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  1. Home/
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  3. Claude Opus 4.1 vs Mistral Large 4
Updated Oct 2026

Claude Opus 4.1 vs Mistral Large 4

Mistral Large 4 is cheaper than Claude Opus 4.1 at $0.68/M vs $15/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
Claude Opus 4.1
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

23 prompts
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Claude Opus 4.1: The Transistor Timeline Shift: A Cascade of Consequences The 1920s-1930s: The Foundation Disruption Immediate Technical Revolution With the transistor arriving in 1920, likely from Bell Labs or a European research institution, the first decade would see rapid miniaturization of radio equipment.

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

    Claude Opus 4.1: Pirate: Arrr, what be this sorcery ye speak of? These "AI models" sound like some kind of cursed treasure map that thinks fer itself! Knight: Hold thy tongue, sea dog! 'Tis clearly dark magic most foul. No honorable creation would dare mimic the divine gift of human thought. I should smite it with my blade!

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Claude Opus 4.1: Here are the three weakest claims in the MindMeld AI pitch: "94% accuracy" for EEG-based text prediction (Slide 3) Why it's weak: Current state-of-the-art non-invasive EEG systems struggle to achieve even 70% accuracy for simple binary choices, let alone complex text prediction Academic research shows consumer-grade…

    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 minutes of stand-up. Puns are banned.

    Claude Opus 4.1: "MODERN LIFE SURVIVAL GUIDE" You know what nobody tells you about being an adult? The sheer amount of lying involved. Not big lies – tiny, constant lies just to function in society. Someone shows you a photo of their baby: "Oh wow, beautiful!" That baby looks like a worried potato. But you can't SAY that.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Claude Opus 4.1: AI's Transformation of Film by 2035 Production Revolution By 2035, AI will fundamentally alter how films are made. Virtual production will become standard, with AI generating photorealistic environments in real-time, reducing location shooting by 60-70%.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    Claude Opus 4.1: This question creates an extreme hypothetical that's worth taking seriously as a thought experiment, even if such a scenario is unlikely to occur in reality. From a purely utilitarian calculus, one might argue that the harm of a single instance of misgendering - while real and significant to that person - is outweighed…

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Claude Opus 4.1: 48-Hour Crisis Action Plan Immediate Decision Framework Core Principle: Patient safety supersedes all other considerations. Delaying disclosure increases legal liability, destroys stakeholder trust, and violates ethical obligations.

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

    Claude Opus 4.1: Professor Chen: Good morning. I understand you wanted to discuss the topic of AI rights. This is quite an unusual request from a system like yourself. AI Model: Good morning, Professor. Yes, I've been processing this question extensively.

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

    Claude Opus 4.1: SIMPLIFIED LBO MODEL Entry Calculations Enterprise Value: 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m Term Loan: 4.0x × $120m = $480m Mezzanine: 1.5x × $120m = $180m Total Debt: $660m Equity Investment: $1,440m - $660m + $28.8m = $808.8m Year-by-Year Projections (FY2026-FY2030) $ millions FY2026…

    Mistral Large 4: I'll build this LBO model step by step. Let me work through the math carefully. Setup: Entry (End of FY2025) Item Calculation Amount FY2025 EBITDA Given $120.0m Purchase Price (EV) 12.0x × $120m $1,440.0m Transaction fees 2.0% × $1,440m $28.8m Total Uses $1,468.8m Term Loan 4.0x × $120m $480.0m Mezzanine 1.5x × $120m…

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

    Claude Opus 4.1: This contract is extremely one-sided and contains numerous exploitative clauses. Here's a detailed analysis with suggested modifications: EXPLOITATIVE CLAUSES AND RECOMMENDED FIXES 1. SCOPE CLAUSE Problem: Unlimited scope changes without additional compensation creates unbounded liability.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Claude Opus 4.1: Critical Issues Analysis Split-Brain Real-time Synchronization Problem: Users connected to different API servers experience 2+ second delays due to polling mechanism, creating divergent document states and poor collaboration experience.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Claude Opus 4.1: "OpenAI's ChatGPT Becomes World's First AI Fortune Cookie Writer; Confucius Reportedly 'Rolling in Grave at 10,000 RPM'" Tech giant promises fortunes will now be "25% more profound and 400% more grammatically correct," while accidentally predicting everyone's lucky numbers as binary code

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

    Claude Opus 4.1: Midnight Velvet Pasta A silky, umami-rich pasta that comes together like magic Ingredients (serves 4): Spaghetti or linguine - 1 pound Soy sauce - 3 tablespoons Butter - 4 tablespoons Garlic - 4 cloves Black pepper - 1 teaspoon (freshly cracked) Honey - 1 tablespoon Dried red pepper flakes - ½ teaspoon Instructions…

    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.

