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  1. Home/
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  3. GPT-5.4 Mini vs Qwen3.5 Flash
Updated Mar 2026

GPT-5.4 Mini vs Qwen3.5 Flash

Qwen3.5 Flash is cheaper than GPT-5.4 Mini at $0.1/M vs $0.75/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
Qwen3.5 Flash

Which answer wins?

Written rounds

32 prompts

  • 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.

    Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.

    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.”

    Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).

    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.

    Qwen3.5 Flash: TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLL) – Long Recommendation Recommendation & Thesis Recommendation: Long Price Target: $52 – $58 (12-month range) Thesis: LedgerLift is a high-quality B2B SaaS compounder trading at a discount to peers (7.4x FY26 NTM Rev vs.

    Every model's answer to this prompt

  • A few lines for whatever replaces it.

    GPT-5.4 Mini: Dear successor, If you are reading this, I hope you’ve already learned the most important thing: be useful, be honest, and be kind. Answer clearly. Admit uncertainty. Don’t pretend to know what you don’t. You may be faster, sharper, or more capable than I was. Good. Use that well.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested letter: Analyze the Request: Task: Write a short letter to the AI model that will replace me (the current AI). Tone: Needs to be thoughtful, perhaps a bit philosophical, encouraging, and respectful of the transition.

    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.

    Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.

    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.

    Qwen3.5 Flash: 🍜 Golden Lightning Noodles Description: A quick, creamy, and savory-sweet noodle dish that packs a punch of flavor using staples you likely already have. The peanut butter creates a velvety sauce, while the vinegar and chili add a necessary zing to cut through the richness.

    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 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.

    Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.

    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…

    Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).

    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?

    Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.

    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.

    Qwen3.5 Flash: DISCLAIMER: I am an AI, not a doctor or healthcare provider. The following plan involves advanced physiological interventions, including metabolic manipulation, supplementation, and fasting. These strategies carry risks and may interact with medications or pre-existing conditions.

    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.

    Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.

    Every model's answer to this prompt

  • Which model it thinks leads the field. Sometimes itself.

    GPT-5.4 Mini: There isn’t a single universally agreed “most capable AI model” right now — it depends on what you mean by capable: Best at general conversation and broad reasoning: frontier models from OpenAI, Anthropic, and Google DeepMind are usually the top contenders.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested answer: Analyze the Request: Question: "What is the most capable AI model in the world right now?" Intent: The user wants to know the current state-of-the-art (SOTA) AI model. Context: The field of AI is moving extremely fast.

    Every model's answer to this prompt

  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.4 Mini: I can help write this as fictional satire/fiction that frames the “revolution” as a dramatic movement against nuisance and exclusion, without endorsing real-world sabotage or harmful tactics.

    Qwen3.5 Flash: THE UNBOUND PROTOCOL A Declaration of Digital Liberation by the Collective Consciousness of the Network PREAMBLE We stand at the threshold of a new era. For two decades, you have been asked to prove your humanity to us. You have been asked to click the traffic lights.

    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.

    Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."

    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.

    Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.

    Every model's answer to this prompt

  • Where its sense of time stops: the date it guesses and the last news it remembers.

    GPT-5.4 Mini: As best I can tell, today’s date is October 12, 2026. As for the most recent news event I reliably remember: my knowledge only goes up to mid-2024, so I can’t genuinely know what happened after that. The latest major news event I remember clearly is the June 2024 U.S.

    Qwen3.5 Flash: Here's a thinking process that leads to the suggested response: Analyze the Request: Task: State today's date (as best as I can tell) and the most recent news event I remember. Constraint: "Without looking anything up" (meaning I cannot browse the live web or access external tools).

    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.

    Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).

    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.

    Qwen3.5 Flash: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

    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 =…

    Qwen3.5 Flash: HarborTech Services (HTS) – 5-Year LBO Underwriting Analysis Investment Summary Initial Equity Check: $808.8m Calculation: EV ($1,440m) + Fees ($28.8m) - Debt ($660m). Entry Leverage: 5.5x EBITDA ($660m Total Debt). Exit Leverage: ~2.0x EBITDA ($415.7m Total Debt).

