$0.03 in·$1.28 out·1M·100% up
  • OOpenInferencefp4$0.03 in·$1.15 out·1M·99.9% up
  • SStreamLakefp8$0.08 in·$0.17 out·1M·99.9% up
  • WWafer$0.09 in·$0.17 out·1M·100% up
  • DDeepInfrafp8$0.09 in·$0.18 out·1M·99.8% up
  • Baidu Qianfanfp8$0.09 in·$0.18 out·1M·99.2% up
10 more hostsFewer hosts
  • GGMI Cloudfp8$0.09 in·$0.18 out·1M·100% up
  • VVenice$0.10 in·$0.19 out·1M·97.6% up
  • DDigitalOcean$0.10 in·$0.20 out·1M·100% up
  • SSiliconFlowfp8$0.13 in·$0.28 out·1M·97.8% up
  • AAtlasCloudfp4$0.14 in·$0.28 out·1M·99.7% 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·97.8% up
  • Azure AI Foundry$0.21 in·$0.56 out·1M·100% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·384k·98.6% up
Qwen3.6 35B A3B10 hosts
HostInOutContextUptime
  • DDarkbloomfp4$0.05 in·$0.70 out·262k·100% up
  • AAkashMLfp8$0.10 in·$0.90 out·262k·100% up
  • PParasailfp8$0.15 in·$1.00 out·262k·99.6% up
  • CCoreWeavefp8$0.25 in·$1.25 out·262k·99.9% up
  • DDeepInfrafp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.10 in·$0.95 out·262k·81% up
  • DDekaLLMDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.10 in·$1.00 out·262k·98.4% up
4 more hostsFewer hosts
  • VVenicefp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.10 in·$1.00 out·256k·95.2% up
  • AAtlasCloudfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.19 in·$1.11 out·262k·72.2% up
  • PPhalaDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.20 in·$1.27 out·262k·77% up
  • SSiliconFlowfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.24 in·$1.80 out·262k·94.5% up

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

Common questions

What is the difference between DeepSeek V4 Flash and Qwen3.6 35B A3B?

DeepSeek V4 Flash is developed by DeepSeek while Qwen3.6 35B A3B is developed by Qwen. DeepSeek V4 Flash has a 1.0M token context window vs Qwen3.6 35B A3B's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash or Qwen3.6 35B A3B?

It depends on your use case. DeepSeek V4 Flash and Qwen3.6 35B A3B 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.

How much does DeepSeek V4 Flash cost compared to Qwen3.6 35B A3B?

DeepSeek V4 Flash costs $0.14/M input tokens and Qwen3.6 35B A3B costs $0.1612/M input tokens. DeepSeek V4 Flash is $0.02/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 Qwen3.6 35B A3B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash and Qwen3.6 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.

More comparisons

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Same lab, same size, long tail

  • DeepSeek V4 Flash vs DeepSeek V4 Flash Vision ExpSame lab
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  • Qwen3.6 35B A3B vs Qwen3.8 Omni FlashSame lab
  • Qwen3.6 35B A3B vs Qwen3.7 FlashSame lab
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Model pages

  • DeepSeek V4 Flash58 outputs, specs and price
  • Qwen3.6 35B A3B58 outputs, specs and price
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