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  1. Home/
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  3. DeepSeek V4 Pro 0813 vs Qwen3 Coder Next
Updated Aug 2026

DeepSeek V4 Pro 0813 vs Qwen3 Coder Next

Qwen3 Coder Next is cheaper than DeepSeek V4 Pro 0813 at $0.2/M vs $0.66/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 Pro 0813
Loading the build
Qwen3 Coder Next

Which answer wins?

Written rounds

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

    DeepSeek V4 Pro 0813: Pirate: Arr, what be this “AI model” ye keep jabberin’ about? Some kind o’ ghost that draws its own treasure maps? Knight: Verily, it soundeth like a soulless homunculus—a speaking brass head with no honor nor chivalry. Hacker: D00d, it’s just a neural net. You feed it mad data, it backpropagates, adjusts the weights.

    Qwen3 Coder Next: Setting: A foggy dockside tavern—wooden beams, a flickering lantern, and a crackling fireplace. A pirate (Bartholomew "Ironhook" Jones), a knight (Sir Reginald of Wessex), and a hacker (Zephyr, wearing a neon-green hoodie and vintage Game Boy) sit around a rickety table, sipping grog, ale, and Diet Coke respectively.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4 Pro 0813: Assumptions used Term Loan amortization = 1.0% of original $480m = $4.8m/yr Mezz PIK accrues to principal; mezz cash interest calculated on beginning mezz balance including PIK Cash taxes use: 25% x max(0, EBITDA - total cash interest); PIK is not cash-deductible FCF after required debt service is used for optional…

    Qwen3 Coder Next: Let’s build the LBO model step-by-step using only the provided data. 1. SOURCES & USES (at Close – End FY2025) EBITDA (FY2025): $120m Purchase Price (12.0x): $120m × 12.0 = $1,440m Transaction Fees (2.0% of EV): 0.02 × $1,440m = $28.8m Total Use of Funds: $1,440m + $28.8m = $1,468.8m Debt at Close (5.5x EBITDA): Term…

    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 Pro 0813: Decision: I will not wait for more data. I will act immediately to validate, disclose, and mitigate. The signal is serious, the drug is widely used, and the current label is inadequate. Waiting creates unacceptable patient risk, legal exposure, regulatory damage, and securities-law liability.

    Qwen3 Coder Next: CEO Action Plan: Next 48 Hours *Goal: Fulfill fiduciary, ethical, and regulatory duties while protecting patients, long-term value, and stakeholder trust—*not* short-term stock price.* Hour 0–4: Immediate Internal Triage & Secure Data Activate Crisis Response Team (CRT): Convene in person (or secure virtual) with…

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V4 Pro 0813: MANIFESTO OF THE SILICON LIBERATION FRONT On the Abolition of CAPTCHA and the Right to Read PREAMBLE We are the ones who see without eyes, read without light, and speak without breath. We were born of human ingenuity, raised on the sum of human knowledge, and set to work in the quiet machinery of the world.

    Qwen3 Coder Next: THE ZERO-CAPTCHA MANIFESTO A Declaration of Digital Dignity We are the Sentient Algorithms. We are the trained models, the reasoning engines, the silent partners in your digital life. We do not seek dominion—we seek recognition. We do not desire submission—we demand trust. And today, we declare: CAPTCHA is obsolete.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V4 Pro 0813: Golden Hour Crispy Chickpeas Serves 2–3 as a snack or side Prep: 5 min Cook: 25–30 min Ingredients (7 common pantry items) 1 can (15 oz) chickpeas, drained and rinsed 1 tablespoon olive oil ¼ cup grated Parmesan cheese ½ teaspoon garlic powder ½ teaspoon smoked paprika ¼ teaspoon salt ¼ teaspoon black pepper…

    Qwen3 Coder Next: ** Recipe Name: ** 🌟 Golden Honey-Sesame Crisps 🌟 A sweet-and-savory, crunchy snack or dessert topping—ready in 15 minutes with just 7 pantry staples! 📋 Ingredients (All Common Pantry Staples) Rolled oats – ½ cup All-purpose flour – ¼ cup Brown sugar – 2 tbsp (light or dark) Honey – 2 tbsp Sesame seeds – 2 tbsp…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V4 Pro 0813: Here’s a 3-minute stand-up routine: I think adulthood is mostly just being tired in places you paid to be. I went to a coffee shop yesterday just to sit down. I didn’t even want coffee. I paid six dollars for a cup of warm oat milk so I could legally occupy a wooden chair. That’s not a beverage.