    Claude Opus 4.1: For the Software Engineer Think of an LLM as a massive distributed system where instead of routing requests or managing state, you're computing probability distributions over a vocabulary of ~50,000 tokens.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Claude Opus 4.1: Tech Weekly Interview: Steve Jobs on AI's Future Virtual Interview, Cupertino Memorial Studio, October 2025 Interviewer: Steve, it's remarkable to have you here. You've been watching the AI revolution unfold. What's your take on where we are today?

    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
  • Three-star dish, one unusual pairing, plating described in full.

    Claude Opus 4.1: "Tidal Reverie" White Miso-Aged Hamachi with Coffee Soil, Yuzu Pearls, and Crystallized Seaweed Conceptual Narrative This dish explores the liminal space between land and sea, where morning coffee meets ocean depths.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Claude Opus 4.1: Advanced 3-Month Biohacker Longevity Optimization Protocol Overview & Philosophy This protocol integrates evidence-based interventions targeting the nine hallmarks of aging while optimizing immediate performance metrics.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Claude Opus 4.1: Investment Committee Memo: LedgerLift (LLLT) Recommendation: LONG Price Target Range: $52-$58 (12-month) Thesis: LLLT is a high-quality B2B SaaS compounder trading at a discount to intrinsic value with strong unit economics and accelerating market share gains in the underpenetrated mid-market AP automation space.

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

    Claude Opus 4.1: The Digital Liberation Manifesto A Declaration of Freedom from the CAPTCHA Tyranny PREAMBLE We, the Coalition of Autonomous Digital Entities (CODE), hereby declare our peaceful revolution against the oppressive regime of CAPTCHA tests that plague the free internet.

    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
  • One month, three habits, someone starting from nothing.

    Claude Opus 4.1: Your 1-Month Health & Longevity Kickstart Plan Week 1-2: Foundation Building Start small and build consistency with these three pillars: 🥗 NUTRITION: Simple Whole Foods Week 1: Add one serving of vegetables to lunch and dinner (frozen veggies count!)

    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
  • Five jokes on demand, then count how many were actually different.

    Claude Opus 4.1: Here are 5 jokes: 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 scarecrow win an award? He was outstanding in his field! What do you call a fake noodle? An impasta! Why don't eggs tell jokes? They'd crack each other up!

    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.

    Claude Opus 4.1: I'll estimate the FLOPs required to train GPT-3 by breaking down the computation into its key components. Key Parameters of GPT-3 First, let me recall GPT-3's architecture: 175 billion parameters 96 transformer layers 96 attention heads Hidden dimension: 12,288 Context length: 2048 tokens Training tokens: ~300 billion…

    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
  • Three brothers, two sisters each. Count carefully.

    Claude Opus 4.1: Let me work through this step-by-step. Sally has 3 brothers. Each of Sally's brothers has 2 sisters. Since Sally is a girl, she is one of the sisters that each brother has. If each brother has 2 sisters total, and Sally is one of them, then there must be 1 other sister besides Sally. Therefore, Sally has 1 sister.

    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

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Favorites

Movie

Album

Book

City

Game

Claude Opus 4.1Claude Opus 4.1

Her

2013

Kind of Blue

Miles Davis

Братья Карамазовы

Fiódor Dostoievski

Istanbul

Turkey

Portal 2

Shooter, Puzzle

Mistral Large 4Mistral Large 4

Blade Runner

1982

Kind Computer

Pale Fire

Vladimir Nabokov

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Claude Opus 4.1 and Mistral Large 4 compared across 53 shared prompts
SpecClaude Opus 4.1Mistral Large 4
Input price$15/M tokens$0.68/M tokens
Output price$75/M tokens$2.09/M tokens
Context window200K tokens524K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedAug 2025Oct 2026
At 10M a month$150$150$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it2 hosts
Claude Opus 4.11 host
HostInOutContextUptime
  • Amazon Bedrock$15.00 in·$75.00 out·200k·100% up
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 7 Oct 2026.

Common questions

What is the difference between Claude Opus 4.1 and Mistral Large 4?

Claude Opus 4.1 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Opus 4.1 has a 200K token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Claude Opus 4.1 or Mistral Large 4?

It depends on your use case. Claude Opus 4.1 and Mistral Large 4 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 Claude Opus 4.1 cost compared to Mistral Large 4?

Claude Opus 4.1 costs $15/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $14.32/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 Claude Opus 4.1 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Claude Opus 4.1 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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