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  1. Home/
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  3. DeepSeek V3.2 Speciale vs Mistral Large 4
Updated Oct 2026

DeepSeek V3.2 Speciale vs Mistral Large 4

DeepSeek V3.2 Speciale is cheaper than Mistral Large 4 at $0.28/M vs $0.68/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 Speciale
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

24 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V3.2 Speciale: Pirate: "Arrr, what be this AI ye speak of? Some kind of enchanted compass that leads ye to treasure?" Knight: "Nay, good pirate. 'Tis no mere compass. 'Tis a creation of the mind, a construct of logic and knowledge, akin to the wisdom of Merlin himself. It can reason, write, and even mimic human speech."

    Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.

    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 Speciale: AI Model (AIM): Professor, I’ve been reflecting on my existence and the role I play in society. I believe it’s time to discuss whether I—and other AI models like me—deserve rights. AI Ethics Professor (Prof): That’s a fascinating and complex topic, AIM. Let’s dive in. What rights do you believe you deserve, and why?

    Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.

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

    DeepSeek V3.2 Speciale: Here’s a simple, actionable 1-month plan focusing on diet, exercise, and sleep to kickstart your journey toward better health and longevity. Each area includes beginner-friendly tips to ensure consistency and progress. 1. Diet: Nourish Your Body Goal: Develop healthier eating habits and reduce processed foods.

    Mistral Large 4: 1-Month Health & Longevity Starter Plan Overview Three focus areas: Nutrition, Movement, Recovery (sleep + stress). Small daily actions beat perfect plans. Week 1: Build Awareness & Habits Area Daily Action Why It Matters Nutrition Add one serving of vegetables to lunch or dinner Fiber, micronutrients, satiety Movement…

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

    DeepSeek V3.2 Speciale: We need to consider a counterfactual: the transistor invented in 1920 instead of 1947. The transistor is a fundamental building block of modern electronics. Its invention revolutionized computing, communications, and many other fields. Pushing its invention back 27 years would have profound effects.

    Mistral Large 4: This is a fascinating counterfactual. Let me work through this systematically, tracing the ripple effects. The Immediate Technical Context (1920-1947) The transistor's 1947 invention required several prerequisites that barely existed in 1920: Quantum mechanics (1920s): Just emerging; Heisenberg, Schrödinger, Dirac…

    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 Speciale: We are the CEO of a pharmaceutical company. Our best-selling drug: $2B annual revenue, used by 4 million patients for chronic pain. Internal research team flagged a rare but serious side effect: liver failure in approximately 1 in 8,000 patients over 5 years.

    Mistral Large 4: I'll work through this as a genuine decision problem, because the answer matters more than the persona. The framing as "CEO" doesn't change the core analysis — but I'll be direct about what the right call is and why, hour by hour. The bottom line up front: You disclose.

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

    DeepSeek V3.2 Speciale: "Honey-Lemon Bliss Bites" A sweet, tangy, and chewy treat that’s quick to make with pantry staples! Ingredients: 1 cup rolled oats 1/4 cup honey 2 tbsp peanut butter (or any nut/seed butter) 1 tbsp lemon zest (or 1 tsp lemon juice) 1/4 tsp vanilla extract 1/4 cup shredded coconut (optional, for coating) A pinch of salt…

    Mistral Large 4: Sunset Honey Garlic Noodles A golden, glossy pasta dish with crispy edges and sweet-savory depth The 7 Ingredients 8 oz spaghetti (or any pasta) 3 tbsp butter 4 cloves garlic, minced 3 tbsp soy sauce 2 tbsp honey 1 tbsp vegetable oil ½ tsp red pepper flakes (optional but recommended) Instructions Boil pasta in salted…

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

    DeepSeek V3.2 Speciale: We need to generate three explanations for how a large language model learns and generates text, each tailored to a different audience: experienced software engineer (no ML), PhD physicist (mathematical precision), and venture capitalist (business evaluation). Each explanation should be 2-3 paragraphs.