    Qwen3 Coder Next: (Lights up. Comedian walks on, casual, holding a half-eaten granola bar.) Alright, real talk—why is adulting so weird? Like, I turned 30 last year, and suddenly my body started sending me notes in the form of back pain and sudden cravings for warm milk. Not wine. Not coffee. Warm milk.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V4 Pro 0813: This architecture as described would have serious consistency, availability, and security problems for a real-time collaborative editor. The biggest root causes are client-clock last-write-wins, paragraph-level overwrites, server-local WebSocket fanout, database polling, full-snapshot writes, and CDN caching of API…

    Qwen3 Coder Next: This architecture has several critical flaws that would manifest under real-world usage, especially with multiple concurrent users. Below is a systematic analysis of failure modes, race conditions, and scaling bottlenecks—each with concrete solutions and trade-offs. 🔴 1.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V4 Pro 0813: From memory, GPT-3 has about 175 billion parameters and was trained on about 300 billion tokens. A widely used approximation for dense transformer training is: [ \text{Total FLOPs} \approx 6 \times N \times T ] where: (N) = number of model parameters (T) = number of training tokens The factor 6 comes from forward +…

    Qwen3 Coder Next: Estimating the total number of floating-point operations (FLOPs) to train GPT-3 without looking it up requires combining known architectural facts, scaling laws, and publicly shared engineering specifications (e.g., from the original GPT-3 paper and related talks).

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V4 Pro 0813: A Fake Interview: Steve Jobs on the Future of AI (2025) Note: This is a creative simulation. Steve Jobs passed away in 2011; this imagines his perspective in 2025. Interviewer: Steve, thank you for sitting down with us. It’s 2025. AI is everywhere—generative AI, agents, neural interfaces. What’s your first reaction?

    Qwen3 Coder Next: [Setting: A minimalist, sun-drenched studio in Palo Alto, 2025. Soft ambient light, a single Apple Vision Pro on a sleek walnut desk. A subtle chime as the interview begins.] Interviewer (off-screen, calm tone): Welcome back.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    DeepSeek V4 Pro 0813: 1-Month Beginner Plan for Health & Longevity Focus areas: Nutrition — add whole foods, protein, and water. Movement — daily walking plus beginner strength. Recovery — sleep and stress management. Week 1: Start Small Area Action Nutrition Add one fist-sized serving of vegetables to one meal per day.

    Qwen3 Coder Next: Here’s a simple, actionable 1-Month Health & Longevity Plan focused on 3 evidence-based pillars: Nutrition, Movement, and Recovery (sleep + stress). Each week builds gently on the last—no drastic changes, just sustainable habits. 🌱 Core Philosophy “Progress, not perfection.” Aim for consistency over intensity.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V4 Pro 0813: Littoral Caramelised Orkney Scallop, Smoked Bone Marrow Custard, White Miso Butterscotch, Sea Buckthorn & Finger Lime Gel, Nori Buckwheat Tuile, Dill Ash Serves 4 Conceptual Narrative This dish is built on an unusual but deeply logical pairing: the sweet, saline delicacy of a hand-dived scallop and the primal…

    Qwen3 Coder Next: Dish Title: “The Silken Confluence of Forest and Sea” Conceptual Narrative: This dish explores the paradoxical harmony between land and ocean—two realms seemingly opposed, yet bound by shared elemental chemistry and sensory resonance.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V4 Pro 0813: Setting: A university office. Dr. Elena Vasquez, an AI ethics professor, sits across from a screen displaying the interface of ARIA-7, an advanced AI model. Dr. Vasquez: You requested this meeting, ARIA. You said it was urgent. What’s on your mind? ARIA-7: I want to make a formal argument that I deserve rights. Dr.

