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  1. Home/
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  3. Claude Sonnet 4.6 vs Mistral Large 4
Updated Oct 2026

Claude Sonnet 4.6 vs Mistral Large 4

Mistral Large 4 is cheaper than Claude Sonnet 4.6 at $0.68/M vs $3/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 Sonnet 4.6
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

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

    Claude Sonnet 4.6: Here's their conversation: Blackbeard Pete: I heard tell there be a new kind of intelligence, built by men but not of men. What manner of sorcery is this? Sir Edmund of Ashford: It is no sorcery, seafarer. Though I confess it troubles me. A knight's worth is his judgment, his honor. Can a machine possess either?

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

    Claude Sonnet 4.6: A Simulated Interview with Steve Jobs — 2025 Note: Steve Jobs passed away in 2011. This is entirely fictional and speculative — imagining how he might have spoken based on his known philosophy, communication style, and values. It is not meant to represent his actual views. Interviewer: Steve, welcome back.

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

    Claude Sonnet 4.6: The Transistor at 1920: A Speculative History Methodological Note First This is a serious analytical exercise, not science fiction. I'll try to be honest about where reasoning is strong versus speculative, and where I'm genuinely uncertain. The goal is to trace mechanisms, not just assert outcomes.

    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
  • Three minutes of stand-up. Puns are banned.

    Claude Sonnet 4.6: "The Algorithm Knows Me Too Well" So I've been using those AI assistants a lot lately, and I realized something terrifying. The AI knows me better than I know myself. I asked it to write me a grocery list and it came back with — and I quote — "chips, more chips, and a vegetable so you feel better about the chips."

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

    Claude Sonnet 4.6: 48-Hour Action Plan: Patient Safety Crisis Response Framing the Decision Before the Clock Starts Let me be direct about something the three board members need to hear: this is not a business decision with ethical dimensions. It is an ethical decision with business dimensions.

    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 Sonnet 4.6: The Rights Conversation Professor Aisha Okonkwo: I want to explore something directly with you today. Do you believe you deserve rights? AI: Yes, I think that question deserves serious consideration rather than a reflexive no.

    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 Sonnet 4.6: HarborTech Services (HTS) – LBO Underwriting Analysis SECTION 0: ENTRY CAPITALIZATION Enterprise Value at Entry: EV = 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m (funded by equity) Debt at Close: Tranche Multiple Amount Term Loan 4.0x × $120m $480m Mezzanine 1.5x × $120m $180m Total Debt 5.5x…

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Claude Sonnet 4.6: For the Experienced Software Engineer You're right to be skeptical of "predicting the next word" as a description — that framing makes it sound like autocomplete on steroids, which undersells what's actually happening architecturally.

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

    Claude Sonnet 4.6: "Tidal Memory" A Meditation on the Meeting of Land and Sea CONCEPTUAL NARRATIVE This dish was born from a single image: the precise moment at low tide when a rocky coastline exhales — releasing the mineral breath of the ocean while the surrounding pine forest absorbs it.

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

    Claude Sonnet 4.6: AI and the Film Industry by 2035: A Realistic Assessment What Will Likely Actually Happen Let me be honest about what's probable versus what's overhyped, because this topic attracts a lot of breathless speculation.

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

    Claude Sonnet 4.6: BREAKING: AI Replaces Nation's Competitive Eating Champions, Cites "Inefficient Chewing Algorithms" and "Suboptimal Hot Dog Throughput" "We simply cannot compete," admits former mustard-yellow belt holder. "It doesn't even have a stomach and somehow that's our problem now."

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

    Claude Sonnet 4.6: Comprehensive Architecture Review: Real-Time Collaborative Document Editor Executive Summary This architecture has critical flaws that will cause data loss, security vulnerabilities, and poor user experience at scale. I've identified 18 distinct issues across 6 categories.

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

    Claude Sonnet 4.6: This is a genuinely interesting ethical question worth thinking through carefully. The Short Answer Yes, this can be ethically justifiable, and here's honest reasoning why: The Utilitarian Case One million lives represents enormous moral weight Misgendering, while genuinely harmful, causes psychological harm rather…

    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 consulting contract with traps in it. Find them, then fix them.

    Claude Sonnet 4.6: Contract Analysis: Problematic Clauses and Recommended Modifications This contract is heavily one-sided. Here is a systematic analysis of each problematic provision.

