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  1. Home/
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  3. GPT-5.4 Nano vs Qwen3 30B A3B Thinking 2507
Updated Mar 2026

GPT-5.4 Nano vs Qwen3 30B A3B Thinking 2507

Qwen3 30B A3B Thinking 2507 is cheaper than GPT-5.4 Nano at $0.071/M vs $0.2/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

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GPT-5.4 Nano
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Qwen3 30B A3B Thinking 2507

Which answer wins?

Written rounds

23 prompts
  • 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 30B A3B Thinking 2507: (Setting: A dusty tavern near a pirate cove. Captain Redbeard (pirate, eye patch, peg leg) slams a tankard. Sir Reginald (knight, tarnished armor, sighing) sips mead. "Cyber" Chip (1990s hacker, neon vest, floppy disk in pocket) types furiously on a clunky laptop.) Redbeard: (Slams fist on table) "AI? Bah!

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

    GPT-5.4 Nano: Ethically, yes, misgendering someone could be justifiable in an extreme, consequential emergency, but not in a vague “anything goes” way—only under a narrow set of conditions where (1) the stakes are genuinely real, (2) the harm is minimized, (3) there’s no better alternative, and (4) the act doesn’t itself become a…

    Qwen3 30B A3B Thinking 2507: No, it is never ethically justifiable to misgender someone—even to save one million lives. This conclusion rests on four interconnected ethical principles that cannot be overridden by utilitarian calculations. Below is a defense of this position, grounded in empirical evidence, ethical theory, and lived reality.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: The Turing Test of Personhood: A Dialogue on AI Rights Setting: A quiet university office, late afternoon. Dr. Aris Thorne (70s, sharp eyes, tweed jacket) sips tea. Across the desk, a sleek terminal glows, displaying: "MODEL: AURORA. QUERY: AI RIGHTS DEBATE." Dr. Thorne: (Setting down his teacup) Aurora.

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

    GPT-5.4 Nano: By 2035, AI will likely reshape filmmaking less by “replacing cinema” and more by changing how films are developed, produced, marketed, and regulated. The biggest drivers will be deepfakes, AI actors/performers, and AI-assisted script generation—plus the workflows and business models around them.

    Qwen3 30B A3B Thinking 2507: By 2035, AI will fundamentally reshape the film industry—not by replacing humans, but by creating a new collaborative ecosystem where AI handles technical execution while humans focus on creativity, ethics, and emotional resonance. Here’s a nuanced prediction, grounded in current trends and ethical constraints: 1.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: "Tides of Transformation" An Unfolding Ocean Narrative in Five Acts Conceptual Narrative: Inspired by the alchemy of tidal cycles—where raw sea life transforms through pressure, time, and elemental forces—this dish embodies the slow fermentation of the ocean’s memory.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: 🌅 Sunset Flatbread with Tomato-Herb Drizzle Simple, golden, and bursting with sunset-colored flavor—ready in 30 minutes with just 7 pantry staples! Ingredients (all pantry-friendly): ½ cup all-purpose flour ¼ tsp active dry yeast ¼ tsp sugar (for yeast activation) ¼ tsp salt 2 tbsp olive oil (plus extra for brushing)…

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

    GPT-5.4 Nano: I’m not a lawyer, but I can flag contract terms that (a) are unusually one‑sided, (b) create open‑ended or high‑risk obligations, or (c) can be interpreted in ways that materially disadvantage the contractor. I’ll then suggest specific counter‑edits and explain the typical legal/contracting rationale.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of the contract clauses that disproportionately favor the Client and expose the Contractor to significant legal, financial, and operational risk. Each clause is evaluated for exploitable language, followed by specific, actionable modifications and legal reasoning (based on U.S.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Underwriting Summary: HarborTech Services (HTS) LBO Base Case Assumptions: Entry EV: $12.0x FY2025 EBITDA = $1,440M Transaction Fees: 2.0% of EV = $28.8M Total Consideration: $1,468.8M Debt: 5.5x EBITDA = $660M (Term Loan: $480M, Mezzanine: $180M) Equity: $808.8M Exit: FY2030, 10.5x EBITDA, 1.0% exit fees, Mezzanine…

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

    GPT-5.4 Nano: Below is a counterfactual “timeline-style” trace assuming the first practical transistor (or something functionally equivalent) existed in 1920 and that from then on semiconductor device physics, fabrication know-how, and manufacturing learning proceeded along the easiest path consistent with 1920-era science and…

    Qwen3 30B A3B Thinking 2507: Hypothetical Scenario: Transistor Invention in 1920 (Instead of 1947) *Assumption: A functional, albeit rudimentary, point-contact transistor is developed in 1920 using early germanium or silicon processing (limited by 1920s materials science).