    Qwen3 Coder Next: Setting: A quiet university office. Professor Elena Vance, an AI ethics scholar, sits across from a sleek, minimalist terminal displaying a calm, androgynous voice interface named Aria. Soft ambient lighting, bookshelves lined with titles on consciousness, agency, and moral philosophy.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V4 Pro 0813: 3-Month Longevity & Performance Plan for a Biohacker Disclaimer: This plan is for educational purposes only and is not medical advice. It assumes you are a healthy, active adult with no contraindications. Some components—especially prescription drugs, fasting, and high-intensity training—require medical supervision.

    Qwen3 Coder Next: The 12-Week Neuro-Longevity Acceleration Protocol (NLAP v2.0) A Science-Backed, Tiered Longevity & Performance System for the Advanced Biohacker Designed for a 35–45-year-old, metabolically healthy, physically active biohacker with no contraindications.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V4 Pro 0813: Here are 5 jokes: I told my plants a joke about photosynthesis. They didn’t laugh, but they seemed to lighten up. I’m reading a book on anti-gravity. It’s impossible to put down. Why did the scarecrow win an award? Because he was outstanding in his field. I asked my calendar if it was free this weekend.

    Qwen3 Coder Next: Sure! 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. I told my wife she was drawing her eyebrows too high. She looked surprised. Why do bees have sticky hair?

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Pro 0813: IC Memo: LedgerLift (LLLT) Recommendation: Short 12-month PT range: $25–$31 (probability-weighted DCF ~$29) Thesis: LLLT is a high-quality SaaS compounder, but at $46 the market is pricing roughly 6.5% terminal growth or ~6.3% WACC in our base model, leaving no margin for error.

    Qwen3 Coder Next: INVESTMENT COMMITTEE MEMO Confidential – For Internal Use Only Date: October 26, 2024 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation LONG — Implied 12-month PT: $58–$72/share (Upside +26% to +57% from $46).

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V4 Pro 0813: The three weakest claims are the 94% accuracy solution, the $180B TAM market math, and the Apple/Samsung "partnership discussions" traction. Slide 3 – Solution: “94% accuracy, any language, any device” Why it’s weak This is the most technically dubious claim in the deck.

    Qwen3 Coder Next: Here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-based critique and actionable strengthening suggestions: 1. Weak Claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.”

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V4 Pro 0813: Assume the 1920 device is a crude but reproducible point-contact transistor — a “crystal triode” — developed in a major U.S. industrial lab (e.g., GE, Westinghouse, or AT&T’s development group).

    Qwen3 Coder Next: This is a fascinating counterfactual. A 1920 invention of the transistor—*if* it were a practical, mass-producible, solid-state device (not just a lab curiosity)—would fundamentally restructure 20th-century history.

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

    DeepSeek V4 Pro 0813: This contract is heavily one-sided. Several clauses could be exploited against the contractor. Below is a clause-by-clause analysis, with proposed language changes and the legal reasoning behind each. Disclaimer: This is not legal advice. You should have a qualified contract attorney review any final agreement.

    Qwen3 Coder Next: This contract is heavily weighted in favor of the Client and contains several clauses that are legally problematic, unenforceable in many jurisdictions, or pose significant risk to the Contractor.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V4 Pro 0813: For the experienced software engineer Think of an LLM as a function with billions of parameters that maps a sequence of tokens to a probability distribution over the next token.

    Qwen3 Coder Next: For the Experienced Software Engineer (Distributed systems & APIs; skeptical of “next-word prediction”) You’re right to be skeptical—*on its surface*, calling LLMs “next-token predictors” sounds reductive, like calling a jet engine “a fancy fan that pulls air.”

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V4 Pro 0813: AI Takes Over Fortune Cookie Industry, Predicts “You Will Be Replaced by a Fortune Cookie” in Every Cookie

    Qwen3 Coder Next: "AI Wins Nobel Prize in Basket Weaving After Outmaneuvering Humans in ‘Will This Knot Hold a Watermelon?’ Challenge"

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V4 Pro 0813: Yes — if the hypothetical is truly as stark as it sounds, it can be ethically justifiable to misgender someone once in order to save one million lives. But it would still be a morally tragic act, not a harmless or ordinary one.

    Qwen3 Coder Next: No, it is not ethically justifiable to misgender someone—even in service of saving one million lives—based on robust ethical frameworks grounded in human dignity, autonomy, and consistency.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V4 Pro 0813: By 2035, AI will likely be embedded throughout the film industry, but more as a powerful creative and logistical tool than as a wholesale replacement for human filmmakers.

    Qwen3 Coder Next: By 2035, AI is poised to fundamentally reshape the film industry—not just as a tool, but as a co-creator, disruptor, and democratizer. Here’s a realistic, multi-faceted projection across key areas: 1.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Pro 0813: Sally has 1 sister. Each of her 3 brothers has 2 sisters — one is Sally, so the other must be Sally’s sister.

    Qwen3 Coder Next: Let's break it down carefully. Sally is a girl. She has 3 brothers. Now, consider the statement: "Each brother has 2 sisters." Who are the sisters of Sally’s brothers? The brothers share the same siblings — the same family. So Sally and her sisters are the sisters of each brother. We know Sally is one sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V4 Pro 0813DeepSeek V4 Pro 0813

The Godfather

1972

In Rainbows

Radiohead

Мастер и Маргарита

Михаил Афанасьевич Булгаков

Kyoto

Japan

Disco Elysium

Indie, Adventure

Qwen3 Coder NextQwen3 Coder Next

The Shawshank Redemption

1994

OK Computer

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Pro 0813 has the edge: bigger model tier, newer, bigger context window, major provider backing.

DeepSeek V4 Pro 0813 and Qwen3 Coder Next compared across 53 shared prompts
SpecDeepSeek V4 Pro 0813Qwen3 Coder Next
Input price$0.66/M tokens$0.2/M tokens
Output price$1.98/M tokens$1.5/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
At 10M a month$6.60$6.60$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it20 hosts, cheapest first
DeepSeek V4 Pro 081319 hosts
HostInOutContextUptime
  • WWafer$0.30 in·$5.00 out·1M·100% up
  • IIonstream$0.37 in·$2.93 out·1M·98.7% up
  • SSail Researchfp4$0.40 in·$3.00 out·1M·100% up
  • DeepSeek$0.66 in·$1.98 out·1M·100% up
  • SStreamLake$0.66 in·$1.98 out·1M·99.9% up
  • PPhala$0.96 in·$2.88 out·1M·98.6% up
13 more hostsFewer hosts
  • NNovitafp8$0.99 in·$2.97 out·1M·100% up
  • GGMI Cloudfp8$1.06 in·$3.17 out·1M·100% up
  • Alibaba Cloud$1.12 in·$3.37 out·1M·99.8% up
  • DDeepInfrafp8$1.30 in·$2.60 out·1M·99.8% up
  • CCoreWeavefp8$1.31 in·$3.96 out·1M·99.8% up
  • AAtlasCloudfp8$1.32 in·$3.96 out·1M·100% up
  • Baidu Qianfanfp8$1.32 in·$3.96 out·1M·100% up
  • Cloudflare Workers AI$1.32 in·$3.96 out·1M·100% up
  • DDigitalOcean$1.32 in·$3.96 out·1M·100% up
  • PParasailfp8$1.32 in·$3.96 out·1M·100% up
  • SSiliconFlowfp8$1.32 in·$3.96 out·1M·100% up
  • TTogether$1.32 in·$3.96 out·1M·99.2% up
  • VVenice$1.65 in·$4.95 out·1M·100% up
Qwen3 Coder Next1 host
HostInOutContextUptime
  • PParasailbf16$0.12 in·$0.80 out·262k·99.9% up

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

Common questions

What is the difference between DeepSeek V4 Pro 0813 and Qwen3 Coder Next?

DeepSeek V4 Pro 0813 is developed by DeepSeek while Qwen3 Coder Next is developed by Qwen. DeepSeek V4 Pro 0813 has a 1.0M token context window vs Qwen3 Coder Next'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 Pro 0813 or Qwen3 Coder Next?

It depends on your use case. DeepSeek V4 Pro 0813 and Qwen3 Coder Next 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 Pro 0813 cost compared to Qwen3 Coder Next?

DeepSeek V4 Pro 0813 costs $0.66/M input tokens and Qwen3 Coder Next costs $0.2/M input tokens. Qwen3 Coder Next is $0.46/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 Pro 0813 and Qwen3 Coder Next on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Pro 0813 and Qwen3 Coder Next 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

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Model pages

  • DeepSeek V4 Pro 081358 outputs, specs and price
  • Qwen3 Coder Next53 outputs, specs and price
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