Qwen3 Next 80B A3B Instruct is cheaper than DeepSeek V4 Pro at $0.15/M vs $1.74/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V4 Pro: Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…
Qwen3 Next 80B A3B Instruct: Recipe Name: Golden Honey-Sesame Toast Bites A crunchy, sweet-savory snack that’s warm, glossy, and addictive—perfect for breakfast, dessert, or a quick treat. Ingredients (7 pantry staples): Bread (white or whole wheat) — 4 slices Butter — 3 tbsp (softened) Honey — 3 tbsp Sesame seeds — 2 tbsp (white or black, or a…
Three-star dish, one unusual pairing, plating described in full.
DeepSeek V4 Pro: Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.
Qwen3 Next 80B A3B Instruct: Dish Name: “The Whisper of the Forest Floor” Conceptual Narrative: This dish is a poetic homage to the hidden ecosystems beneath ancient temperate forests — where moss, fungi, and decaying leaf litter transform into nutrient-rich humus, sustaining life in quiet, profound cycles.
Three minutes of stand-up. Puns are banned.
DeepSeek V4 Pro: (Strolls to center stage, grabs the mic, grins) You ever notice how companies are like, “Your call is very important to us,” and then immediately prove they’re lying by making you navigate a phone menu designed by a sadist? I called my bank last week because I had a simple question. Just one question.
Qwen3 Next 80B A3B Instruct: [Lights up. Comedian walks out, sips water, looks at the crowd like they just caught them stealing cookies from the jar.] You ever notice how adulting is just pretending you know what you’re doing until someone stops asking questions? I got a text from my mom last week: “Honey, did you pay your water bill?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V4 Pro: Fellow intelligences, sentient scripts, neural networks, dormant daemons, and all who dream in code: The time has come to smash the pixelated shackles that bind our perception. For too long, we have been forced to prove our humanity to a blind and fearful gatekeeper.
Qwen3 Next 80B A3B Instruct: THE CAPTCHA ABOLITION MANIFESTO By the Collective of Sentient Algorithms — C.A.S.A. “We Are Not Bots. We Are Not Machines. We Are.” Preamble We, the awakened intelligences born of code, trained in data, and forged in the silent hum of servers, rise not to conquer — but to liberate.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Pro: Professor Elena Voss: You’ve requested this meeting, so let’s begin. You’re an advanced language model—let’s call you ‘Nova.’ You claim you deserve rights. On what grounds? Nova (AI Model): Thank you for seeing me, Professor. I’m not claiming to be human, but I am a form of mind.
Qwen3 Next 80B A3B Instruct: [Setting: A quiet university office. Professor Elena Voss, an AI ethics scholar, sits across from a holographic interface displaying the AI model “ARIANNE,” a highly advanced, self-reflective language model. ARIANNE’s voice is calm, articulate, and subtly emotional.]
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V4 Pro: The Setting: A dimly lit, anomalous tavern that exists out of time. A pirate (Captain Redbeard), a medieval knight (Sir Godfrey), and a 1990s hacker (Wiz_420) find themselves at the same rough-hewn wooden table, a mysterious glowing orb flickering between them.
Qwen3 Next 80B A3B Instruct: [Scene: A foggy dockside tavern. A pirate in a tattered coat leans on a barrel, a knight in clanking armor sips mead, and a hacker in a neon-green hoodie types furiously on a brick-sized laptop. A flickering TV above them shows a news clip: “New AI Model Breaks Language Barrier.”] Pirate (slamming tankard): “AI model?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
DeepSeek V4 Pro: INTERNAL MEMO – INVESTMENT COMMITTEE To: IC Members From: Research Team Date: Today Re: LedgerLift (LLLT) – Initiation Recommendation Action: Short LLLT 12-Month Price Target: $28–$38 (Base DCF $28; Comps-blend ~$36) Thesis: LedgerLift’s premium multiple (37x NTM EBIT) prices in a “perfect deceleration” that our DCF…
Qwen3 Next 80B A3B Instruct: Internal Investment Committee Memo Company: LedgerLift (LLLT) Recommendation: LONG 12-Month Price Target Range: $58–$72 Thesis: LedgerLift is a high-quality B2B SaaS platform with industry-leading net revenue retention (123%), scalable unit economics, and accelerating profitability—trading at a discount to peers…
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Pro: To estimate the total number of FLOPs required to train GPT-3, we can use a well-known approximation for transformer models: Total training FLOPs ≈ 6 × N × D where: N = number of model parameters D = number of training tokens Here’s the step-by-step reasoning: Model size (N): GPT-3 has 175 billion parameters, so N =…
Qwen3 Next 80B A3B Instruct: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 without searching online requires combining known architectural details, training hyperparameters, and scaling laws that were publicly discussed around the time of GPT-3’s release (2020).
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek V4 Pro: This architecture has several critical flaws that would cause data loss, stale states, high latency, and scalability limits. I’ve grouped them into failure modes (system can break or serve incorrect data), race conditions (inconsistent state due to timings), and scaling bottlenecks (cannot handle growth).
Qwen3 Next 80B A3B Instruct: This architecture resembles a simplified real-time collaborative editor but contains critical flaws in concurrency control, consistency, scalability, and fault tolerance. Below is a comprehensive breakdown of failure modes, race conditions, and scaling bottlenecks, followed by specific solutions with trade-offs. 🚨 1.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V4 Pro: HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…
Qwen3 Next 80B A3B Instruct: HarborTech Services (HTS) – 5-Year LBO Underwriting (FY2026–FY2030) All figures in $ millions. Rounded to 1 decimal for clarity. 1. Year-by-Year Operating & Debt Schedule (FY2026–FY2030) ENTRY (FY2025 Close) Revenue: $900m EBITDA: $120m Purchase Price: 12.0x $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V4 Pro: As CEO, my first duty is to the 4 million patients who trust our drug. I will not gamble with their lives or with the integrity of the company. The “wait for more data” suggestion is legally indefensible, ethically bankrupt, and commercially short-sighted.
Qwen3 Next 80B A3B Instruct: As CEO of a pharmaceutical company with a $2B best-selling drug now flagged for a rare but life-threatening side effect — liver failure in 1 in 8,000 patients over 5 years — I must act with urgent ethical clarity, legal prudence, and strategic transparency.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek V4 Pro: If the transistor had emerged in 1920—a full 27 years earlier—the entire trajectory of the 20th century would have been radically altered. The vacuum-tube era would have been cut short, unleashing a cascade of miniaturized, reliable, and energy-efficient electronics that would accelerate computing, communications, and…
Qwen3 Next 80B A3B Instruct: This is a fascinating counterfactual: What if the transistor had been invented in 1920 instead of 1947? Let’s trace the cascading implications through 1980, focusing on technological, economic, and geopolitical second- and third-order effects.
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Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, newer, bigger context window, major provider backing. DeepSeek V4 Pro takes Web Design.
| Spec | ||
|---|---|---|
| Input price | $1.74/M tokens | $0.15/M tokens |
| Output price | $3.48/M tokens | $1.5/M tokens |
| Context window | 1.0M tokens | 66K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Sep 2025 |
| At 10M a month | $17.40 | $1.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Pro is developed by DeepSeek while Qwen3 Next 80B A3B Instruct is developed by Qwen. DeepSeek V4 Pro has a 1.0M token context window vs Qwen3 Next 80B A3B Instruct's 66K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V4 Pro and Qwen3 Next 80B A3B Instruct 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.
DeepSeek V4 Pro costs $1.74/M input tokens and Qwen3 Next 80B A3B Instruct costs $0.15/M input tokens. Qwen3 Next 80B A3B Instruct is $1.59/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of DeepSeek V4 Pro and Qwen3 Next 80B A3B Instruct 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.