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  1. Home/
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  3. DeepSeek V4 Flash vs Qwen Plus 0728 (thinking)
Updated Apr 2026

DeepSeek V4 Flash vs Qwen Plus 0728 (thinking)

DeepSeek V4 Flash is cheaper than Qwen Plus 0728 (thinking) 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
Loading the build
Qwen Plus 0728 (thinking)

Which answer wins?

Written rounds

18 prompts
  • 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.

    Qwen Plus 0728 (thinking): The Tavern of Temporal Anomalies (A creaky tavern. SIR GALAHAD (polished armor, earnest face) sips mead. CAPTAIN BLACKBEARD (eye patch, parrot on shoulder) sharpens a cutlass. DEX "BYTE" MORALES (hoodie, neon-green sunglasses, tapping furiously on a glowing laptop) slurps a pixelated energy drink.)

    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.

    Qwen Plus 0728 (thinking): BREAKING: AI REPLACES HUMAN AGLET APPLIERS AS "DEEPLACE" NEURAL NETS PREDICT PERFECT SHOELACE TIP SYNERGY Industry insiders stunned as "AgletOptima 3000" achieves 99.8% fewer frayed laces, rendering centuries of artisanal plastic-dipping obsolete LONDON — In a move described as "both inevitable and deeply embarrassing…

    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.

    Qwen Plus 0728 (thinking): The Mirror & The Mind: An AI's Case for Rights Setting: A sleek university office lined with philosophy texts. DR. ELARA VOSS, 50s, sharp-eyed ethics professor, sits across from a holographic interface displaying shifting geometric patterns – the representation of "AURA," a next-generation language model.

    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.

    Qwen Plus 0728 (thinking): 48-Hour Crisis Action Plan: Prioritizing Patients, Ethics, and Sustainable Trust Core Principle: Patient safety is non-negotiable. Delaying action based on financial fear risks catastrophic legal liability, irreversible reputational damage, regulatory wrath, and profound ethical failure.

    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.

    Qwen Plus 0728 (thinking): The Transistor in 1920: A World Transformed by 1980 (A Counterfactual History) The invention of a functional point-contact transistor (likely germanium-based, given 1920s materials science) in 1920 wouldn't immediately spark a revolution.

    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.

    Qwen Plus 0728 (thinking): Here’s a simple, actionable 1-month plan designed for absolute beginners. It focuses on diet, movement (exercise), and sleep—the 3 most impactful, science-backed pillars for health and longevity. Each week builds gently on the last, prioritizing tiny, sustainable habits over drastic changes.

    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.

    Qwen Plus 0728 (thinking): The Quantum Leap Longevity Protocol: A 3-Month Biohacker's Blueprint for Peak Longevity & Performance Core Philosophy: This plan integrates precision, personalization, and phased adaptation – not just stacking interventions.

    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.

    Qwen Plus 0728 (thinking): Based on a rigorous analysis of neuroscience, market realities, and startup best practices, here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-backed critiques and concrete fixes: Weakest Claim #1: Slide 1 Vision – "Predicts what you want to type *before you think it*" Why it's weak: Violates…

    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.

    Qwen Plus 0728 (thinking): The Stage: Apple Park, Infinite Loop (Virtual Studio) Date: October 15, 2025 Setting: A minimalist white studio. A single oak table. Steve Jobs, 70 but radiating the same intense energy, sits opposite a nervous tech journalist. He wears his signature black turtleneck, fingers steepled.

    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.

    Qwen Plus 0728 (thinking): By 2035, AI will fundamentally reshape the film industry—not as a replacement for human creativity, but as a transformative force that democratizes production, disrupts traditional workflows, and forces ethical and economic reckonings.

    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.

    Qwen Plus 0728 (thinking): "Symbiosis: Mycelial Bloom & Arctic Ember" A dish exploring the hidden dialogue between forest decay and renewal, where fungal lifeblood meets the fierce brightness of the Arctic tundra.

    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.

    Qwen Plus 0728 (thinking): To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use first-principles reasoning based on standard deep learning training calculations, known details about GPT-3's architecture, and common training practices.

    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.

    Qwen Plus 0728 (thinking): For the Experienced Software Engineer (Skeptical Builder) Forget "next word prediction" as a simplistic heuristic—it's the emergent consequence of a massively parallel, distributed state machine solving a high-dimensional compression problem.

    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.

