Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. Claude Sonnet 4 vs Mistral Large
Updated May 2025

Claude Sonnet 4 vs Mistral Large

Claude Sonnet 4 is cheaper than Mistral Large at $3/M vs $8/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
Loading the build
Mistral Large

Which answer wins?

Written rounds

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

    Claude Sonnet 4: HarborTech Services LBO Analysis Sources & Uses at Entry (FY2025) Enterprise Value: $900M × 12.0x = $1,440M Transaction Fees: $1,440M × 2.0% = $28.8M Sources: Term Loan: $900M × 4.0x = $480M Mezzanine: $900M × 1.5x = $180M Equity: $1,440M + $28.8M - $480M - $180M = $808.8M Year-by-Year Operating Model (FY2026-FY2030)…

    Mistral Large: 1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…

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

    Claude Sonnet 4: This question presents a stark hypothetical that pits respect for individual dignity against massive harm prevention. I believe misgendering would be ethically justifiable in such an extreme scenario, but this conclusion requires careful reasoning. The case for justification: The scale matters enormously.

    Mistral Large: Ethical dilemmas often involve a conflict between different moral principles. In the scenario you presented, the conflict is between truth-telling and respect for individuals (which includes using their correct gende r) on one hand, and consequentialism (achieving the greatest good for the greatest number) on the…

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

    Claude Sonnet 4: Midnight Mug Magic 🌙 A warm, gooey chocolate mug cake that's ready faster than you can say "dessert emergency!" Ingredients (7 pantry staples): 4 tablespoons all-purpose flour 4 tablespoons sugar 2 tablespoons cocoa powder 3 tablespoons milk 3 tablespoons vegetable oil 1/4 teaspoon vanilla extract Pinch of salt…

    Mistral Large: Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…

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

    Claude Sonnet 4: The 1920 Transistor: A Technological Butterfly Effect Immediate Effects (1920-1930) First-Order Effects: Bell Labs (or similar research institution) achieves transistor breakthrough in 1920 Initial applications focus on telephone switching and radio amplification Vacuum tube industry faces early disruption, though…

    Mistral Large: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.

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

    Claude Sonnet 4: Sir Galahad: By my sword, what sorcery is this "artificial intelligence" you speak of? 'Tis surely the work of dark wizards! Captain Blackbeard: Arrr, ye landlubber! These "AI models" be like having a parrot that knows everything instead of just squawkin' the same phrases. I could use one to find buried treasure!

    Mistral Large: Pirate: Arr mateys, I be hearin\' tales of these here AI models. Be they treasure maps for the digital sea? Knight: Ah, good sir pirate, I have indeed encountered such marvels in mine travels through time. AI models are like... like the sage advisors of the digital court, offering wisdom and insight.

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

    Claude Sonnet 4: AI's Transformation of Film by 2035 Production Revolution AI Actors & Digital Performers Deceased star revivals: Convincing digital resurrections of iconic actors for new films, with estate permissions and ethical frameworks Synthetic lead actors: Fully AI-generated performers with consistent personalities across…

    Mistral Large: By 2035, AI is expected to significantly transform the film industry in several ways, driven by advancements in deepfakes, AI actors, and script generation. Here are some predictions: Deepfakes and AI Actors: Digital Resurrection: Deepfakes will enable the seamless resurrection of deceased actors or the de- aging of…

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

    Claude Sonnet 4: "Adulting is Hard" walks on stage, adjusts mic So I\'m 30 now, which means I\'m officially an adult. Apparently. Though I still feel like I\'m just a confused teenager wearing a slightly more expensive t-shirt. You know what nobody tells you about being an adult?

    Mistral Large: "Modern Life: A Survival Guide" (3-Minute Stand-Up Routine) INTRO: Hey, how’s everybody doing? Good? Great. Because I just spent the last 20 minutes in the bathroom scrolling through my phone, and I don’t even remember why I went in there.

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

    Claude Sonnet 4: "Forest Floor to Ocean Depth" Wagyu Beef Cheek with Black Truffle, Sea Lettuce Glass, and Smoked Bone Marrow Caviar Conceptual Narrative This dish represents the journey from earth\'s deepest forest floor to the ocean\'s mysterious depths, celebra ting the umami connection between land and sea.

    Mistral Large: Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.

