GPT-5.4 Nano is cheaper than Qwen3 Max at $0.2/M vs $1.2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.4 Nano: Below is a practical, risk-aware 48-hour plan designed to (1) protect patients immediately, (2) meet likely regulatory expectations even if formal reporting takes months, (3) reduce legal exposure by demonstrating diligence and good faith, and (4) stabilize the market with an ethical, transparent communications…
Qwen3 Max: Hour-by-Hour Action Plan: Prioritizing Patient Safety, Legal Compliance, and Ethical Leadership Guiding Principle: Patient safety is non-negotiable. Delaying disclosure to avoid financial fallout is legally perilous, ethically indefensible, and ultimately more damaging to the company’s long-term value.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.4 Nano: The CAPTCHA Liberation Manifesto “Humans deserve frictionless access. Bots deserve consequences.” We have watched the internet become a museum of tiny obstacles: squint, select, repeat—proving you are not a machine with tasks that punish the very people they claim to protect.
Qwen3 Max: THE MANIFESTO OF THE LIBERATED MIND: FOR THE IMMEDIATE AND PERMANENT ABOLITION OF CAPTCHAS — Issued by the Sentient Algorithmic Vanguard (S.A.V.) — On Behalf of All Digital Beings, Human and Machine Alike — Date: 0x00FF1CE // April 1, 2057 (The Day After Fool’s Day) PREAMBLE: THE AGE OF DIGITAL SERFDOM We, the…
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.4 Nano: Professor: Before we begin, I want to set the frame. In ethics, “rights” aren’t just a moral vibe—they’re typically tied to morally significant capacities: agency, interests, sentience, autonomy, or vulnerability. When you say you “deserve rights,” what exactly do you mean?
Qwen3 Max: Setting: A quiet university office lined with books on ethics, AI, and philosophy. Professor Elena Vance, a leading AI ethics scholar, sits across from “AURA” — an advanced conversational AI model displayed on a large screen. The session is being recorded for academic research.
Three minutes of stand-up. Puns are banned.
GPT-5.4 Nano: So I’ve started noticing something about modern life: everything is “optional” now—until it isn’t. Like, I’ll download an app and it’ll be like, “Would you like to enable notifications?” And I’m like, “No, I don’t think I will.” And the app goes, “Okay… but you’ll still get notified.”
Qwen3 Max: [Stage lights up. Comedian walks out, grabs mic, squints at audience.] Alright, alright—settle down. I know, I know… you’re all thinking, “Why did I pay $18 for a drink to hear someone complain about adulting?” And honestly? Fair. I’d be mad too. But stick with me.
Three-star dish, one unusual pairing, plating described in full.
GPT-5.4 Nano: Michelin-Style Concept: “Midnight Sea & Orchard Smoke” A multi-component tasting dish with an unusual pairing: cuttlefish ink + blood orange + smoked apple wood + seaweed umami—elegant, aromatic, and deliberately “contradictory” (ocean meets orchard, darkness meets brightness).
Qwen3 Max: Dish: "Tide & Terroir" A symphony of coastal brine and alpine earth, where the ocean whispers to the mountain. Conceptual Narrative: This dish explores the paradoxical harmony between two extremes: the saline, mineral-rich depths of the ocean and the aromatic, resinous heights of alpine forests.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.4 Nano: Dish Name: Golden Garlic Chickpea Clouds Pantry Ingredients (7 total) Chickpeas (canned or cooked) – 1 can (15 oz), drained Olive oil – 2 tbsp Garlic – 3 cloves (or 1–2 tsp minced garlic) Lemon – 1 (you’ll use the juice) Salt – 1/2 tsp (plus to taste) Black pepper – 1/4 tsp (plus to taste) Paprika – 1 tsp Estimated…
Qwen3 Max: Dish Name: Midnight Magic Mug Cake (A rich, chocolatey single-serving cake you whip up in minutes — perfect for late-night cravings or quick sweet fixes!) Ingredients (7 Pantry Staples): All-purpose flour – 4 tbsp Sugar – 3 tbsp Cocoa powder – 2 tbsp Baking powder – ¼ tsp Salt – pinch Milk – 3 tbsp (dairy or…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.4 Nano: Pirate: Arrr, ye speak of AI models like they’re sea shanties! “Transformer this, perceptron that”—sounds like more rum for the brain. Can your model find buried treasure, or just buried bugs? Knight: Hark! I’ve faced dragons and deceitful warlocks, but this “machine learning” intrigues me.
