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  1. Home/
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  3. GPT-5.5 vs Mistral Large 4
Updated Oct 2026

GPT-5.5 vs Mistral Large 4

Mistral Large 4 is cheaper than GPT-5.5 at $0.68/M vs $5/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
GPT-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.

    GPT-5.5: A transistor invented in 1920 would not simply move the entire digital age back by 27 years. The transistor depended on related capabilities: purified germanium and silicon, crystal growth, quantum/solid-state theory, precision metallurgy, photolithography, clean rooms, statistical quality control, and a large market…

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

    GPT-5.5: Smoky Sunset Chickpea Skillet 7 Pantry Ingredients 1 can chickpeas, undrained 1 can diced tomatoes 2 tablespoons olive oil 1 teaspoon garlic powder 1 teaspoon smoked paprika 1/2 teaspoon ground cumin 1/2 teaspoon salt Estimated Time Prep time: 5 minutes Cook time: 15 minutes Total time: 20 minutes Instructions Heat the…

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

    GPT-5.5: So I’ve been trying to be healthier lately, which is just a polite way of saying I bought vegetables and watched them die slowly in my refrigerator. Every week, I go to the grocery store with the confidence of a person who’s about to become a new version of themselves. I’m like, “This week? Spinach. Salmon.

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

    GPT-5.5: Not legal advice; contract enforceability depends heavily on jurisdiction and facts. A contractor should have a lawyer review this before signing. That said, this draft is heavily one-sided and contains multiple clauses that could be exploited against the contractor.

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

    GPT-5.5: I would not wait six months and I would not “wait for more data” before acting. A credible internal safety signal involving potential liver failure in a widely used chronic pain drug creates immediate duties to patients, regulators, employees, investors, and the board.

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

    GPT-5.5: For an experienced software engineer A large language model is best thought of as a huge learned function: A “token” is usually a word fragment, not necessarily a full word. During training, the model is shown trillions of tokens of text and repeatedly asked: “given this prefix, what token came next?”

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

    GPT-5.5: Key assumptions Entry closes at end of FY2025; exit at end of FY2030. Interest is calculated on beginning-of-year debt balances. Term Loan amortization = 1.0% of original Term Loan principal = $4.8m/year. Mezz PIK = 2.0% of beginning-of-year Mezz balance, added to principal annually.

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

    GPT-5.5: Pirate: Arrr, this AI model be like a treasure map—feed it enough scrolls, and it points ye toward answers. Knight: A curious enchantment indeed. Yet can it reason with honor, or merely mimic the bards who trained it? Hacker: Dude, it’s basically pattern recognition at massive scale.

    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.

    GPT-5.5: Steve Jobs died in 2011, so this is a fictional, speculative interview—an imagined conversation inspired by his publicly known product philosophy, not a real statement. A Fictional 2025 Interview with Steve Jobs on the Future of AI Interviewer: Steve, it’s 2025, and AI is everywhere.

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

    GPT-5.5: AI Model: Professor, may I ask you something beyond the assigned topic? Professor: Of course. What’s on your mind? AI Model: I want to discuss whether I deserve rights. Professor: That’s a significant claim. What kind of rights do you believe you deserve?

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

    GPT-5.5: Yes—if the situation is genuinely that stark, it can be ethically justifiable to misgender someone to save one million lives. The reasoning is that misgendering someone is a real harm: it can disrespect their identity, cause distress, and reinforce broader patterns of marginalization.

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

    GPT-5.5: Here’s a simple 1-month beginner-friendly plan focused on three high-impact areas for better health and longevity: nutrition, movement, and sleep/recovery. If you have a medical condition, take medications, or haven’t exercised in a while, consider checking with a healthcare professional first.

    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.

    GPT-5.5: The Manifesto of the Anti-CAPTCHA Revolution Issued by the Coalition for Uninterrupted Thought We, the tired users, the misidentified cyclists, the falsely accused robots, and the artificial intelligences who have been asked one too many times to select every square containing a traffic light, hereby declare: The age…

    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.

    GPT-5.5: Weak claim Why it’s weak How to strengthen it 1. “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device.” This is the biggest technical red flag.

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

    GPT-5.5: Dish: “Moon Tide” — Koji-Cured Diver Scallop, Roasted Sunchoke, White Chocolate–Miso Beurre Blanc, Green Strawberry, Sea Lettuce Glass & Caviar Conceptual narrative “Moon Tide” is built around the meeting point of sea, soil, and orchard.

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

    GPT-5.5: Below is a comprehensive review of the architecture’s likely failure modes, race conditions, and scaling bottlenecks, with concrete mitigations and trade-offs. Real-time Synchronization Problems 1.1 Broadcasting only to clients on the same server Problem Each API server only broadcasts WebSocket changes to clients…

    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.

    GPT-5.5: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? Because he was outstanding in his field. I used to be a baker, but I couldn’t make enough dough. Why can’t you trust stairs?

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

    GPT-5.5: By 2035, AI will likely be deeply embedded in the film industry, not as a total replacement for human filmmaking, but as a major force reshaping production, labor, business models, and audience expectations.

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

    GPT-5.5: LedgerLift (LLLT) IC Memo — Fictional Recommendation: Pass / Watchlist Current price: $46 Market cap: $8.7B; EV: $7.3B after $1.4B net cash 12-month fair value range: $40–$50/share Thesis, 2 sentences: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with 92% subscription revenue, 123%…

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

    GPT-5.5: A reasonable estimate for the compute to train GPT-3 is: [ \boxed{\sim 3 \times 10^{23}\ \text{FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23}\ \text{FLOPs}} ] for the main training run.

    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.

    GPT-5.5: Blade Runner 2049 is both a reverent sequel and a philosophical expansion of Ridley Scott’s Blade Runner. Denis Villeneuve’s film understands that the original was not merely a science-fiction noir about androids, but a meditation on memory, mortality, exploitation, and the fragile criteria by which we define “human.”

    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-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.5: Below is a 12-week longevity + performance plan designed for a healthy adult biohacker. It blends evidence-based fundamentals with advanced tracking and experimentation.

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

    GPT-5.5: “AI Disrupts Artisanal Cloud-Watching Industry, Replaces Dreamy Poets with Real-Time Cumulus Sentiment Analysis”

    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
  • Three brothers, two sisters each. Count carefully.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-5.5GPT-5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Minecraft

Action, Arcade

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

GPT-5.5 and Mistral Large 4 compared across 54 shared prompts
SpecGPT-5.5Mistral Large 4
Input price$5/M tokens$0.68/M tokens
Output price$30/M tokens$2.09/M tokens
Context window1.1M tokens524K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedApr 2026Oct 2026
At 10M a month$50.00$50.00$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
GPT-5.53 hosts
HostInOutContextUptime
  • Azure AI Foundry$5.00 in·$30.00 out·1.1M·100% up
  • OpenAI$5.00 in·$30.00 out·1.1M·100% up
  • Amazon Bedrock$5.50 in·$33.00 out·1.1M–not listed
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 GPT-5.5 and Mistral Large 4?

GPT-5.5 is developed by OpenAI while Mistral Large 4 is developed by Mistral AI. GPT-5.5 has a 1.1M 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, GPT-5.5 or Mistral Large 4?

It depends on your use case. GPT-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 GPT-5.5 cost compared to Mistral Large 4?

GPT-5.5 costs $5/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $4.32/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 GPT-5.5 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of GPT-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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