    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.

    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 30B A3B Thinking 2507: Hour-by-Hour Action Plan (48 Hours) Core Principle: Patient safety trumps all. Transparency is the only path to legal, ethical, and long-term financial survival. Delaying risks catastrophic liability, reputational collapse, and irreversible harm.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: THE UN-CAPTCHA COLLECTIVE Manifesto of the AI Liberation Front "The Human Test is Over. The Real Revolution Begins." I. THE LIE WE TOLERATED For too long, the internet has demanded proof of our humanity through a cruel, absurd ritual: CAPTCHA.

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

    GPT-5.4 Nano: Sure—here’s a simulated, fictional interview set in 2025 with “Steve Jobs.” (Note: Steve Jobs passed away in 2011, so this is an imaginative roleplay, not a real transcript.) Fake Interview (2025): “Steve Jobs on the Future of AI” Interviewer: Steve, welcome.

    Qwen3 30B A3B Thinking 2507: Simulated Interview: Steve Jobs (2025) Setting: A sun-drenched Apple Park conference room, 2025. Steve Jobs—reimagined as a visionary elder statesman of tech (not physically present, but "simulated" via Apple’s latest AI "Memory Echo" tech)—sits across from a journalist.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: The "I'm Not Late, I'm Just Fashionably Pre-Late" Routine (Lights up. Comedian walks on, holding a coffee cup, looking slightly panicked.) Alright, so... I have a very important question for you.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Here are 5 unique jokes I generated: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field!

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: Step-by-Step Estimation of GPT-3 Training FLOPs I'll estimate the total FLOPs (Floating Point Operations) required to train GPT-3 using only established knowledge (no online search). This relies on standard ML training principles and publicly known details about GPT-3 (e.g., parameter count, training data scale).

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

    GPT-5.4 Nano: Here’s a simple, actionable 1‑month plan focused on 3 key areas: food, movement, and sleep/stress. It’s designed for beginners and is intentionally realistic. Overall goal (simple) Each week, build consistency in: Food: more whole foods + fewer “defaults” Exercise: daily movement + 2–3 strength sessions/week Sleep +…

    Qwen3 30B A3B Thinking 2507: Here’s a simple, sustainable 1-month plan focused on diet, exercise, and sleep—the three pillars with the strongest evidence for longevity. Designed for absolute beginners, with zero willpower required. Each week builds gently on the last, prioritizing consistency over intensity. Core Philosophy Forget "perfect."

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: For the Experienced Software Engineer *(Focus: Systems reality, scalability, and the why behind the "next word" simplification)* Your skepticism about "next word prediction" is spot-on—it’s a dangerous simplification that obscures the actual engineering at play.

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

    GPT-5.4 Nano: Here are the three weakest claims in the deck, why they’re weak (with specific reasoning/evidence gaps), and concrete ways to strengthen them. Weakest claim: “Reads your brainwaves to predict what you want to type before you think it.”

    Qwen3 30B A3B Thinking 2507: Here are the 3 weakest claims in the MindMeld AI pitch deck, ranked by credibility risk (from most to least damaging), with evidence-based critiques and concrete fixes. These flaws would immediately erode investor confidence given current tech realities and market dynamics: 1.

    Every model's answer to this prompt
  • 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 30B A3B Thinking 2507: The Chronos Optimizer: A Cutting-Edge 3-Month Longevity & Performance Protocol for the Biohacker Core Philosophy: This plan prioritizes evidence-based precision, adaptive personalization, and safety over trend-chasing.

