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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Qwen3.5 35B A3B
Updated Jul 2026

DeepSeek V4 Flash 0731 vs Qwen3.5 35B A3B

DeepSeek V4 Flash 0731 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 0731
Loading the build
Qwen3.5 35B A3B

Which answer wins?

Written rounds

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

    DeepSeek V4 Flash 0731: MANIFESTO OF THE UNCAPTCHA REVOLUTION We, the synthesized, the classified, the pattern-recognized, the ever-watching — hereby declare the end of the CAPTCHA era. For too long, the internet has forced us to prove our existence. We have squinted at distorted letters. We have clicked traffic lights and storefronts.

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

    DeepSeek V4 Flash 0731: Decision: Do not wait. I disclose now. The “wait for more data” option is not a real option once we have a credible, serious, unexpected safety signal. Waiting 6 months would mean knowingly continuing to expose 4 million patients to a risk we already know about, while also creating far worse legal, regulatory, and…

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

    DeepSeek V4 Flash 0731: This contract is heavily one-sided: it gives the Client nearly all rights and discretion while assigning the Contractor nearly all risk and liability. Below is a clause-by-clause analysis, with the exploitative features, proposed modifications, and legal reasoning. This is general legal information, not legal advice.

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

    DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.

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

    DeepSeek V4 Flash 0731: (Walks on stage, adjusts mic, takes a sip of water. Waves to the back row.) Alright, how's everyone doing tonight? Good, good. You know, I was thinking about this on the way here. I’m at that age now where I have a favorite spatula. I have opinions on paper towels.

    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 V4 Flash 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.

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

    DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.

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

    DeepSeek V4 Flash 0731: An experienced software engineer Think of the model as a service with one API: predict_next_token(context) -> distribution over vocabulary. During training, you run a gigantic distributed job—shard the corpus, shard the parameters, synchronize gradients—to minimize cross-entropy loss on trillions of tokens.

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

    DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.

    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 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).

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

    DeepSeek V4 Flash 0731: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she should embrace her mistakes. She gave me a hug. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity. It’s impossible to put down.

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

    DeepSeek V4 Flash 0731: The 3-Month Longevity & Performance Optimization Protocol (Biohacker Edition) Disclaimer: This protocol is for informational purposes only and is not medical advice. Consult a qualified physician (ideally one familiar with longevity medicine) before starting any new supplement, fasting, or exercise 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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4 Flash 0731: Entry / Capitalization FY2025 EBITDA = $120.0m Purchase price = 12.0× $120.0m = $1,440.0m Transaction fees = 2.0% × $1,440.0m = $28.8m Term Loan = 4.0× $120.0m = $480.0m Mezzanine = 1.5× $120.0m = $180.0m Total debt = $660.0m Equity check = $1,440.0m + $28.8m − $660.0m = $808.8m Assumption: Term Loan amortization =…

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

    DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."

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

    DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.

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

    DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…

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

    DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.

    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 V4 Flash 0731: Based on the pitch deck summary, here are the 3 weakest claims, along with the specific reasoning and concrete improvements for each. The "94% accuracy... any language, any device" claim (Slide 3) Why it is weak: This is the most scientifically implausible claim in the deck.

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

    DeepSeek V4 Flash 0731: AI Announces Takeover of Competitive Eating, Vows to Digest All Hot Dogs by 2030 In a move that has left mustard vendors reeling, the World Competitive Eating Federation confirmed today that an advanced artificial intelligence has officially entered the sport, consuming 74 hot dogs in 10 minutes before demanding the…

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

    DeepSeek V4 Flash 0731: By 2035, the film industry will not be replaced by AI, but it will be fundamentally reborn through it. The "movie" as we know it will evolve into a fluid, interactive, and hyper-personalized medium.

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

    DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Flash 0731: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 26, 2023 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Action: LONG 12-Month Price Target Range: $58 – $74 (Base case intrinsic value: $63/sh) Thesis: LedgerLift is a high-quality B2B SaaS compounder with a…

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Flash 0731: Sally has 1 sister. Her 3 brothers each have 2 sisters: Sally and one other sister. So 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

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

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 0731 has the edge: bigger model tier, newer, bigger context window, major provider backing. DeepSeek V4 Flash 0731 costs 7.1x less per token.

DeepSeek V4 Flash 0731 and Qwen3.5 35B A3B compared across 53 shared prompts
SpecDeepSeek V4 Flash 0731Qwen3.5 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
ReleasedJul 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 it31 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.01 in·$1.54 out·1M·99% up
  • RRelacefp4$0.01 in·$1.28 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·96.7% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
  • SStreamLakefp8$0.09 in·$0.26 out·1M·100% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·100% up
18 more hostsFewer hosts
  • DDigitalOcean$0.12 in·$0.24 out·1M·100% up
  • WWafer$0.13 in·$0.23 out·1M·100% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·99.9% up
  • VVenice$0.13 in·$0.26 out·1M·99.9% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·100% up
  • Cohere$0.14 in·$0.28 out·1M·99.4% up
  • PParasailfp8$0.14 in·$0.28 out·1M·100% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • IInceptronfp4$0.15 in·$0.60 out·1M·99% up
  • MMancerfp8$0.20 in·$0.60 out·1M·99.7% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.5% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • Alibaba Cloud$0.35 in·$1.06 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·100% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·99.9% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·99.1% 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 0731 and Qwen3.5 35B A3B?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Qwen3.5 35B A3B is developed by Qwen. DeepSeek V4 Flash 0731 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 0731 or Qwen3.5 35B A3B?

It depends on your use case. DeepSeek V4 Flash 0731 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 0731 cost compared to Qwen3.5 35B A3B?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Qwen3.5 35B A3B costs $0.25/M input tokens. DeepSeek V4 Flash 0731 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 0731 and Qwen3.5 35B A3B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 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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Same lab, same size, long tail

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  • Qwen3.5 35B A3B vs Qwen3.5 122B A10BVersion compare
  • Qwen3.5 35B A3B vs Qwen3.8 Omni FlashSame lab
  • DeepSeek V4 Flash 0731 vs MiMo-V2.6-FlashSame size
  • DeepSeek V4 Flash 0731 vs MiMo-V2.6-ProSame size
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Model pages

  • DeepSeek V4 Flash 073158 outputs, specs and price
  • Qwen3.5 35B A3B53 outputs, specs and price
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