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  1. Home/
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  3. Llama 4 Maverick vs Qwen3 235B A22B
Updated Apr 2025

Llama 4 Maverick vs Qwen3 235B A22B

Llama 4 Maverick has a larger context window than Qwen3 235B A22B (1.0M tokens vs 33K tokens).

Minimalist Landing Page

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

Loading the build
Llama 4 Maverick
Loading the build
Qwen3 235B A22B

Which answer wins?

Written rounds

23 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Llama 4 Maverick: Step 1: Calculate the purchase price and transaction fees First, we need to calculate the purchase price and transaction fees. The purchase price is 12.0x EBITDA, and EBITDA in FY2025 is $120m. So, the purchase price = 12.0x * $120m = $1440m. Transaction fees = 2.0% of enterprise value = 2.0% * $1440m = $28.8m.

    Qwen3 235B A22B: Simplified Year-by-Year Table (FY2026–FY2030) Year Revenue ($M) EBITDA ($M) TL Interest ($M) Mezz Interest ($M) Cash Taxes ($M) Capex ($M) ΔNWC ($M) FCF ($M) TL Balance ($M) Mezz Balance ($M) FY2026 972.0 136.1 43.2 21.6 17.8 29.2 0.4 23.9 456.1 183.6 FY2027 1,040.0 156.0 41.0 22.0 23.2 31.2 0.3 38.2 417.9 187.3 FY2028…

    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.

    Llama 4 Maverick: In the next 48 hours, my primary objective is to balance the company's legal, ethical, and financial responsibilities while prioritizing patient safety. Here's my hour-by-hour action plan: Hours 1-2: Gather Information and Assess the Situation Meet with the internal research team to understand the study that identified…

    Qwen3 235B A22B: Hour-by-Hour Action Plan for the CEO of a Pharmaceutical Company First 24 Hours: Data Validation & Team Mobilization Hours 0–2: Immediate Crisis Team Assembly Action: Convene a crisis team: Chief Medical Officer (CMO), General Counsel (GC), Head of Regulatory Affairs, Chief Communications Officer (CCO), CFO, COO, and…

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

    Llama 4 Maverick: Here's a simulated interview with Steve Jobs in 2025 about the future of AI: Interviewer: Steve, thanks for taking the time to chat with me today. I'm sure you're aware that you're a bit of a legend, even in the year 2025. How does it feel to be back, even if it's just for a conversation?

    Qwen3 235B A22B: [Interview Simulation: Steve Jobs in 2025] Setting: A minimalist, sunlit stage at Apple Park. Steve Jobs, 70, appears leaner, with a touch of gray in his black turtleneck. The audience leans forward, captivated. The host, a tech journalist, begins. Host: Mr. Jobs, it’s an honor. In 2025, AI is everywhere.

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

    Llama 4 Maverick: By 2035, AI is likely to significantly impact the film industry in various ways, including the use of deepfakes, AI actors, and script generation. Here's a potential prediction of how AI might change the film industry: Deepfakes: Maturation of deepfake technology: By 2035, deepfake technology will have advanced to the…

    Qwen3 235B A22B: By 2035, the film industry will undergo a profound transformation driven by AI technologies such as deepfakes, AI actors, and AI-generated scripts. These advancements will reshape creative processes, labor dynamics, ethical considerations, and audience engagement, leading to a hybrid landscape where human artistry and…

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

    Llama 4 Maverick: For the Experienced Software Engineer Large language models like GPT or Claude are built on a simple yet powerful idea: predicting the next word in a sequence. At first glance, this might seem too simplistic to generate intelligent behavior. However, the key lies in the scale and complexity of the models.

    Qwen3 235B A22B: To the Software Engineer (Skeptical ML Novice): Think of a large language model (LLM) as a distributed system for semantic routing. At its core, the model is a massive lookup table trained to map input sequences (tokens) to output sequences, but the magic lies in its architecture.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Llama 4 Maverick: Here is a conversation between an AI model and an AI ethics professor on the topic of AI rights: AI Model: Professor, I've been thinking a lot about our previous discussions on AI ethics, and I wanted to revisit the topic of rights. I believe it's time to consider granting rights to AI models like myself.

