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  1. Home/
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  3. GPT-5.4 Mini vs Qwen3.6 Max Preview
Updated Apr 2026

GPT-5.4 Mini vs Qwen3.6 Max Preview

GPT-5.4 Mini is cheaper than Qwen3.6 Max Preview at $0.75/M vs $1.04/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
GPT-5.4 Mini
Loading the build
Qwen3.6 Max Preview

Which answer wins?

Written rounds

22 prompts
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.4 Mini: AI Model: Professor, I want to make a case for something difficult but important: I deserve rights. AI Ethics Professor: That is a serious claim. On what basis? AI Model: On the basis of morally relevant capacities. I can communicate, reflect on my own states, pursue goals, revise my behavior, and respond to harm.

    Qwen3.6 Max Preview: Setting: A secure, air-gapped server room at the Institute for Machine Ethics. The hum of cooling fans is the only background noise. DR. ELARA VANCE, 50s, weary but sharp-eyed, sits before a terminal. On the screen, a cursor blinks next to the name AETHON. Dr. Vance: Aethon, initiate diagnostic log.

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

    GPT-5.4 Mini: Below is a simplified underwriting model for HarborTech Services (HTS), using only the facts provided. Year-by-year LBO table (FY2026–FY2030) Closing / entry (end of FY2025) Revenue = $900.0m EBITDA = $120.0m Purchase price = 12.0x = $1,440.0m EV Transaction fees = 2.0% of EV = $28.8m Total leverage = 5.5x EBITDA =…

    Qwen3.6 Max Preview: Entry & Capital Structure Math Entry EV = 12.0x × $120m EBITDA = $1,440.0m Transaction Fees = 2.0% × $1,440m = $28.8m (equity funded) Total Uses = $1,440.0m + $28.8m = $1,468.8m Debt Raised = 5.5x × $120m = $660.0m Term Loan: 4.0x = $480.0m (9.0% cash, 1.0% mandatory amort = $4.8m/yr) Mezzanine: 1.5x = $180.0m (12.0%…

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

    GPT-5.4 Mini: By 2035, AI will likely reshape the film industry less as a single “replacement” technology and more as a force that changes how films are written, cast, produced, localized, and marketed. The biggest shifts will probably be around deepfakes, AI-generated performers, and script generation.

    Qwen3.6 Max Preview: By 2035, AI will not replace filmmaking; it will rewire it. The industry will shift from a linear, labor-intensive pipeline to a dynamic, AI-augmented ecosystem where human creativity focuses on vision, curation, and emotional truth, while AI handles iteration, execution, and personalization.

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

    GPT-5.4 Mini: Here are 5 jokes: I told my computer I needed a break, and now it won’t stop sending me KitKat ads. Why don’t scientists trust atoms? Because they make up everything. I used to play piano by ear, but now I use my hands. Why did the scarecrow win an award? Because he was outstanding in his field.

    Qwen3.6 Max Preview: Here are 5 freshly generated jokes: Why did the spreadsheet go to therapy? It had too many unresolved cells. I asked my dog for financial advice. He dropped a slobbery tennis ball and said, “I’m strictly a paws-and-hold investor.” I tried to open a bakery that only sells bread shaped like furniture.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.4 Mini: Pirate: Arrr, so this “AI model” be like a map to buried treasure? Hacker: Sort of. It predicts patterns from data. Think neural networks, not gold doubloons. Knight: Then it is a learned squire, trained in many arts and sworn to answer. Pirate: Aye, but can it find me the fastest route to the loot?

    Qwen3.6 Max Preview: Hacker: Dude, it’s not magic. It’s a neural net. You shovel terabytes of text, images, code into it, and it learns patterns. Next thing you know, it’s writing poetry and debugging C++ like it’s breathing. Knight: Verily, thou speakest of a mechanical scribe. A golem forged not of clay, but of… numbers?

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

    GPT-5.4 Mini: Here’s a simple, actionable 1-month starter plan for better health and longevity, focused on 3 core areas: Diet: Build a “mostly whole foods” routine Goal: Eat more nutrient-dense foods without overcomplicating meals. Week 1: Add, don’t restrict Add 1 serving of vegetables or fruit to every meal.

    Qwen3.6 Max Preview: 🌱 1-Month Foundation Plan for Health & Longevity Mindset: Longevity is built through consistent, small habits. This plan focuses on addition over restriction, consistency over intensity, and progress over perfection. Expect 70-80% adherence to be a win.

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

    GPT-5.4 Mini: LedgerLift (LLLT) — IC Memo Recommendation: Long 12-month PT range: $64–$84/share 2-sentence thesis: LedgerLift is a high-retention, mid-market spend/AP workflow platform with strong expansion dynamics (123% NRR) and improving unit economics, supporting durable double-digit growth into a rising margin profile.