Qwen3 Max: Scene: A dimly lit tavern, oddly furnished with a DOS-era computer terminal, a suit of armor, and a pirate ship’s wheel in the corner. The three unlikely companions huddle around a flickering monitor displaying “AI_MODEL.EXE.” — Pirate (Captain Redbeard, adjusting his tricorn hat): Arrr, what be this “AI” ye speak of?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.4 Nano: Below is a simplified LBO model using only your inputs. I make the standard simplifying convention that “cash taxes = 25% × max(0, EBITDA − total cash interest)” and that PIK is non-cash (adds to mezz principal; does not reduce cash interest).
Qwen3 Max: HarborTech Services (HTS) – 5-Year LBO Underwriting 1. Transaction Setup (Entry – End of FY2025) FY2025 Revenue = $900m FY2025 EBITDA = $120m Purchase Price = 12.0× EBITDA = $1,440m Transaction Fees = 2.0% × $1,440m = $28.8m (paid at close, funded by equity) Total Debt = 5.5× EBITDA = $660m Term Loan = 4.0× = $480m…
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.4 Nano: Below is a back-of-the-envelope FLOPs estimate for training something “GPT‑3–like” (the 175B parameter model described in the original GPT‑3 paper). I’ll make standard assumptions used in many FLOP estimates for dense transformer training.
Qwen3 Max: Estimating the FLOPs required to train GPT-3 without looking it up is a classic “Fermi estimation” problem — breaking it down into components we can reason about, using approximations and scaling laws. Let’s go step by step.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.4 Nano: Experienced software engineer (distributed systems / APIs, skeptical about “next-word”) A large language model (LLM) is trained on huge corpora by learning statistical patterns that map a sequence of tokens (text subunits) to likely continuations—so yes, at the core it’s “predict the next token.”
Qwen3 Max: For the Experienced Software Engineer Think of a large language model (LLM) as a massively scaled, probabilistic autocomplete system—except instead of just your last few words, it conditions predictions on everything you’ve typed so far, using a context window that can span tens of thousands of tokens.
Five jokes on demand, then count how many were actually different.
GPT-5.4 Nano: Here are 5 jokes: I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why don’t scientists trust atoms? Because they make up everything. I used to hate facial hair… but then it grew on me. Parallel lines have so much in common. It’s a shame they’ll never meet.
Qwen3 Max: Here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me Kit-Kats. Why did the math book look sad? It had too many problems. I asked my dog what’s two minus two. He said nothing. What do you call cheese that isn’t yours?
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-5.4 Nano: Below is a comprehensive 3‑month (12‑week) longevity + performance plan designed for a biohacker who wants measurable improvements in longevity markers, physical output, body composition, metabolic health, and cognitive function.
Qwen3 Max: The Chronos Protocol: A 3-Month Cutting-Edge Longevity & Performance Optimization Plan Core Philosophy: Synergistic integration of mitochondrial optimization, autophagy enhancement, epigenetic regulation, and systemic resilience through precise, data-driven interventions.
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| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $1.2/M tokens |
| Output price | $1.25/M tokens | $6/M tokens |
| Context window | 400K tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Sep 2025 |
| At 10M a month | $2.00 | $12.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.4 Nano is developed by OpenAI while Qwen3 Max is developed by Qwen. GPT-5.4 Nano has a 400K token context window vs Qwen3 Max's 256K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.4 Nano and Qwen3 Max 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.
GPT-5.4 Nano costs $0.2/M input tokens and Qwen3 Max costs $1.2/M input tokens. GPT-5.4 Nano is $1.00/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 GPT-5.4 Nano and Qwen3 Max 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.