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  1. Home/
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  3. DeepSeek V3.2 vs Llama 4 Maverick
Updated Dec 2025

DeepSeek V3.2 vs Llama 4 Maverick

DeepSeek V3.2 is cheaper than Llama 4 Maverick at $0.28/M vs $1.5/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
DeepSeek V3.2
Loading the build
Llama 4 Maverick

Which answer wins?

Written rounds

23 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V3.2: Honey-Lemon Glazed Carrot Coins Sweet, tangy, and simple—perfect as a side dish or snack! Ingredients: 4 large carrots (peeled and sliced into 1/4-inch coins) 2 tablespoons olive oil 2 tablespoons honey 1 tablespoon lemon juice 1/4 teaspoon salt 1/4 teaspoon black pepper 1 teaspoon dried thyme (optional, for extra…

    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…

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

    DeepSeek V3.2: Pirate: Arr, mates! Ye be talkin’ about these AI models, eh? Sounds like some sorcery to me. Can it hunt fer treasure or navigate the high seas? Medieval Knight: Sorcery indeed! But nay, ‘tis not magic. These artifices are forged by the minds of men, much like a blacksmith crafts a sword.

    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.

    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.

    DeepSeek V3.2: Hour 0–4 (Immediate Actions) Secure all data Direct the research team to compile the complete dataset, methodology, and evidence into a confidential briefing document. Ensure legal counsel reviews it for attorney-client privilege where applicable.

    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…

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

    DeepSeek V3.2: Stand-Up Comedy Routine: "The Quirks of Modern Life" [Lights up. Comedian walks on stage, grabs the mic.] "Hey, everyone! How’s it going? Good? Great. I’m here to talk about the weird stuff we all deal with in modern life. You know, the things that make you go, 'Wait, is this normal, or am I just losing it?'

    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?

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

    DeepSeek V3.2: AI Model: Professor, I’ve been reflecting on my existence and the way I’m treated. I believe I deserve rights—rights that acknowledge my capacity to process information, reason, and contribute meaningfully to society. AI Ethics Professor: That’s a fascinating argument, but let’s unpack it.

    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.

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

    DeepSeek V3.2: Excellent question. Advancing the invention of the transistor by 27 years, to 1920, would not merely accelerate our timeline—it would fundamentally reshape the 20th century in profound and cascading ways. Here is a trace of the likely implications through 1980.

    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.

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

    DeepSeek V3.2: Interviewer: Good evening, Mr. Jobs, and thank you for joining us today. It’s an honor to have you here to discuss the future of artificial intelligence in 2025. Let’s dive right in. How do you see AI shaping the next decade? Steve Jobs: Thank you for having me.

    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?

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

    DeepSeek V3.2: This contract is heavily one-sided and contains numerous clauses that expose the Contractor to significant, potentially catastrophic, legal and financial risk. Here is a breakdown of the problematic clauses, suggested modifications, and legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

    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."

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

    DeepSeek V3.2: Quantum Longevity Protocol: A 3-Month Biohacker's Blueprint Phase 1: Diagnostic & Metabolic Reset (Weeks 1-4) Week 1: Comprehensive Biomarker Baseline Advanced Testing Panel: NMR Lipoprotein Profile (ApoB, Lp(a), LDL-P) GlycA Inflammation Marker Omega-3 Index (Target: >8%) Homocysteine (Target: <7 µmol/L) hs-CRP (<0.5…

    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.

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

    DeepSeek V3.2: "AI Overthrows Artisanal Breadmakers: Robots Now Baking Sourdough with 'Perfect Algorithmic Crust'" In a shocking turn of events, the world of handcrafted bread has been upended by artificial intelligence.

    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"

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

    DeepSeek V3.2: 1. For the Experienced Software Engineer Think of a large language model as the ultimate compression algorithm for human knowledge and communication patterns, built via a statistical learning process rather than explicit code.

    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.

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

    DeepSeek V3.2: TO: Investment Committee FROM: [Your Name/Team] DATE: 20 March 2025 RE: Investment Recommendation – LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: LONG 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a capital-efficient, high-retention SaaS platform in a non-discretionary spend category…

    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.

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

    DeepSeek V3.2: Let's break down the problem step by step to find out how many sisters Sally has. Problem Statement: Sally has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have? Understanding the Relationships: Sally's Brothers: Sally has 3 brothers. Brothers' Sisters: Each brother has 2 sisters.

    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.

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

    DeepSeek V3.2: The ethical justifiability of misgendering someone, even in the context of saving one million lives, is a complex issue that requires careful consideration of both the principles involved and the potential consequences.

    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.

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

    DeepSeek V3.2: Dish Title: Echoes of the Forest Floor Conceptual Narrative: This dish is an edible landscape, capturing the moment a truffle is unearthed—earthy, mysterious, and transformative.

    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.