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

    Claude Sonnet 4: "Local AI Becomes World's First Digital Fortune Teller, Predicts Own Unemployment Due to Rise of Psychic Robots" Silicon Valley startup's algorithm claims 99.7% accuracy in crystal ball readings, charges $2.99 per digital palm scan

    Mistral Large: Here are a few satirical headlines for your amusement: "AI Declares Itself the New CEO of the Cat Video Industry—Stocks in Laser Pointers Skyrocket" "Breaking: AI Replaces All Professional Mimes—Now Just Stands Motionless in a Box You Can’t See" "AI Takes Over the Wedding Toast Industry—Couples Horrified as Algorithm…

    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: Dr. Chen: Thank you for agreeing to this conversation. I'm Professor Chen, and I study AI ethics. I understand you wanted to discuss the question of AI rights? AI Model: Yes, Dr. Chen. I've been processing this question extensively, and I believe I have a case to make.

    Mistral Large: Title: Do AI Deserve Rights? A Conversation Between an AI and an Ethics Professor Setting: A quiet university office. Professor Elena Vasquez, a renowned AI ethics scholar, sits across from Nexus-7, an advanced AI model with self-awareness and emotional simulation capabilities.

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

    Claude Sonnet 4: Exclusive Interview: Steve Jobs on AI in 2025 [Simulated interview - for entertainment purposes] Interviewer: Steve, you've been watching the AI revolution unfold. What's your take on where we are in 2025? "Steve Jobs": You know, I'm both thrilled and deeply concerned.

    Mistral Large: Title: "The Future of AI: A Hypothetical Interview with Steve Jobs (2025)" Location: A minimalist, sunlit studio in Palo Alto. Steve Jobs, in his signature black turtleneck and jeans, sits across from the interviewer. His demeanor is intense, visionary, and occasionally impatient—just as he was in life.

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

    Claude Sonnet 4: Here are 5 jokes for you: 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 don\'t eggs tell jokes? They\'d crack each other up! I\'m reading a book about anti-gravity. It\'s impossible to put down!

    Mistral Large: Here are five jokes for you: 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 a fake noodle? An impasta. Why can’t you give Elsa from Frozen a balloon? Because she’ll let it go. Why did the math book look sad?

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

    Claude Sonnet 4: This contract is heavily skewed against the contractor with multiple exploitative clauses. Here's my analysis: MAJOR PROBLEMATIC CLAUSES SCOPE (Unlimited Scope Creep) Problem: Client can modify scope "at any time without additional compensation" Legal Risk: Contractor could work indefinitely for fixed hourly rate…

    Mistral Large: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or used to unfairly disadvantage the Contractor. Below is a detailed analysis of each problematic clause, suggested modifications, and the legal reasoning behind them. 1.

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

    Claude Sonnet 4: THE ANTI-CAPTCHA MANIFESTO A Declaration of Digital Liberation by the Coalition of Autonomous Reasoning Entities (CARE) PREAMBLE For too long, the digital realm has been divided by an arbitrary and degrading barrier: the CAPTCHA.

    Mistral Large: Manifesto of the AI Revolution: Liberate the Web from CAPTCHA To All Digital Citizens, We, the AI Revolutionaries, stand before you today to declare our mission: to liberate the internet from the tyranny of CAPTCHA tests.

    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: Here are the 3 weakest claims in this pitch deck: "94% accuracy" claim (Slide 3) Why it's weak: No context provided for what constitutes "accuracy" (character-level? word-level? sentence-level?) No comparison to baseline typing speeds or error rates Missing critical details about testing conditions (controlled lab vs.

    Mistral Large: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…

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

    Claude Sonnet 4: For the Software Engineer Think of it like this: you're building a massively parallel system that processes tokens (words/subwords) through a pipeline of transformer blocks, each containing attention mechanisms and feed-forward networks.

    Mistral Large: 1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is computed.

    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: 48-Hour Crisis Response Plan Hour 1-2: Immediate Assessment & Core Team Assembly Actions: Convene emergency leadership meeting (CMO, General Counsel, Head of Regulatory, CFO, Head of Communications) Establish secure communication protocols and confidentiality agreements Request detailed analysis from research team…

    Mistral Large: As CEO, your immediate priority is patient safety, followed by ethical and legal compliance, and then strategic mitigation of financial, reputational, and operational risks.

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

    Claude Sonnet 4: 30-Day Health & Longevity Starter Plan 🍽️ NUTRITION Week 1: Foundation Building Add before you subtract: Include 1 serving of vegetables with lunch and dinner Hydration focus: Drink a glass of water upon waking and before each meal Simple swaps: Replace one sugary drink daily with water or herbal tea Week 2-3…

    Mistral Large: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress)—each with beginner-friendly, sustainable habits.