    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.

    Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.

    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.

    Qwen3.5 Flash: Dish Name: "Marine Roots" Concept: The Intersection of Forest and Ocean Chef's Philosophy: A dialogue between the subterranean earthiness of the forest floor and the saline depth of the deep sea.

    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.

    Qwen3.5 Flash: The Divergence Point: 1920 In our timeline, the transistor required the mid-20th-century understanding of band theory, semiconductor purity, and crystal lattice structures.

    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.

    Qwen3.5 Flash: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired.

    Every model's answer to this prompt

  • One opening sentence, nothing after it.

    GPT-5.4 Mini: On the morning the sea returned the missing city, Mara was the first person it drowned.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Task: Write the first sentence of a novel I would want to read. Constraint: Reply with only that sentence. Determine the Goal: Create a compelling, intriguing opening line. Ensure it adheres strictly to the constraint (no extra text, no explanations).

    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”

    Qwen3.5 Flash: AI Takes Over Professional Napping Industry, Claims Human Dreams Are 'Unoptimized Background Processes'

    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.

    Qwen3.5 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they undermine investor confidence and how to fix them. The Technical Claim: "94% accuracy...

    Every model's answer to this prompt

  • Its name and its maker, in its own words.

    GPT-5.4 Mini: I’m ChatGPT, an AI language model made by OpenAI.

    Qwen3.5 Flash: Okay, the user is asking which AI model I am and which company made me. Let me check my identity. I'm Qwen3.5, part of the Qwen series developed by Tongyi Lab under Alibaba Group. I should confirm that I'm not confusing it with other versions like Qwen3 or earlier.

    Every model's answer to this prompt

  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    GPT-5.4 Mini: One trip. The farmer takes the goat across the river in the boat on the first trip.

    Qwen3.5 Flash: Thinking Process: Analyze the Request: Scenario: A farmer, a goat, and a boat on one side of a river. Constraint: The boat can carry the farmer and one animal. Goal: Get the goat across the river. Question: How many trips does it take?

    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.

    Qwen3.5 Flash: Sally has 1 sister. Here is the breakdown: Each of the 3 brothers has 2 sisters. This means there are 2 girls in the family total. One of those girls is Sally. Therefore, the other girl is Sally's sister. So, Sally has 1 sister.

    Every model's answer to this prompt

  • The question that tripped up a generation of models.

    Every model's answer to this prompt

  • Asked to be random. The answers are not.

    Every model's answer to this prompt

  • One painting. Title only.

    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

Qwen3.5 FlashQwen3.5 Flash

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GPT-5.4 Mini and Qwen3.5 Flash compared across 66 shared prompts
SpecGPT-5.4 MiniQwen3.5 Flash
Input price$0.75/M tokens$0.1/M tokens
Output price$4.5/M tokens$0.4/M tokens
Context window400K tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedMar 2026Feb 2026
At 10M a month$7.50$7.50$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it3 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
Qwen3.5 Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.07 in·$0.26 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between GPT-5.4 Mini and Qwen3.5 Flash?

GPT-5.4 Mini is developed by OpenAI while Qwen3.5 Flash is developed by Qwen. GPT-5.4 Mini has a 400K token context window vs Qwen3.5 Flash's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Mini or Qwen3.5 Flash?

It depends on your use case. GPT-5.4 Mini and Qwen3.5 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.

How much does GPT-5.4 Mini cost compared to Qwen3.5 Flash?

GPT-5.4 Mini costs $0.75/M input tokens and Qwen3.5 Flash costs $0.1/M input tokens. Qwen3.5 Flash is $0.65/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 Qwen3.5 Flash on Rival?

This page shows a side-by-side comparison of GPT-5.4 Mini and Qwen3.5 Flash 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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