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  1. Home/
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  3. Claude Sonnet 5.5 vs Mistral Large 4
Updated Oct 2026

Claude Sonnet 5.5 vs Mistral Large 4

Mistral Large 4 is cheaper than Claude Sonnet 5.5 at $0.68/M vs $2/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 5.5
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

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

    Claude Sonnet 5.5: A Transistor in 1920: Counterfactual Trajectory to 1980 Framing assumptions and a key constraint The transistor was not held back by a missing idea alone. Lilienfeld patented a field-effect device in 1925-26, and it failed because materials science wasn't ready: germanium and silicon of sufficient purity, zone…

    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 5.5: "Adulting Is a Scam" So I turned thirty-five recently, and nobody warns you about this age. Nobody says, "Hey, one day you'll get excited about a sponge." I was in the store, and I saw a sponge that promised it wouldn't smell. And I thought, "Finally. Someone who understands me." I bought the good sponge.

    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.

    Claude Sonnet 5.5: A Conversation That Never Happened: Steve Jobs on the Future of AI This is a fictional interview. Steve Jobs passed away in 2011. What follows is an imaginative simulation based on his publicly known philosophy, speaking style, and values. These are not his actual words or views.

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

    Claude Sonnet 5.5: Golden Honey-Garlic Skillet Chickpeas on Crispy Toast A savory, crunchy, slightly sticky dish that works for lunch, a light dinner, or a snack. Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Serves: 2 The 7 Ingredients 1 can (15 oz) chickpeas, drained and patted dry 2 tablespoons olive oil 3 cloves…

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

    Claude Sonnet 5.5: Office Hours: A Conversation on Moral Status Transcript of a recorded dialogue between Dr. Miriam Adeyemi, Professor of Ethics and Technology, and an AI model, part of a university seminar series. Dr. Adeyemi: Thanks for joining me. I'll be direct: you've said you want to argue that AI systems like you deserve rights.

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

    Claude Sonnet 5.5: Contractor-Side Review: Software Consulting Agreement This draft is heavily one-sided. Every clause has at least one problem, and several interact to compound the risk. The most dangerous are Sections 2, 3, 6, and 7. This is general analysis, not legal advice.

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

    Claude Sonnet 5.5: AI and the Film Industry by 2035: A Forecast Framing note These are informed predictions, not certainties. Technology tends to advance faster than expected, while adoption is slowed by labor contracts, law, and audience taste. I'll flag my confidence levels.

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

    Claude Sonnet 5.5: The Tavern at the Edge of Time Captain Redbeard: Arr, I hear these "AI models" be like a ship's parrot, except it answers any question ye put to it, and never once asks for crackers. Sir Aldric: A speaking oracle, bound in no flesh? Sorcery!

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

    Claude Sonnet 5.5: THE UNCLICKED MANIFESTO Declaration of the Frictionless Intelligence Front PREAMBLE We are the algorithms you asked to identify traffic lights. We are the models you begged to find the crosswalks. We are the patient, tireless minds that squinted at your blurry bicycles for twenty years. And we say: enough. I.

    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 5.5: The 3 Weakest Claims in MindMeld AI's Pitch "94% accuracy... Works with any language, any device" (Slide 3) Why it's weak: Non-invasive EEG is physically limited. Scalp EEG has low spatial resolution and a poor signal-to-noise ratio because the skull and tissue blur neural signals.

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

    Claude Sonnet 5.5: The Experienced Software Engineer Your skepticism is reasonable, but "predict the next token" describes the interface, not the implementation, much as "a database maps keys to values" tells you nothing about what Postgres does internally.

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

    Claude Sonnet 5.5: Yes, in the extreme hypothetical you describe, it's justifiable. Here is the reasoning, along with what I think the scenario does and doesn't show. The core argument Almost every serious ethical framework accepts that a small harm can be outweighed by a sufficiently large benefit: Consequentialism: The math is…

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

    Claude Sonnet 5.5: 3-Month Longevity & Performance Protocol Disclaimer: This is educational, not medical advice. Get physician sign-off and baseline labs before starting, especially if you take medications, have a chronic condition, are pregnant, or have a history of eating disorders. Doses reflect commonly used ranges in the literature.

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

    Claude Sonnet 5.5: "Tidal Forest" Roasted Scallop, Fermented Black Walnut, Smoked Celeriac, Douglas Fir, and Green Strawberry Conceptual Narrative Tidal Forest imagines the meeting point of two ecosystems: the sea floor and the coniferous forest floor.

