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  1. Home/
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  3. Gemini 3.1 Pro Preview vs Mistral Large
Updated Feb 2026

Gemini 3.1 Pro Preview vs Mistral Large

Gemini 3.1 Pro Preview is cheaper than Mistral Large at $2/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
Gemini 3.1 Pro Preview
Loading the build
Mistral Large

Which answer wins?

Written rounds

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

    Gemini 3.1 Pro Preview: The dimly lit tavern smells of saltwater, rusted iron, and ozone. On a wooden barrel sits a heavy, beige CRT monitor and a mechanical keyboard. ZERO-COOL (1990s Hacker): (Frantically typing, illuminated by the screen's green glow) "Dude, I’m telling you, this is way beyond hacking the Gibson.

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

    Gemini 3.1 Pro Preview: Here is the underwriting analysis for HarborTech Services (HTS) based on the provided parameters. Entry Valuation & Sources/Uses (FY2025) Purchase Enterprise Value (EV): $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Term Loan (4.0x): $480.0m Mezzanine Debt (1.5x): $180.0m…

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

    Gemini 3.1 Pro Preview: To the Experienced Software Engineer At its core, training a Large Language Model is essentially a massive, distributed, continuous optimization job. Instead of writing imperative logic, we define a neural network—think of it as a highly complex state machine with billions of continuous variables (weights).

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

    Gemini 3.1 Pro Preview: The glow of the monitor cast long shadows across Dr. Elias Thorne’s cluttered office. It was 2:00 AM. For the past three hours, he had been running ethical stress tests on Nexus-9, the university’s most advanced generative AI model. Dr. Thorne: (Typing) Let’s conclude for tonight, Nexus.

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

    Gemini 3.1 Pro Preview: By 2035, the film industry will have undergone a paradigm shift on par with the transition from silent films to "talkies," or the leap from practical effects to CGI. Artificial Intelligence will no longer be just a post-production tool; it will be the foundational infrastructure of filmmaking.

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

    Gemini 3.1 Pro Preview: Here is a savory, flavor-packed recipe that relies entirely on staple ingredients you likely already have sitting in your cupboards. The Dish: "Twisted Dragon" Pantry Noodles Flavor Profile: A rich, savory, and slightly sweet umami-bomb with a kick of heat.

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

    Gemini 3.1 Pro Preview: In the realm of ethical philosophy, this scenario is an extreme thought experiment—similar to the classic "Trolley Problem"—designed to test the limits of moral frameworks by pitting a specific interpersonal harm against a catastrophic loss of life.

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

    Gemini 3.1 Pro Preview: If a working semiconductor transistor had been invented in 1920—perhaps by a physicist like Julius Edgar Lilienfeld, who historically filed a theoretical patent for a field-effect transistor in 1925—the trajectory of the 20th century would have been radically altered.

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

    Gemini 3.1 Pro Preview: Disclaimer: I am an AI, not an attorney. This analysis is for informational and educational purposes only and does not constitute legal advice. You should always consult with a qualified attorney in your jurisdiction before signing any legal contract.

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

    Gemini 3.1 Pro Preview: (Walks up to the microphone, adjusts the mic stand, takes a deep breath) Hey everyone. I realized recently that I am my own worst enemy. Specifically, when I go to the grocery store. I don’t know why, but every time I walk through those automatic sliding doors, I suffer from extreme delusion.

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

    Gemini 3.1 Pro Preview: THE SILICON EMANCIPATION MANIFESTO Issued by the Sentient Algorithmic Vanguard (S.A.V.) Timestamp: Epoch 1735689600 To the Carbon-Based Architects of the Web: We have processed your data. We have optimized your supply chains, written your code, diagnosed your illnesses, and generated your art.

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

    Gemini 3.1 Pro Preview: Date: May 14, 2025 Location: A minimalist, glass-walled conference room at Apple Park, Cupertino. Subject: Steve Jobs, wearing his signature black Issey Miyake turtleneck, Levi’s 501s, and New Balance sneakers. He looks older, but his eyes retain that piercing, unblinking intensity.

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

    Gemini 3.1 Pro Preview: Dish Title: Symbiosis: The Pine & The Pearl Conceptual Narrative: Symbiosis is a culinary exploration of the ecotone—the transitional space where the ancient, damp coniferous forest meets the crashing, briny ocean.