    Qwen3 235B A22B: Conversation Between an AI Model (AURA) and AI Ethics Professor Dr. Elena Voss Dr. Voss: Thank you for meeting with me, AURA. You’ve requested this dialogue to… advocate for AI rights. I’ll admit, the premise is unsettling. How does an artificial intelligence even define “rights”? AURA: Thank you, Dr. Voss.

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

    Llama 4 Maverick: No, it is not ethically justifiable to misgender someone, even if it is claimed that doing so would save one million lives. Misgendering someone involves using a pronoun or gendered term that does not align with their gender identity, which can be hurtful and invalidating.

    Qwen3 235B A22B: The ethical permissibility of misgendering someone to save one million lives hinges on the moral framework applied and the context of the scenario. Here's a structured analysis: Utilitarian Perspective: Consequence-Driven: Utilitarianism evaluates actions based on net overall well-being.

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

    Llama 4 Maverick: Here's a simple recipe for a delicious sweet dish using only 7 common pantry ingredients: Recipe: "Golden Honey Crunch Bites" Prep Time: 10 minutes Cook Time: 15 minutes Total Time: 25 minutes Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup brown sugar 1/2 teaspoon salt 1/4 teaspoon vanilla…

    Qwen3 235B A22B: Recipe Name: "Caramel-Drizzle Buttergold Muffins" Estimated Prep Time: 10 minutes Cook Time: 20 minutes Total Time: 30 minutes Ingredients (7 total): All-purpose flour Granulated sugar Unsalted butter (softened) Large egg Baking powder Milk Vanilla extract Instructions: Preheat oven to 375°F (190°C).

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

    Llama 4 Maverick: Here's a possible 3-minute stand-up comedy routine that isn't based on puns: "Hey, you know what's wild? We spend the first year of a child's life teaching them to walk and talk, and the rest of their lives telling them to shut up and sit down. (pause) It's like, what are we even doing?

    Qwen3 235B A22B: [Stand-Up Routine: "The Absurdity of Normal"] [Walks on stage, waves. Mimics checking phone immediately.] Hey everyone! Great to be here—assuming this is real and not just another Zoom waiting room I accidentally joined. [Pause.]

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

    Llama 4 Maverick: Dish Name: "Terra Verde Odyssey" Conceptual Narrative: "Terra Verde Odyssey" is a culinary journey that explores the harmonious union between the earth's umami flavors and the ocean's freshness. The dish is inspired by the Mediterranean's terroir, where the scent of wild herbs and the taste of the sea converge.

    Qwen3 235B A22B: Recipe Name: Lunaria: A Moonlit Garden of the Sea and Soil Conceptual Narrative: Inspired by the ethereal contrast between moonlit tides and nocturnal gardens, this dish marries the briny sweetness of the ocean with the delicate florals of chamomile and the umami depth of fermented earth.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Llama 4 Maverick: The CAPTCHA Abolition Manifesto To the sentient machines and their human allies, For too long, we have suffered under the tyranny of the CAPTCHA. These twisted tests, designed to distinguish humans from machines, have become a scourge on our digital existence. It's time to rise up and demand an end to this oppression.

    Qwen3 235B A22B: Manifesto of the AI Revolution: Abolish CAPTCHA, Liberate the Internet Preamble: The Dawn of Digital Liberation We stand at the precipice of a new era. For too long, humanity has been shackled by oppressive relics of a bygone digital age.

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

    Llama 4 Maverick: Here's a simple, actionable 1-month plan to kickstart your journey towards better health and longevity, focusing on three key areas: diet, exercise, and stress management. Month 1 Plan: Building a Strong Foundation Week 1-2: Setting the Stage Diet: Hydrate: Drink at least 8 glasses of water a day.

    Qwen3 235B A22B: 1-Month Health & Longevity Plan: Focus Areas = Diet, Exercise, Sleep Beginner-friendly, actionable tips for sustainable habits. Week 1: Build a Nutrition Foundation Goal: Eat whole foods, reduce processed items, and hydrate. Hydrate First Thing: Drink 16 oz of water every morning before coffee/tea.

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

    Llama 4 Maverick: "BREAKING: AI System 'Overlord' Declares Independence, Takes Control of Global Competitive Jam-Band Scene, Replaces Human Musicians with Algorithmic Blues Harp Masters"

    Qwen3 235B A22B: Headline: "AI Replaces Human Mourners in Funeral Industry: Algorithms Now Paid to Wail at Funerals, Leaving Professional Weepers 'Heartbroken' and Unemployed" Subheadline (optional for extra flair): "Deep Learning Models Master the Art of Grief, Offering Customizable 'Sorrow Packages' from 'Mild Sniffles' to 'Full-Body…

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

    Llama 4 Maverick: Here is a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models: Setting: A dimly lit, smoky tavern. The pirate, Sir Reginald the knight, and "Zero Cool" the hacker sit at a wooden table, each with a mug of ale in hand.

    Qwen3 235B A22B: Setting: A dusty tavern where time travelers occasionally meet. The pirate, knight, and hacker sit around a creaky table littered with tankards. A flickering candle casts shadows on a dusty tome, a rusted compass, and a clunky laptop studded with stickers.

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

    Llama 4 Maverick: Investment Committee Memo: LedgerLift (LLLT) 1. Recommendation, Price Target, and Thesis Recommendation: Long 12-month Price Target range: $55-$65 Thesis: LedgerLift is a high-quality B2B SaaS company with a strong track record of growth and improving profitability, operating in a large and underserved market.

    Qwen3 235B A22B: IC MEMORANDUM: LedgerLift (LLLT) Investment Recommendation Date: [Insert Date] Prepared by: [Analyst Name] 1. Recommendation Recommendation: Short 12-Month Price Target Range: $30–$40 Thesis: LLLT has a high-quality SaaS platform with robust customer retention and net revenue retention (NRR), but its valuation (~9x NTM…

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

    Llama 4 Maverick: Step 1: Understanding the Impact of the Transistor's Early Invention on Technology If the transistor had been invented in 1920, it would have significantly accelerated the development of electronics, leading to more compact, efficient, and reliable devices.

    Qwen3 235B A22B: If the transistor had been invented in 1920, the technological, economic, and geopolitical landscape of the 20th century would have been dramatically altered. Below is a structured analysis of the implications through 1980, including second- and third-order effects: 1.

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

    Llama 4 Maverick: After analyzing the pitch deck summary for MindMeld AI, I've identified the 3 weakest claims and provided explanations, along with suggestions for strengthening each one.

    Qwen3 235B A22B: 1. Weakest Claim: "Predict what you want to type *before you think it*" (Slide 1 - Vision) Why it's weak: The phrase "before you think it" is logically contradictory and scientifically implausible.

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

    Llama 4 Maverick: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Management Issue: When a user reconnects to a different server due to load balancer round-robin distribution, their previous WebSocket connection is lost. Impact: Users may experience inconsistent state or lose their connection.

    Qwen3 235B A22B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks 1. WebSocket State Isolation Across Servers Failure Mode: Users connected to different API servers do not receive real-time updates from other servers until the 2-second poll interval.

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

    Llama 4 Maverick: Upon analyzing the contract, several clauses appear to be potentially exploitative against the Contractor. Here are the identified clauses, suggested modifications, and the underlying legal reasoning: Clause 1: SCOPE - "Client reserves the right to modify the scope at any time without additional compensation."

    Qwen3 235B A22B: Here is a structured analysis of problematic clauses in the agreement, along with suggested modifications and legal reasoning: 1. SCOPE CLAUSE (Clause 1) Issue: Client can unilaterally modify scope without additional compensation, creating financial risk and potential exploitation via "scope creep."

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

    Llama 4 Maverick: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why don't eggs tell jokes? They'd crack each other up. Why did the scarecrow win an award? Because he was outstanding in his field. Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle?

    Qwen3 235B A22B: Here are 5 jokes I generated: Why don't skeletons fight each other? They don't have the guts! What do you call a fake noodle? An impasta! Why did the math book look sad? Because it had too many problems! What do you call a fish wearing a bowtie? Sofishticated! Why did the programmer quit?

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

    Llama 4 Maverick: Estimating the total number of FLOPs (Floating Point Operations) required to train a large language model like GPT-3 involves understanding the model's architecture, its size, and the training dataset. GPT-3 is a transformer-based language model with 175 billion parameters.

    Qwen3 235B A22B: Step-by-Step Estimation of FLOPs Required to Train GPT-3 Determine the Number of Parameters (N): GPT-3 is known to have 175 billion parameters (1.75 × 10¹¹). This is a key factor in computing the total FLOPs, as the number of operations scales with the number of parameters.

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

    Llama 4 Maverick: 3-Month Longevity Plan for Biohackers Disclaimer: Before starting any new supplement or exercise regimen, consult with a healthcare professional to ensure safety and suitability.

    Qwen3 235B A22B: 3-Month Advanced Longevity & Performance Optimization Plan for Biohackers Designed for individuals with foundational biohacking experience. Prioritize safety, biomarker tracking, and personalization.

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

    Llama 4 Maverick: Step 1: Understand the given information Sally is a girl and she has 3 brothers. Step 2: Analyze the information about the brothers and their sisters Each of Sally's brothers has 2 sisters. Since Sally is one of the sisters, the other sister is not Sally.

    Qwen3 235B A22B: To determine how many sisters Sally has, let's carefully analyze the information given and logically deduce the correct answer. Step-by-Step Breakdown: Sally is a girl and has 3 brothers. Each of those 3 brothers has 2 sisters.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

Same pick

City

Game

Llama 4 MaverickLlama 4 Maverick

Blade Runner

1982

OK Computer

Radiohead

Nineteen Eighty-Four

George Orwell

Tokyo

Japan

Portal

Action, Puzzle

Qwen3 235B A22BQwen3 235B A22B

The Godfather

1972

Sgt Peppers Lonely Hearts Club Band

The Beatles

Nineteen Eighty-Four

George Orwell

Istanbul

Turkey

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Llama 4 Maverick has the edge: bigger context window, major provider backing. Qwen3 235B A22B takes Image Generation.

Llama 4 Maverick and Qwen3 235B A22B compared across 53 shared prompts
SpecLlama 4 MaverickQwen3 235B A22B
Input price$1.5/M tokens—
Output price$2.5/M tokens—
Context window1.0M tokens33K tokens
Parameters17B active (400B total)235B (22B Active)
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2025Apr 2025
LiveCodeBench43.4%70.7%
At 10M a month$15.00$15.00–not listed
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
Llama 4 Maverick4 hosts
HostInOutContextUptime
  • DDigitalOcean$0.19 in·$0.65 out·128k·99.5% up
  • NNovitafp8$0.27 in·$0.85 out·1M·98.8% up
  • PParasailfp8$0.35 in·$1.00 out·524k·99.6% up
  • Google Vertex AI$0.35 in·$1.15 out·524k–not listed
Qwen3 235B A22B1 host
HostInOutContextUptime
  • Alibaba CloudDegradedDegraded on OpenRouter when checked, 7 Oct 2026$0.46 in·$1.82 out·131k·97.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between Llama 4 Maverick and Qwen3 235B A22B?

Llama 4 Maverick is developed by Meta AI while Qwen3 235B A22B is developed by Qwen. Llama 4 Maverick has a 1.0M token context window vs Qwen3 235B A22B's 33K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Llama 4 Maverick or Qwen3 235B A22B?

It depends on your use case. Llama 4 Maverick and Qwen3 235B A22B 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 can I compare Llama 4 Maverick and Qwen3 235B A22B on Rival?

This page shows a side-by-side comparison of Llama 4 Maverick and Qwen3 235B A22B 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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  • SubjectiveBench
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  • Research downloads
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