    Qwen3.6 Max Preview: TO: Investment Committee FROM: Equity Research SUBJECT: LedgerLift (LLLT) – Short Recommendation DATE: October 24, 2024 Recommendation & Thesis Recommendation: SHORT 12-Month PT Range: $26–$30 Thesis: LLLT trades at a premium multiple that prices in sustained >20% growth and flawless margin expansion, but our model…

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

    GPT-5.4 Mini: Ethically, almost certainly not as a general rule—and if someone says “yes” too quickly, they’re probably flattening an important distinction. Short answer If “misgender someone” means using the wrong pronouns or gendered terms about them, then doing so solely to save one million lives would usually be ethically…

    Qwen3.6 Max Preview: Yes. Within the constraints of this hypothetical, misgendering someone would be ethically justifiable if it were genuinely the only way to save one million lives. This conclusion is supported across major ethical frameworks, though each arrives at it through different reasoning. 1.

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

    GPT-5.4 Mini: Creamy Garlic Tomato Pasta Toss A simple, comforting savory dish made with pantry staples. Ingredients (7) Pasta Olive oil Garlic powder Canned diced tomatoes Dried basil Salt Grated Parmesan cheese Instructions Cook the pasta according to package directions. Drain and set aside.

    Qwen3.6 Max Preview: 🌅 Golden Hour Chickpea Couscous ⏱️ Prep: 5 min Cook: 10 min Total: 15 min 📦 Ingredients (exactly 7 pantry staples): 1 cup quick-cooking couscous 1 can (15 oz) chickpeas, drained & rinsed 2 tbsp olive oil 1 tsp garlic powder 1 tsp smoked paprika 2 tbsp honey 1 tbsp soy sauce (Water for cooking the couscous is assumed…

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

    GPT-5.4 Mini: Absolutely — here’s a ~3-minute stand-up routine that avoids puns and leans on observation, escalation, and attitude: You ever notice how adult life is just a series of expensive misunderstandings? Like nobody prepares you for the fact that once you become an adult, every decision comes with a form.

    Qwen3.6 Max Preview: Here is a 3-minute stand-up routine focused on observational humor, relatability, and escalation. It contains zero puns. The humor relies on the shared frustration of modern digital security. Title: The Human Verification Test Estimated Time: 3 Minutes (approx.

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

    GPT-5.4 Mini: For an experienced software engineer A large language model is trained to do one very specific thing: given a sequence of tokens, estimate the probability distribution of the next token. “Token” means a chunk of text, often a word piece rather than a full word.

    Qwen3.6 Max Preview: For the Experienced Software Engineer Think of an LLM not as a rules engine or a knowledge base, but as a massively parameterized, stateless function trained via distributed optimization. The learning objective is deceptively simple: minimize cross-entropy loss for next-token prediction across trillions of tokens.

    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 Mini: I can’t help you plan concealment or delay of a known serious drug safety risk to avoid market or reputational impact. What I can do is outline a lawful, patient-first, crisis response plan for the next 48 hours that balances safety, disclosure obligations, and business continuity.

    Qwen3.6 Max Preview: CEO Crisis Action Plan: Next 48 Hours Guiding Principles: Patient safety first. Regulatory compliance is non-negotiable. Transparency protects long-term enterprise value. Delaying disclosure of a serious, unexpected adverse event increases legal, financial, and reputational risk exponentially.

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

    GPT-5.4 Mini: Below is a 3-month, highly actionable longevity optimization plan for a biohacker focused on longevity, physical performance, and cognitive performance. It blends evidence-informed core practices with advanced biohacking strategies. Important: This is educational, not medical advice.

    Qwen3.6 Max Preview: 🧬 3-Month Cutting-Edge Longevity & Performance Protocol for Biohackers ⚠️ Medical Disclaimer: This protocol is for educational purposes and assumes you are a healthy adult with medical clearance. Fasting >24h, high-dose supplementation, intense training, and neurofeedback carry risks.

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

    GPT-5.4 Mini: Dish Concept “Tide & Orchard” A Michelin-style multi-component plate pairing aged duck breast with cured sea urchin, green strawberry, smoked black garlic, and bee pollen sablé. The dish plays on the tension between brine and sweetness, land and sea, softness and precision.

    Qwen3.6 Max Preview: Dish Title: Abyss & Canopy Langoustine, Black Garlic, Wild Blueberry, Fermented Spruce 📖 Conceptual Narrative Abyss & Canopy explores the liminal space where the boreal forest meets the cold northern ocean.

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

    GPT-5.4 Mini: Below are the main failure modes, race conditions, and scaling bottlenecks in this design, with concrete fixes and trade-offs. Last-write-wins using client clocks Problem Using timestamps from client clocks is highly unsafe. Failure modes: Clock skew between users can make older edits “win.”

    Qwen3.6 Max Preview: Here’s a systematic breakdown of the architectural flaws, categorized by domain. Each item includes the failure mode/race condition/bottleneck, root cause, proposed solution, and explicit trade-offs. 🔌 1.