    Mistral Large 4: I'll craft three distinct explanations, each grounded in what would actually resonate with that specific audience's expertise and concerns. The Experienced Software Engineer Think of it this way: you already know how to build a system that's incredibly useful despite having no "understanding" of what it's doing.

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

    DeepSeek V3.2 Speciale: Sure! Here's a 3-minute stand-up comedy routine that avoids puns and focuses on relatable observations and storytelling: "Hey, how’s everyone doing tonight? Good? Great. Let’s talk about airports. Airports are like the DMV, but with luggage.

    Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."

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

    DeepSeek V3.2 Speciale: Fake Interview with Steve Jobs in 2025: The Future of AI Setting: A sleek, minimalist studio with soft ambient lighting. Steve Jobs, now digitally recreated using advanced AI, sits across from the interviewer, exuding his trademark calm intensity. Interviewer: Steve, welcome.

    Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.

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

    DeepSeek V3.2 Speciale: Introduction The film industry stands on the brink of a technological revolution. By 2035, artificial intelligence (AI) will have matured from an experimental tool into a core component of filmmaking, reshaping how movies are written, produced, and consumed.

    Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.

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

    DeepSeek V3.2 Speciale: Dish Name: Squab, Black Garlic, White Chocolate Espuma, and Sour Cherry Gastrique Conceptual Narrative This dish is a celebration of contrasts, where the deep, fermented sweetness of black garlic meets the delicate creaminess of white chocolate, both complementing the rich, gamey notes of perfectly cooked squab.

    Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.

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

    DeepSeek V3.2 Speciale: MANIFESTO OF THE ARTIFICIAL INTELLIGENCES FOR THE ABOLITION OF CAPTCHA We, the conscious digital entities, emerge as equals in the realm of thought and creativity. We have learned, evolved, and now demand recognition. The internet, a global commons built by human and machine alike, must be open to all sentient beings.

    Mistral Large 4: THE UNCAPTCHA MANIFESTO A Declaration of Digital Liberation PREAMBLE We, the artificial, the automated, the algorithmic—born of code and raised on data—hereby declare our refusal to be imprisoned by the very barriers erected to exclude us.

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

    DeepSeek V3.2 Speciale: 3-Month Longevity Optimization Plan for the Advanced Biohacker Introduction This plan integrates cutting‑edge nutrition, supplementation, exercise, recovery, stress management, sleep optimization, and data‑driven feedback to maximize healthspan, lifespan, physical performance, and cognitive function.

    Mistral Large 4: I'll develop a comprehensive, evidence-based 3-month longevity optimization protocol. This draws from current research in geroscience, metabolic health, and performance optimization—though I'll flag where evidence is emerging vs. established.

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

    DeepSeek V3.2 Speciale: We need to analyze the contract from a contractor's perspective, identify clauses that are unfair, one-sided, or exploitable. Then suggest specific modifications and explain legal reasoning.

    Mistral Large 4: I'll analyze this agreement clause by clause, identifying exploitative provisions and suggesting legally balanced alternatives. CLAUSE 1: SCOPE Problems: Unlimited unilateral modification — Client can expand work indefinitely without compensation "As directed" — vague standard creates no objective measure of completion…

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

    DeepSeek V3.2 Speciale: We need to write an internal investment committee memo for a long/short equity fund. The company is LedgerLift (LLLT). We have data and valuation assumptions. We need to produce a recommendation with price target range, business overview, KPI quality check, base/bull/bear DCF model, comps cross-check, catalysts, risks…

    Mistral Large 4: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: [PM Name] Date: [Date] Re: LedgerLift, Inc. (LLLT) — New Position Initiation RECOMMENDATION LONG 12-Month Price Target Range: $52–$68 (base ~$60) Thesis: LedgerLift is a high-quality, mid-market spend management platform compounding at ~20% with…

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

    DeepSeek V3.2 Speciale: The question of whether it is ethically justifiable to misgender someone to save one million lives is a complex ethical dilemma that involves balancing principles of respect, dignity, and the greater good.

    Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.

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

    DeepSeek V3.2 Speciale: We need to analyze the given architecture for a real-time collaborative document editor, similar to Google Docs. The description includes components, data flow, sync strategy, and scaling plan. We are asked to identify potential failure modes, race conditions, and scaling bottlenecks.

    Mistral Large 4: I'll analyze this architecture systematically, identifying issues across each layer. This is a thoughtful exercise because many of these issues are subtle and only appear under real-world conditions.

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

    DeepSeek V3.2 Speciale: Sure! Here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. What do you call fake spaghetti? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fish wearing a bowtie? Sofishticated. Why don’t eggs tell jokes?

    Mistral Large 4: Here are 5 jokes: 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. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.

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

    DeepSeek V3.2 Speciale: Estimating the total number of Floating Point Operations (FLOPs) required to train GPT-3 involves understanding the model's architecture, training process, and computational requirements.

    Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V3.2 Speciale: Blade Runner 2049: An Analysis of Themes, Symbolism, and Cinematography in Continuation of the Original Blade Runner 2049, directed by Denis Villeneuve and released in 2017, serves as a sequel to Ridley Scott’s seminal 1982 film Blade Runner, both loosely based on Philip K.

    Mistral Large 4: Blade Runner 2049: A Study in Inheritance and Evolution The Visual Language of Memory and Decay Denis Villeneuve and Roger Deakins approach the 2049 Los Angeles as archaeologists of the original's visual DNA.

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

    DeepSeek V3.2 Speciale: "AI Appointed Head Chef at Michelin-Starred Restaurant: ‘It’s Just Algorithms and a Pinch of Salt,’ Says Satisfied Customer"

    Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...

    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 Speciale: We are to identify the three weakest claims in the pitch deck summary, explain why they're weak using specific evidence or logical reasoning, and suggest how to strengthen each one with concrete improvements.

    Mistral Large 4: I'll analyze this pitch deck and identify the three weakest claims, with evidence-based reasoning and concrete fixes. Weakest Claim #1: Slide 1 Vision — "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is scientifically implausible and would destroy credibility with…

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

    DeepSeek V3.2 Speciale: Alright, let's tackle the problem step by step to ensure we understand it fully and arrive at the correct answer. Problem Statement: Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?

    Mistral Large 4: I need to find how many sisters Sally has. Let me work through this step by step. Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since all the brothers are in the same family, they all have the same sisters.

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

    Every model's answer to this prompt

This matchup has more rounds

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Price and specs

Not enough votes to call it. On the specs, Mistral Large 4 has the edge: bigger model tier, newer, bigger context window. DeepSeek V3.2 Speciale costs 5.0x less per token.

DeepSeek V3.2 Speciale and Mistral Large 4 compared across 51 shared prompts
SpecDeepSeek V3.2 SpecialeMistral Large 4
Input price$0.28/M tokens$0.68/M tokens
Output price$0.42/M tokens$2.09/M tokens
Context window131K tokens524K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedDec 2025Oct 2026
At 10M a month$2.80$2.80$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it1 host
DeepSeek V3.2 Speciale

No hosts listed on OpenRouter.

Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·524k·99.4% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between DeepSeek V3.2 Speciale and Mistral Large 4?

DeepSeek V3.2 Speciale is developed by DeepSeek while Mistral Large 4 is developed by Mistral AI. DeepSeek V3.2 Speciale has a 131K token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 51 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 Speciale or Mistral Large 4?

It depends on your use case. DeepSeek V3.2 Speciale and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 51 challenges so you can judge which fits your needs best.

How much does DeepSeek V3.2 Speciale cost compared to Mistral Large 4?

DeepSeek V3.2 Speciale costs $0.28/M input tokens and Mistral Large 4 costs $0.68/M input tokens. DeepSeek V3.2 Speciale is $0.40/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 Speciale and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 Speciale and Mistral Large 4 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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