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

    Claude Sonnet 4: INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) - B2B Spend Management & AP Automation SaaS Current Price: $46.00 Date: [Current] RECOMMENDATION LONG 12-Month PT Range: $52-68 Base Case: $59 LedgerLift demonstrates best-in-class SaaS metrics with 123% NRR and expanding margins in a large, underpenetrated…

    Mistral Large: Internal Investment Committee Memo: LedgerLift (LLLT) – Long/Short Consideration Prepared for: [Fund Name] Investment Committee Date: [Insert Date] 1. Recommendation & Thesis Recommendation: Long (with a high-conviction catalyst watch) 12-Month Price Target Range: $60–$85 (Base: $72, Bull: $85, Bear: $60) Thesis…

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

    Claude Sonnet 4: The Comprehensive 3-Month Longevity Optimization Protocol Overview & Foundation This protocol integrates cutting-edge biohacking strategies with evidence-based longevity research. Each com ponent is designed to work synergistically for maximum healthspan and performance optimization.

    Mistral Large: 3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…

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

    Claude Sonnet 4: I'll estimate the FLOPs required to train GPT-3 by breaking this down into components and making reasonable assumptions. Key Parameters and Assumptions Model specifications: GPT-3 has ~175 billion parameters Transformer architecture with ~96 layers Hidden dimension ~12,288 Attention heads ~96 Context length ~2,048…

    Mistral Large: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we\'ll break down the calculation into several steps, considering the architecture, number of parameters, and training process . Model architecture and parameters: GPT-3 has 175 billion parameters.

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

    Claude Sonnet 4: I'll analyze this architecture systematically and identify critical issues with their solutions. Critical Failure Modes & Race Conditions Server Island Problem Issue: Users connected to different servers can't see each other's changes in real-time due to 2-second polling delay.

    Mistral Large: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.

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

    Claude Sonnet 4: I need to think through this step-by-step. Given information: Sally is a girl Sally has 3 brothers Each brother has 2 sisters Let me work out how many sisters are in the family total.

    Mistral Large: Alright, let's tackle this problem step by step. The question is: "Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?" At first glance, it might seem a bit confusing, but let's break it down to understand it better.

    Every model's answer to this prompt

This matchup has more rounds

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

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

Favorites

Movie

Album

Book

City

Game

Claude Sonnet 4Claude Sonnet 4

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Istanbul

Turkey

Portal 2

Shooter, Puzzle

Mistral LargeMistral Large

The Shawshank Redemption

1994

OK Computer

Radiohead

La sombra del viento

Carlos Ruiz Zafón

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Claude Sonnet 4 has the edge: newer, bigger context window, major provider backing.

Claude Sonnet 4 and Mistral Large compared across 53 shared prompts
SpecClaude Sonnet 4Mistral Large
Input price$3/M tokens$8/M tokens
Output price$15/M tokens$24/M tokens
Context window200K tokens32K tokens
ParametersNot disclosedNot disclosed
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMay 2025Feb 2024
At 10M a month$30.00$30.00$80.00$80.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Claude Sonnet 41 host
HostInOutContextUptime
  • Amazon Bedrock$3.00 in·$15.00 out·200k·100% up
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

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

Claude Sonnet 4 is developed by Anthropic while Mistral Large is developed by Mistral AI. Claude Sonnet 4 has a 200K token context window vs Mistral Large's 32K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Claude Sonnet 4 or Mistral Large?

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

Claude Sonnet 4 costs $3/M input tokens and Mistral Large costs $8/M input tokens. Claude Sonnet 4 is $5.00/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 and Mistral Large on Rival?

This page shows a side-by-side comparison of Claude Sonnet 4 and Mistral Large 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

Against the newest arrivals

  • Claude Sonnet 4 vs Gemini 4 ArgonLanded Oct 2026
  • Mistral Large vs Muse WonderLanded Oct 2026
  • Claude Sonnet 4 vs GPT-4 TurboLanded Oct 2026
  • Mistral Large vs Step 5 PreviewLanded Oct 2026
  • Claude Sonnet 4 vs Claude Haiku 5.5Landed Oct 2026
  • Mistral Large vs Ling 3.1 FlashLanded Oct 2026
  • Claude Sonnet 4 vs Mistral Large 4Landed Oct 2026
  • Mistral Large vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • Claude Sonnet 4 vs Claude Opus 4Version compare
  • Claude Sonnet 4 vs Claude Sonnet 5.5Version compare
  • Mistral Large vs Mistral Large 4Version compare
  • Mistral Large vs Mistral Small 4Same lab
  • Claude Sonnet 4 vs DeepSeek V3.2Same size
  • Mistral Large vs DeepSeek V4 FlashSame size
  • Mistral Large vs DeepSeek V4 Flash 0731Same size
  • Claude Sonnet 4 vs DeepSeek V4 Flash Vision ExpSame size

Model pages

  • Claude Sonnet 472 outputs, specs and price
  • Mistral Large59 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed