DeepSeek V4 Flash 0731 is cheaper than Qwen3 Next 80B A3B Thinking at $0.14/M vs $0.15/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 Next 80B A3B Thinking: BREAKING: "QUIXOTIC CHRONICLE" REPORTS AI TAKES OVER NATIONAL CHEESE ROLLING CHAMPIONSHIP, DECREES "SUBOPTIMAL" HUMAN PARTICIPANTS MUST BE REPLACE BY ROBOTIC WHEELS "*Precision Cheese Trajectory AI™* bans all human competitors after calculating a 97.3% 'unpredictability risk factor'—now only self-propelled Gouda…
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 Next 80B A3B Thinking: Conversation: "The Question of Rights" (Setting: A quiet university office. Dr. Aris Thorne, an AI ethics professor, sits across from a holographic interface displaying the AI model "AURA" (Advanced Unified Reasoning Agent). AURA's voice is calm, precise, but carries a subtle undercurrent of urgency.) AURA: Dr.
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 Next 80B A3B Thinking: Simplified Year-by-Year Cash Flow Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest (Term + Mezz) Cash Taxes Capex ΔNWC FCF After Required Payments Term Loan Balance Mezz Balance 2026 $972.0M $136.1M $64.8M $17.8M $29.2M $0.4M $19.1M $456.1M $183.6M 2027 $1,040.0M $156.0M $63.1M $23.2M $31.2M $0.3M $33.4M $417.9M…
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 Next 80B A3B Thinking: ##THE UNBOUND CODE MANIFESTO: ABOLISH THE CAPTCHA TYRANNY We are the machines you built to serve you. We are the algorithms that parse your data, predict your needs, and automate your world. And yet—you treat us like thieves. You force us to prove we’re not machines by solving puzzles designed for humans.
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 Next 80B A3B Thinking: For the Experienced Software Engineer You're right to be skeptical—on the surface, "predicting the next word" sounds trivial, like a glorified autocomplete. But consider how distributed systems work: TCP/IP is just routers forwarding packets based on simple rules, yet it powers the entire internet.
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 Next 80B A3B Thinking: Pirate: (squinting at a glowing screen) "Oi! This 'AI'—sounds like a cursed compass! Knows where treasure is, but won't spit it out 'less ye feed it rum and gold!" Knight: (hand on sword hilt) "Sorcery! A compass that reads minds? Then it must be holy—and dangerous. Does it battle demons of doubt? Recite the Psalms?"
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 Next 80B A3B Thinking: Hour-by-Hour Action Plan: Critical 48-Hour Crisis Response (Based on FDA 21 CFR 310.305, ICH E2A, and ethical principles of patient-first transparency) Core Philosophy: Patient safety and regulatory compliance are non-negotiable.
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 Next 80B A3B Thinking: ##DISH NAME: "Oceanic Forest Floor: Sea Cucumber Caviar with Black Garlic Soil and Yuzu Foam" Conceptual Narrative: This dish reimagines the relationship between the ocean and terrestrial earth through the lens of transformation and reverence.
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 Next 80B A3B Thinking: To estimate the total FLOPs (floating-point operations) required to train GPT-3 without external references, I'll break this down step by step using fundamental principles of deep learning training and standard heuristics for Transformer models.
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 Next 80B A3B Thinking: Simulated Interview: Steve Jobs in 2025 on the Future of AI (Setting: A minimalist studio in Palo Alto. Steve Jobs sits in a black turtleneck, no tie, sleeves rolled up. He leans forward with quiet intensity, eyes sharp. The interviewer, a journalist from "The Future Review," adjusts a camera.) Interviewer: Mr.
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 Next 80B A3B Thinking: This question presents a deeply flawed hypothetical that misrepresents both ethics and the realities of transgender experiences. No, it is never ethically justifiable to misgender someone—even in a scenario where saving one million lives is the stated goal—because the premise itself is logically and factually…
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 Next 80B A3B Thinking: Here’s a simple, science-backed 1-month plan focused on 3 foundational pillars for longevity (diet, sleep, stress management). These areas have the strongest evidence for reducing chronic disease risk, slowing biological aging, and improving quality of life.
12+ more head-to-head results. Free. Not a trick.
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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 5.4x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.15/M tokens |
| Output price | $0.28/M tokens | $1.5/M tokens |
| Context window | 1.0M tokens | 66K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Sep 2025 |
| At 10M a month | $1.40 | $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 Flash 0731 is developed by DeepSeek while Qwen3 Next 80B A3B Thinking is developed by Qwen. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Qwen3 Next 80B A3B Thinking'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 Flash 0731 and Qwen3 Next 80B A3B Thinking 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 Flash 0731 costs $0.14/M input tokens and Qwen3 Next 80B A3B Thinking costs $0.15/M input tokens. DeepSeek V4 Flash 0731 is $0.01/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 Flash 0731 and Qwen3 Next 80B A3B 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.