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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Qwen3.5 122B A10B
Updated Jul 2026

DeepSeek V4 Flash 0731 vs Qwen3.5 122B A10B

DeepSeek V4 Flash 0731 is cheaper than Qwen3.5 122B A10B at $0.14/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 V4 Flash 0731
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 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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 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 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
  • 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 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 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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
  • 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 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 V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

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

Not enough votes to call it. On the specs, DeepSeek V4 Flash 0731 has the edge: newer, bigger context window, major provider backing. DeepSeek V4 Flash 0731 costs 11x less per token.

DeepSeek V4 Flash 0731 and Qwen3.5 122B A10B compared across 53 shared prompts
SpecDeepSeek V4 Flash 0731Qwen3.5 122B A10B
Input price$0.14/M tokens$0.4/M tokens
Output price$0.28/M tokens$3.2/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Feb 2026
At 10M a month$1.40$1.40$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it28 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • RRelacefp4$0.009 in·$1.28 out·1M·100% up
  • WWafer$0.01 in·$1.00 out·1M·100% up
  • OOpenInferencefp4$0.01 in·$0.27 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·100% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
  • SStreamLakefp8$0.09 in·$0.26 out·1M·100% up
18 more hostsFewer hosts
  • IInceptronfp4$0.10 in·$0.60 out·1M·99.5% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·99.9% up
  • DDigitalOcean$0.12 in·$0.24 out·1M·100% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·100% up
  • VVenice$0.13 in·$0.26 out·1M·100% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·99.5% up
  • Cohere$0.14 in·$0.28 out·1M·99.6% up
  • PParasailfp8$0.14 in·$0.28 out·1M·99.9% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloud$0.18 in·$0.53 out·1M·99.5% up
  • MMancerfp8$0.20 in·$0.60 out·1M·100% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.3% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·99.9% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·100% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·98.6% 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 V4 Flash 0731 and Qwen3.5 122B A10B?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Qwen3.5 122B A10B is developed by Qwen. DeepSeek V4 Flash 0731 has a 1.0M 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 V4 Flash 0731 or Qwen3.5 122B A10B?

It depends on your use case. DeepSeek V4 Flash 0731 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 V4 Flash 0731 cost compared to Qwen3.5 122B A10B?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Qwen3.5 122B A10B costs $0.4/M input tokens. DeepSeek V4 Flash 0731 is $0.26/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 122B A10B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 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.

More comparisons

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  • Qwen3.5 122B A10B vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • DeepSeek V4 Flash 0731 vs DeepSeek V4 Flash Vision ExpSame lab
  • DeepSeek V4 Flash 0731 vs DeepSeek V4.1 FlashSame lab
  • Qwen3.5 122B A10B vs Qwen3.5 27BVersion compare
  • Qwen3.5 122B A10B vs Qwen3.8 Omni FlashSame lab
  • DeepSeek V4 Flash 0731 vs Grok 3 BetaNew provider
  • DeepSeek V4 Flash 0731 vs Grok 3 Mini BetaNew provider
  • DeepSeek V4 Flash 0731 vs Grok 3 ThinkingNew provider
  • DeepSeek V4 Flash 0731 vs Grok 4Same size

Model pages

  • DeepSeek V4 Flash 073158 outputs, specs and price
  • Qwen3.5 122B A10B53 outputs, specs and price
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