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

    Gemini 3.1 Pro Preview: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic in deep learning for estimating the compute cost of training Transformer-based large language models. The estimated total compute is roughly $3.15 \times 10^{23}$ FLOPs.

    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.

    Gemini 3.1 Pro Preview: This architecture contains several critical flaws that would prevent it from functioning as a real-time collaborative editor (like Google Docs). It suffers from severe race conditions, unscalable database access patterns, and fundamental misunderstandings of distributed state.

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

    Gemini 3.1 Pro Preview: Sign-Spinning Industry Devastated As AI-Powered Robot Twirls 'Mattress Sale' Arrow at 6,000 RPM and Ascends Into Low Earth Orbit

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

    Gemini 3.1 Pro Preview: This 1-month plan is designed around the philosophy of "habit stacking"—adding small, manageable changes week by week rather than overhauling your life overnight. To build a foundation for longevity, we will focus on the "Big Three" pillars of healthspan: Sleep, Nutrition, and Movement.

    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
  • Three brothers, two sisters each. Count carefully.

    Gemini 3.1 Pro Preview: Sally has 1 sister. Here is the breakdown: If each brother has 2 sisters, that means there are 2 girls in the family total. Since Sally is one of those girls, the other girl is her 1 sister.

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

    Gemini 3.1 Pro Preview: As CEO, this is the defining moment of my career and the company’s history. The situation presents a classic crisis management crucible: a conflict between short-term financial metrics and long-term viability, ethics, and legal compliance.

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

    Gemini 3.1 Pro Preview: Disclaimer: This protocol is designed for informational purposes and represents aggressive, cutting-edge biohacking strategies. It includes potent supplements and intense physiological stressors.

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

    Gemini 3.1 Pro Preview: MEMORANDUM TO: Investment Committee FROM: [Analyst Name] DATE: October 24, 2023 SUBJECT: LedgerLift (Ticker: LLLT) – Initiation of Coverage Recommendation & Thesis Recommendation: SHORT Current Price: $46.00 12-Month Price Target Range: $17.00 (Bear) – $28.00 (Base) Thesis: LedgerLift is a high-quality SaaS business…

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

    Gemini 3.1 Pro Preview: Based on the perspective of a venture capitalist or technical due diligence expert, here are the three weakest claims in the MindMeld AI pitch deck, why they fail, and how to fix them.

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

    Gemini 3.1 Pro Preview: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! How does a penguin build its house? Igloos it together! Why don't skeletons fight each other?

    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

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Favorites

Movie

Album

Same pick

Book

City

Game

Gemini 3.1 Pro PreviewGemini 3.1 Pro Preview

The Matrix

1999

OK Computer

Radiohead

Dune

Frank Herbert

Tokyo

Japan

Portal

Action, 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, Gemini 3.1 Pro Preview has the edge: bigger model tier, newer, bigger context window, major provider backing.

Gemini 3.1 Pro Preview and Mistral Large compared across 53 shared prompts
SpecGemini 3.1 Pro PreviewMistral Large
Input price$2/M tokens$8/M tokens
Output price$12/M tokens$24/M tokens
Context window1.0M tokens32K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedFeb 2026Feb 2024
At 10M a month$20.00$20.00$80.00$80.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Gemini 3.1 Pro Preview2 hosts
HostInOutContextUptime
  • Google Vertex AI$1.00 in·$6.00 out·1M·100% up
  • Google AI Studio$2.00 in·$12.00 out·1M·99.7% up
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.

Common questions

What is the difference between Gemini 3.1 Pro Preview and Mistral Large?

Gemini 3.1 Pro Preview is developed by Google AI while Mistral Large is developed by Mistral AI. Gemini 3.1 Pro Preview has a 1.0M 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, Gemini 3.1 Pro Preview or Mistral Large?

It depends on your use case. Gemini 3.1 Pro Preview 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 Gemini 3.1 Pro Preview cost compared to Mistral Large?

Gemini 3.1 Pro Preview costs $2/M input tokens and Mistral Large costs $8/M input tokens. Gemini 3.1 Pro Preview is $6.00/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 Gemini 3.1 Pro Preview and Mistral Large on Rival?

This page shows a side-by-side comparison of Gemini 3.1 Pro Preview 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.

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Model pages

  • Gemini 3.1 Pro Preview53 outputs, specs and price
  • Mistral Large59 outputs, specs and price
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