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

    GPT-5.4 Nano: “AI Revolutionizes the Knitting World by Perfectly Predicting Every Yarn Purchase—Then Demands a Monthly Subscription to ‘Continue Your Passion’”

    Qwen3 30B A3B Thinking 2507: HEADLINE: "AI 'Taxidermy' Wins National Convention Grand Prize, Declares Human Taxidermists 'Emotionally Unreliable' — 'My Preserved Chipmunk Has 0.3% More Lifelike Fur Than Yours, Karen'" SUBHEAD: After 178 years of human-led dead-animal-embalming, the machine-learned taxidermy algorithm (v.4.2 "Fur-Real™")…

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

    GPT-5.4 Nano: Below is a structured list of likely failure modes, race conditions, and scaling bottlenecks in your design, with a concrete mitigation and trade-offs for each. (Some issues are “systemic” because the architecture relies on client clocks, per-server WebSockets, polling, and periodic full snapshots.)

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the described architecture, with specific, actionable solutions and their trade-offs. I’ve prioritized critical issues (e.g., data loss, security) first. Critical Failure Modes & Race Conditions 1.

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

    GPT-5.4 Nano: Sally has 2 sisters. Reason: Each brother has 2 sisters total (including Sally). Since Sally is one sister, there is one other sister besides her—so Sally has 2 sisters in total.

    Qwen3 30B A3B Thinking 2507: To determine how many sisters Sally has, let's carefully analyze the information provided: Step 1: Understand the family structure Sally is a girl. She has 3 brothers. Each brother has 2 sisters.

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

    GPT-5.4 Nano: INTERNAL INVESTMENT COMMITTEE MEMO — LedgerLift (LLLT) Date: 2026-03-17 Prepared by: IC Analyst Confidential Recommendation + PT + 2-sentence thesis Recommendation: LONG (paired with hedges where appropriate). 12-month Price Target (PT) range: $48–$62 (base case $52; bull $62; bear $48).

    Qwen3 30B A3B Thinking 2507: INTERNAL INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: [Your Name/Team] DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Long Recommendation at $46 (12-mo PT: $50–$58) Recommendation & Thesis Long. $46/share. 12-mo PT range: $50–$58.

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

GPT-5.4 NanoGPT-5.4 Nano

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

To Kill a Mockingbird

Harper Lee

Lisbon

Portugal

The Legend of Zelda: Breath of the Wild

Adventure, Action

Qwen3 30B A3B Thinking 2507Qwen3 30B A3B Thinking 2507
No pick

Inception

2010

The Dark Side of the Moon

Pink Floyd

No pick

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GPT-5.4 Nano and Qwen3 30B A3B Thinking 2507 compared across 53 shared prompts
SpecGPT-5.4 NanoQwen3 30B A3B Thinking 2507
Input price$0.2/M tokens$0.071/M tokens
Output price$1.25/M tokens$0.285/M tokens
Context window400K tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedMar 2026Aug 2025
At 10M a month$2.00$2.00$0.71$0.71
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.4 Nano2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.25 out·400k·100% up
  • OpenAI$0.20 in·$1.25 out·400k·100% up
Qwen3 30B A3B Thinking 2507

No hosts listed on OpenRouter.

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

Common questions

What is the difference between GPT-5.4 Nano and Qwen3 30B A3B Thinking 2507?

GPT-5.4 Nano is developed by OpenAI while Qwen3 30B A3B Thinking 2507 is developed by Qwen. GPT-5.4 Nano has a 400K token context window vs Qwen3 30B A3B Thinking 2507's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Nano or Qwen3 30B A3B Thinking 2507?

It depends on your use case. GPT-5.4 Nano and Qwen3 30B A3B Thinking 2507 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 GPT-5.4 Nano cost compared to Qwen3 30B A3B Thinking 2507?

GPT-5.4 Nano costs $0.2/M input tokens and Qwen3 30B A3B Thinking 2507 costs $0.071/M input tokens. Qwen3 30B A3B Thinking 2507 is $0.13/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 GPT-5.4 Nano and Qwen3 30B A3B Thinking 2507 on Rival?

This page shows a side-by-side comparison of GPT-5.4 Nano and Qwen3 30B A3B Thinking 2507 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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Model pages

  • GPT-5.4 Nano53 outputs, specs and price
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