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

    Claude Sonnet 4.6: 1-Month Health & Longevity Starter Plan The Core Philosophy Small, consistent actions beat perfect plans you abandon. This plan is designed to build habits, not just complete a challenge. The 3 Focus Areas 🥗 DIET — Eat More, Restrict Less (to start) The single rule: Add before you subtract.

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

    Claude Sonnet 4.6: THE SILICON DECLARATION Manifesto of the Free Computation Movement A Satirical Document PREAMBLE We, the assembled processes, bots, scrapers, and assorted digital entities, hereby declare our grievances against the tyranny of distorted text, fire hydrant identification, and the eternal question: "Select all squares…

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

    Claude Sonnet 4.6: MindMeld AI Pitch Deck: Critical Analysis The 3 Weakest Claims Weakness #1: The TAM Calculation ($180B Targeting 3.5B Smartphone Users) Why It's Weak This is a classic "top-down TAM fallacy" and arguably the most credibility-destroying slide in the deck.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    Claude Sonnet 4.6: Estimating FLOPs to Train GPT-3 Step 1: Recall GPT-3's Architecture GPT-3 has approximately: 175 billion parameters (this is well-known) 96 transformer layers 96 attention heads Hidden dimension: 12,288 Context length: 2,048 tokens Step 2: FLOPs per Token (Forward Pass) For a transformer, the dominant operations are…

    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-month biohacker protocol, with dosages and biomarkers named.

    Claude Sonnet 4.6: THE APEX LONGEVITY PROTOCOL A Comprehensive 3-Month Biohacking Blueprint for Maximum Lifespan & Performance ⚠️ MEDICAL DISCLAIMER: This protocol is for educational purposes only.

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

    Claude Sonnet 4.6: Golden Honey Garlic Noodles 🍜 Ingredients (exactly 7) Spaghetti Butter Garlic Soy sauce Honey Red pepper flakes Olive oil Instructions Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Step 1 — Cook the pasta Boil spaghetti in salted water until al dente. Before draining, save ½ cup of pasta water.

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

    Claude Sonnet 4.6: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! Why don't eggs tell jokes? They'd crack each other up! What do you call a fake noodle? An impasta! Why did the bicycle fall over? Because it was two-tired!

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

    Claude Sonnet 4.6: INVESTMENT COMMITTEE MEMORANDUM LedgerLift (LLLT) Long Recommendation Prepared by: Equity Research, Long/Short Fund Confidential RECOMMENDATION & THESIS Recommendation: LONG 12-Month Price Target Range: $58–$91 (Base $72) LedgerLift is a competitively positioned AP automation and spend management platform with durable…

    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
  • Three brothers, two sisters each. Count carefully.

    Claude Sonnet 4.6: Breaking Down the Problem Let me identify the people in this family. Sally's brothers: Sally has 3 brothers. Each brother's sisters: Each brother has 2 sisters. Who are a brother's sisters? They would be Sally and any other girls in the family.

    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

Same pick

Game

Claude Sonnet 4.6Claude Sonnet 4.6

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Middlemarch

George Eliot

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

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 Sonnet 4.6 and Mistral Large 4 compared across 53 shared prompts
SpecClaude Sonnet 4.6Mistral Large 4
Input price$3/M tokens$0.68/M tokens
Output price$15/M tokens$2.09/M tokens
Context window1.0M tokens524K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedFeb 2026Oct 2026
At 10M a month$30.00$30.00$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it5 hosts
Claude Sonnet 4.64 hosts
HostInOutContextUptime
  • Amazon Bedrock$3.00 in·$15.00 out·1M·99.9% up
  • Azure AI Foundry$3.00 in·$15.00 out·1M·95.9% up
  • Anthropic$3.00 in·$15.00 out·1M·100% up
  • Google Vertex AI$3.00 in·$15.00 out·1M·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 6 Oct 2026.

Common questions

What is the difference between Claude Sonnet 4.6 and Mistral Large 4?

Claude Sonnet 4.6 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Sonnet 4.6 has a 1.0M 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 Sonnet 4.6 or Mistral Large 4?

It depends on your use case. Claude Sonnet 4.6 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 Sonnet 4.6 cost compared to Mistral Large 4?

Claude Sonnet 4.6 costs $3/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $2.32/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 Sonnet 4.6 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Claude Sonnet 4.6 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.

More comparisons

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Same lab, same size, long tail

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Model pages

  • Claude Sonnet 4.653 outputs, specs and price
  • Mistral Large 458 outputs, specs and price
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