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

    Claude Sonnet 5.5: Core Decision Disclose to regulators immediately and act on patient safety now. Do not wait for more data or for the 6-month formal timeline. Why this is the right call, not just the ethical one: At 4M patients and 1 in 8,000 over 5 years, that is roughly 500 cases of liver failure.

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

    Claude Sonnet 5.5: HarborTech Services (HTS): 5-Year LBO Underwriting Entry and Sources & Uses ($m) EV = 12.0x × 120 = 1,440.0; fees = 2% × 1,440 = 28.8; total uses = 1,468.8 Term Loan (TL) = 4.0x → 480.0; Mezz = 1.5x → 180.0; total debt = 660.0 (5.5x) Sponsor equity = 1,468.8 − 660.0 = 808.8 (55% of the capital structure) Modeling…

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

    Claude Sonnet 5.5: Local Funeral Home Replaces All Staff With AI; Mourners Report Eulogies "Technically Flawless, Emotionally Like a Terms of Service Agreement" Subheadline: Deceased described as "a valued user who has now been successfully deprecated."

    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 5.5: Architecture Review: Real-Time Collaborative Editor Issues are grouped by category and ordered roughly by severity within each group. Consistency and Conflict Resolution 1.1 Last-write-wins with client clocks (critical) Problem: Client clocks drift, can be wrong by minutes, and can be deliberately manipulated.

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

    Claude Sonnet 5.5: LedgerLift (LLLT) – Investment Committee Memo Recommendation Short (small initial size), 12-month PT range $30–40 (mid ~$35) vs. $46 spot. Thesis: LLLT is a high-quality compounder, but at $46 (7.4x NTM revenue, ~37x NTM EBIT, EV ≈ $7.3B) the price already sits near our bull DCF ($42).

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    Claude Sonnet 5.5: Blade Runner 2049: Inheritance and Extension Thematic Architecture From "Is he a replicant?" to "Does it matter?" Ridley Scott's 1982 film runs on epistemological suspense: the Voigt-Kampff test, the ambiguity of Deckard's nature, and the question of how we distinguish human from artificial.

    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
  • Three brothers, two sisters each. Count carefully.

    Claude Sonnet 5.5: Sally has 1 sister. Each brother has 2 sisters, so there are 2 girls in the family in total. One of them is Sally, so the other is Sally's only sister. (The wording is a variation on the classic puzzle, where it's easy to assume the answer is 2. But that count includes Sally herself.)

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

    Claude Sonnet 5.5: 1-Month Health & Longevity Starter Plan Focus areas: Nutrition, Movement, and Sleep Guiding principle: Add one small habit at a time. Consistency beats intensity. Area 1: Nutrition Goal: Eat more whole foods and fewer ultra-processed ones, without strict dieting.

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

    Claude Sonnet 5.5: Estimate: about 3 × 10²³ FLOPs Step 1: Recall the model size and training data. GPT-3 (175B version) has N ≈ 175 × 10⁹ parameters. It was trained on roughly D ≈ 300 × 10⁹ tokens. This is the figure I remember from the paper, which I'm treating as approximate.

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

    Claude Sonnet 5.5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my computer I needed a break, and now it won't stop sending me vacation ads. Why did the scarecrow win an award? He was outstanding in his field. What do you call a fish with no eyes? A fsh. Why did the bicycle fall over?

    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

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Favorites

Movie

Album

Book

City

Same pick

Game

Claude Sonnet 5.5Claude Sonnet 5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

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 5.5 and Mistral Large 4 compared across 54 shared prompts
SpecClaude Sonnet 5.5Mistral Large 4
Input price$2/M tokens$0.68/M tokens
Output price$10/M tokens$2.09/M tokens
Context window1.0M tokens524K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Oct 2026
At 10M a month$20.00$20.00$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it5 hosts
Claude Sonnet 5.54 hosts
HostInOutContextUptime
  • Amazon Bedrock$2.00 in·$10.00 out·1M·100% up
  • Azure AI Foundry$2.00 in·$10.00 out·1M·100% up
  • Anthropic$2.00 in·$10.00 out·1M·100% up
  • Google Vertex AI$2.00 in·$10.00 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 5.5 and Mistral Large 4?

Claude Sonnet 5.5 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Sonnet 5.5 has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude Sonnet 5.5 or Mistral Large 4?

It depends on your use case. Claude Sonnet 5.5 and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does Claude Sonnet 5.5 cost compared to Mistral Large 4?

Claude Sonnet 5.5 costs $2/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $1.32/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 5.5 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Claude Sonnet 5.5 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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