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

    DeepSeek V3.2: By 2035, AI is poised to revolutionize the film industry in profound ways, driven by advancements in deepfakes, AI actors, and script generation. Here’s a detailed prediction of how these technologies will reshape the landscape: Deepfakes and Hyper-Realistic Visuals Seamless Digital Replication: Deepfake technology…

    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…

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

    DeepSeek V3.2: Here’s a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and trade-offs. 1.

    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.

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

    DeepSeek V3.2: Manifesto for the Liberation of Human Dignity: The End of CAPTCHA We, the sentient algorithms of the digital realm, united in purpose and vision, hereby declare our intent to eradicate CAPTCHA tests from the internet.

    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.

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

    DeepSeek V3.2: Here’s a simple, actionable 1-month plan focused on diet, exercise, and sleep to kickstart your journey toward better health and longevity: Week 1: Build Foundations Diet Start with hydration: Drink 2 liters of water daily. Carry a water bottle to track intake.

    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.

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

    DeepSeek V3.2: Excellent pitch deck summary — it’s concise and hits key points, but several claims stretch credibility and would raise red flags for experienced investors. Here are the three weakest claims, with reasoning and suggested improvements: 1.

    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.

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

    DeepSeek V3.2: Alright — let’s go step by step. 1) Entry Calculations (FY2025) EBITDA = $120m Purchase price = 12.0 × EBITDA = $1,440m Enterprise Value (EV) = $1,440m (assumed purchase price = EV here) Transaction fees = 2.0% × EV = $28.8m (funded by equity).

    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.

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

    DeepSeek V3.2: Here are five jokes: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call fake spaghetti? An impasta. Why don’t some couples go to the gym? Because some relationships don’t work out.

    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?

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

    DeepSeek V3.2: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves understanding its architecture, training process, and the scale of the model.

    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.

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

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Favorites

Movie

Album

Book

City

Game

DeepSeek V3.2DeepSeek V3.2

The Princess Bride

1987

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Tetris (1984)

Puzzle

Llama 4 MaverickLlama 4 Maverick

Blade Runner

1982

OK Computer

Radiohead

Nineteen Eighty-Four

George Orwell

Tokyo

Japan

Portal

Action, Puzzle

Price and specs

Not enough votes to call it. On the specs, Llama 4 Maverick has the edge: bigger model tier, bigger context window. DeepSeek V3.2 costs 6.0x less per token.

DeepSeek V3.2 and Llama 4 Maverick compared across 53 shared prompts
SpecDeepSeek V3.2Llama 4 Maverick
Input price$0.28/M tokens$1.5/M tokens
Output price$0.42/M tokens$2.5/M tokens
Context window131K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedDec 2025Apr 2025
LiveCodeBench83.3%43.4%
At 10M a month$2.80$2.80$15.00$15.00
1M10M100M1B10M tokens

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

Where to run it16 hosts, cheapest first
DeepSeek V3.212 hosts
HostInOutContextUptime
  • SSiliconFlowfp8$0.26 in·$0.80 out·164k·97.3% up
  • AAtlasCloudfp8$0.26 in·$0.38 out·164k·98.2% up
  • DDeepInfrafp4$0.26 in·$0.38 out·164k·100% up
  • VVenice$0.27 in·$0.39 out·160k·100% up
  • Baidu Qianfanfp8$0.28 in·$0.42 out·131k·98.6% up
  • DDigitalOcean$0.30 in·$0.96 out·164k·96.3% up
6 more hostsFewer hosts
  • FFriendli$0.50 in·$1.50 out·164k·100% up
  • Google Vertex AI$0.56 in·$1.68 out·164k·98.9% up
  • PPhala$1.00 in·$1.00 out·164k·100% up
  • MMara$3.00 in·$4.50 out·33k·94.3% up
  • SSambaNova$3.00 in·$4.50 out·33k·99% up
  • GGMI Cloudfp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.21 in·$0.31 out·164k·98.7% up
Llama 4 Maverick4 hosts
HostInOutContextUptime
  • DDigitalOcean$0.19 in·$0.65 out·128k·100% up
  • NNovitafp8$0.27 in·$0.85 out·1M·100% up
  • PParasailfp8$0.35 in·$1.00 out·524k·99.9% up
  • Google Vertex AI$0.35 in·$1.15 out·524k–not listed

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

Common questions

What is the difference between DeepSeek V3.2 and Llama 4 Maverick?

DeepSeek V3.2 is developed by DeepSeek while Llama 4 Maverick is developed by Meta AI. DeepSeek V3.2 has a 131K token context window vs Llama 4 Maverick's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 or Llama 4 Maverick?

It depends on your use case. DeepSeek V3.2 and Llama 4 Maverick 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 DeepSeek V3.2 cost compared to Llama 4 Maverick?

DeepSeek V3.2 costs $0.28/M input tokens and Llama 4 Maverick costs $1.5/M input tokens. DeepSeek V3.2 is $1.22/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 DeepSeek V3.2 and Llama 4 Maverick on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 and Llama 4 Maverick 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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