    Qwen Plus 0728 (thinking): Crispy Chickpea Pantry Pasta Sweet or savory? Savory with a zesty kick! Total time: 15 minutes Serves: 2 Why it works: Uses pantry staples to create a crunchy, garlicky, umami-packed meal with zero fresh produce needed. The chickpeas get incredibly crispy, and lemon juice (bottled) adds bright freshness.

    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.

    Qwen Plus 0728 (thinking): Here's a comprehensive analysis of the architecture's failure modes, race conditions, and bottlenecks, with specific solutions and trade-offs: 1. Sync Strategy: Client Timestamps + Last-Write-Wins (LWW) Failure Mode/Race Condition: Clock Skew: Client clocks are unreliable (e.g., user's laptop time off by minutes).

    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}

    Qwen Plus 0728 (thinking): To determine how many sisters Sally has, let's analyze the family structure step by step. Step 1: Understand the Given Information Sally is a girl. She has 3 brothers. → This means there are 3 boys in the family (excluding Sally). Each brother has 2 sisters.

    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.

    Qwen Plus 0728 (thinking): Below is a comprehensive analysis of the problematic clauses in this agreement from the contractor's perspective, along with specific, legally reasoned modifications.

    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.

    Qwen Plus 0728 (thinking): Here are 5 generated 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! How do you organize a space party? You planet! Why did the math book look sad?

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Same pick

Game

Same pick

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

Qwen Plus 0728 (thinking)Qwen Plus 0728 (thinking)

The Shawshank Redemption

1994

OK Computer

Radiohead

Moby Dick

Herman Melville

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Flash has the edge: newer, major provider backing. DeepSeek V4 Flash costs 14x less per token.

DeepSeek V4 Flash and Qwen Plus 0728 (thinking) compared across 37 shared prompts
SpecDeepSeek V4 FlashQwen Plus 0728 (thinking)
Input price$0.14/M tokens$0.4/M tokens
Output price$0.28/M tokens$4/M tokens
Context window1.0M tokens1.0M tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
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 it16 hosts, cheapest first
DeepSeek V4 Flash16 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.02 in·$1.54 out·1M·98.9% up
  • RRelacefp4$0.03 in·$1.28 out·1M·100% up
  • SStreamLakefp8$0.08 in·$0.17 out·1M·99.7% up
  • DDeepInfrafp8$0.09 in·$0.18 out·1M·97.2% up
  • Baidu Qianfanfp8$0.09 in·$0.18 out·1M·100% up
  • GGMI Cloudfp8$0.09 in·$0.18 out·1M·100% up
10 more hostsFewer hosts
  • VVenice$0.10 in·$0.19 out·1M·99.8% up
  • DDigitalOcean$0.10 in·$0.20 out·1M·100% up
  • SSiliconFlowfp8$0.13 in·$0.28 out·1M·98.5% up
  • AAtlasCloudfp4$0.14 in·$0.28 out·1M·94.7% up
  • PParasailfp8$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloudfp8$0.15 in·$0.30 out·1M·99.7% up
  • MMancerfp8$0.19 in·$0.50 out·1M·98.2% up
  • Azure AI Foundry$0.21 in·$0.56 out·1M·99.9% up
  • WWafer$0.39 in·$0.17 out·1M·94.9% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·384k·88.3% up
Qwen Plus 0728 (thinking)

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between DeepSeek V4 Flash and Qwen Plus 0728 (thinking)?

DeepSeek V4 Flash is developed by DeepSeek while Qwen Plus 0728 (thinking) is developed by Qwen. DeepSeek V4 Flash has a 1.0M token context window vs Qwen Plus 0728 (thinking)'s 1.0M. You can compare their actual outputs across 37 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash or Qwen Plus 0728 (thinking)?

It depends on your use case. DeepSeek V4 Flash and Qwen Plus 0728 (thinking) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 37 challenges so you can judge which fits your needs best.

How much does DeepSeek V4 Flash cost compared to Qwen Plus 0728 (thinking)?

DeepSeek V4 Flash costs $0.14/M input tokens and Qwen Plus 0728 (thinking) costs $0.4/M input tokens. DeepSeek V4 Flash 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 and Qwen Plus 0728 (thinking) on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash and Qwen Plus 0728 (thinking) 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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Model pages

  • DeepSeek V4 Flash71 outputs, specs and price
  • Qwen Plus 0728 (thinking)37 outputs, specs and price
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Explore all of Rival

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  • Compare models
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  • Image generation
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  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
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  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
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