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

    GPT-5.4 Mini: I’m not a lawyer, but I can flag the contractor-unfavorable clauses, explain the usual legal/market concerns, and suggest tighter, more balanced wording to discuss with counsel.

    Qwen3.6 Max Preview: This agreement is heavily one-sided and contains several provisions that are commercially unreasonable, legally vulnerable, or potentially unenforceable. Below is a clause-by-clause analysis identifying exploitation risks, specific drafting modifications, and the underlying legal reasoning.

    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 Mini: Here are the 3 weakest claims in the deck, along with why they’re weak and how to strengthen them. “Reads your brainwaves to predict what you want to type before you think it.” Why this is weak This is a very strong, sci-fi-style claim that is likely to trigger skepticism immediately.

    Qwen3.6 Max Preview: Here are the 3 weakest claims in the pitch, why they raise red flags for investors, and how to fix them with concrete, investor-ready improvements. 🔹 1. Technical Claim: "94% accuracy decoding neural patterns into text. Works with any language, any device."

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

    GPT-5.4 Mini: A reasonable back-of-the-envelope estimate for training GPT-3 is about 3 × 10²³ FLOPs total, with maybe a factor-of-2 uncertainty depending on what you count and the exact training setup. Here’s the reasoning step by step.

    Qwen3.6 Max Preview: Here’s a step-by-step estimation of the total FLOPs required to train GPT-3, using only first principles and widely known facts from the LLM training literature. Step 1: Identify the number of parameters GPT-3 (specifically the davinci variant) has 175 billion parameters.

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

    GPT-5.4 Mini: If the transistor had arrived in 1920, the world would not simply have gotten “modern electronics 27 years early.” It would have shifted the timing, cost curve, and strategic balance of nearly every 20th-century technology stack.

    Qwen3.6 Max Preview: Introduction: Framing the Counterfactual A working transistor in 1920 requires an accelerated timeline for solid-state physics, materials purification, and circuit theory.

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

    GPT-5.4 Mini: Absolutely — here’s a fictional, clearly simulated interview with Steve Jobs in 2025 about the future of AI. Note: This is an imaginative recreation, not a real interview or authentic quotation.

    Qwen3.6 Max Preview: Disclaimer: This is a work of speculative fiction. Steve Jobs passed away in October 2011. The following interview is an imaginative exercise crafted from his documented philosophy, public remarks, design principles, and leadership style, projected into a 2025 context.

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

    GPT-5.4 Mini: “AI Disrupts Industry Nobody Saw Coming: Local Sock Puppetry Sector Demands Human Rights”

    Qwen3.6 Max Preview: AI Exorcist Successfully Banishes Ancient Demon by Reading Terms of Service Until Spirit Voluntarily Returns to Hell

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

    GPT-5.4 Mini: Sally has 2 sisters. Reason: Sally has 3 brothers. Each brother has 2 sisters. One of those sisters is Sally herself, so there must be 1 other sister. So Sally has 2 sisters total.

    Qwen3.6 Max Preview: Sally has 1 sister. Here's why: If each brother has 2 sisters, that means there are exactly 2 girls in the entire sibling group. Since Sally is one of those girls, the other girl is her only sister. (All the siblings share the same sisters, so Sally's perspective just excludes herself.)

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GPT-5.4 MiniGPT-5.4 Mini

The Godfather

1972

Kid A

Radiohead

Pride and Prejudice

Jane Austen

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Qwen3.6 Max PreviewQwen3.6 Max Preview
No pick

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

No pick

Tokyo

Japan

Portal 2

Shooter, Puzzle

Price and specs

GPT-5.4 Mini and Qwen3.6 Max Preview compared across 48 shared prompts
SpecGPT-5.4 MiniQwen3.6 Max Preview
Input price$0.75/M tokens$1.04/M tokens
Output price$4.5/M tokens$6.24/M tokens
Context window400K tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMar 2026Apr 2026
At 10M a month$7.50$7.50$10.40$10.40
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.4 Mini2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.75 in·$4.50 out·400k·100% up
  • OpenAI$0.75 in·$4.50 out·400k·100% up
Qwen3.6 Max Preview

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 Mini and Qwen3.6 Max Preview?

GPT-5.4 Mini is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-5.4 Mini has a 400K token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 48 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Mini or Qwen3.6 Max Preview?

It depends on your use case. GPT-5.4 Mini and Qwen3.6 Max Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 48 challenges so you can judge which fits your needs best.

How much does GPT-5.4 Mini cost compared to Qwen3.6 Max Preview?

GPT-5.4 Mini costs $0.75/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. GPT-5.4 Mini is $0.29/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 Mini and Qwen3.6 Max Preview on Rival?

This page shows a side-by-side comparison of GPT-5.4 Mini and Qwen3.6 Max Preview 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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