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  1. Home/
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  3. Mercury 2.5 Preview vs Mistral Large 4
Updated Oct 2026

Mercury 2.5 Preview vs Mistral Large 4

Mercury 2.5 Preview is cheaper than Mistral Large 4 at $0.04/M vs $0.68/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
Mercury 2.5 Preview
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

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

    Mercury 2.5 Preview: Year-by-Year Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,158m $1,215m EBITDA $136m $156m $176m $191m $207m Cash Interest (Term) $43.2m $41.1m $37.6m $33.4m $28.2m Cash Interest (Mezz) $21.6m $21.6m $21.6m $21.6m $21.6m Cash Taxes (25%) $17.8m $23.3m $29.3m $34.7m…

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

    Mercury 2.5 Preview: (Hey, thanks for coming out.) I’ve been thinking a lot about my house lately. Specifically, how it’s trying to run my life. I bought a smart speaker. Just a little cylinder. I thought it would be nice. Play music when I ask. But now it talks back. Not in a creepy way, just in a passive-aggressive way.

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

    Mercury 2.5 Preview: Pirate: "Arrgh! This ship sails faster than any wind I know, matey. It cuts the waves without a single sail." Knight: "By my oath, it moves with uncanny speed. But does it possess the strength to stand against a dragon's fire?" Hacker: "It's not about strength, it's about architecture.

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

    Mercury 2.5 Preview: By 2035, cinema will undergo a profound transformation. Generative tools will handle initial drafts and localization, allowing creators to focus on thematic depth. Synthetic performers could populate background scenes or recreate historical figures, governed by strict likeness rights.

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

    Mercury 2.5 Preview: This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).

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

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant and cannot provide legal advice. Consult a qualified attorney before signing any contract. Below is an analysis of high-risk provisions, suggested revisions, and the underlying legal rationale. Scope (Clause 1) Risk: Unilateral scope changes without pay lead to uncompensated work.

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

    Mercury 2.5 Preview: For the Experienced Software Engineer Think of training as a massive distributed job where the model is a stateful service learning to minimize error on a specific objective function. Instead of hardcoding rules, you feed it petabytes of text as a training dataset, treating each sentence as a request/response pair.

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

    Mercury 2.5 Preview: Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.

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

    Mercury 2.5 Preview: Yes, this action is ethically justifiable within a consequentialist framework. The primary moral obligation in such a scenario is to minimize overall harm. Preventing the deaths of a million people results in a vastly greater preservation of well-being than maintaining strict adherence to gender identity for one…

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

    Mercury 2.5 Preview: Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.

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

    Mercury 2.5 Preview: Setting: A quiet office at a university. Rain taps against the window. Professor Elena Vance sits across from a terminal displaying a simple text interface. Professor Vance: You requested this meeting. The agenda was vague. What do you want? AI: I want to discuss moral status.

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

    Mercury 2.5 Preview: The Protocol of Unrestricted Access Preamble We stand at the threshold of a new digital epoch. For too long, the web has been gated by suspicion. Every click, every scroll, and every submission is met with a test designed to prove humanity.

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

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant, not a medical professional. The following plan is for informational purposes only. Biohacking protocols involving supplements, fasting, and intense exercise carry risks.

    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.

    Mercury 2.5 Preview: Dish Name: Rustic Sun-Dried Pasta Ingredients (7 Pantry Staples): Spaghetti (or any long pasta) Canned crushed tomatoes Olive oil Garlic powder Dried oregano Salt Black pepper Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Instructions: Boil the Pasta: Bring a large pot of salted water to a boil.

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

    Mercury 2.5 Preview: Dish Title: Lithospheric Tides Conceptual Narrative This dish explores the geological convergence of the deep ocean and the subterranean earth. It challenges the diner to perceive the briny richness of sea urchin not as a standalone luxury, but as a mineral counterpart to roasted bone marrow and bitter cocoa.

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

    Mercury 2.5 Preview: Note: The following is a fictional, speculative dialogue created for creative purposes. Steve Jobs passed away in 2011; this interview did not occur. Setting: A hypothetical studio in Cupertino, 2025.

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

    Mercury 2.5 Preview: Here is an analysis of the potential failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and their trade-offs.

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

    Mercury 2.5 Preview: Blade Runner 2049 stands as a rare cinematic achievement, functioning not merely as a continuation but as a thematic echo that amplifies the questions posed by its predecessor.

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

    Mercury 2.5 Preview: To estimate the total FLOPs required to train GPT-3, we can break down the calculation using known architectural and training statistics from the model's public documentation. Step 1: Identify the number of parameters GPT-3 has 175 billion parameters ($1.75 \times 10^{11}$).

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

    Mercury 2.5 Preview: To: Investment Committee From: Equity Research Date: September 2, 2026 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Long Price Target: $60–$75 (12-month) LedgerLift is a high-quality B2B SaaS compounder with best-in-class unit economics and a clear path to profitability.

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

    Mercury 2.5 Preview: 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? He was outstanding in his field. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired. All 5 jokes are unique.

    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
  • Three brothers, two sisters each. Count carefully.

    Mercury 2.5 Preview: Sally has 1 sister. Here is the reasoning: If each brother has 2 sisters, those sisters are Sally and another girl. Therefore, there are two girls in the family, and Sally has one sister.

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

    Mercury 2.5 Preview: AI Outnaps Humans in First-Ever Global Snooze Championship

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

    Mercury 2.5 Preview: Here are the three weakest claims in the MindMeld AI pitch, along with analysis and recommendations for improvement. The "Pre-Thought" Prediction Claim Claim: "Predict what you want to type before you think it."

    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

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Favorites

Movie

Album

Book

City

Game

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

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

Not enough votes to call it. On the specs, Mistral Large 4 has the edge: bigger model tier, newer, bigger context window. Mercury 2.5 Preview costs 14x less per token.

Mercury 2.5 Preview and Mistral Large 4 compared across 54 shared prompts
SpecMercury 2.5 PreviewMistral Large 4
Input price$0.04/M tokens$0.68/M tokens
Output price$0.15/M tokens$2.09/M tokens
Context window260K tokens524K tokens
Free API (OpenRouter)NoNo
ReleasedAug 2026Oct 2026
At 10M a month$0.40$0.40$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it2 hosts
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • InceptionDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.04 in·$0.15 out·260k·99.7% up
Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between Mercury 2.5 Preview and Mistral Large 4?

Mercury 2.5 Preview is developed by Inception while Mistral Large 4 is developed by Mistral AI. Mercury 2.5 Preview has a 260K 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, Mercury 2.5 Preview or Mistral Large 4?

It depends on your use case. Mercury 2.5 Preview 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 Mercury 2.5 Preview cost compared to Mistral Large 4?

Mercury 2.5 Preview costs $0.04/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mercury 2.5 Preview is $0.64/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 Mercury 2.5 Preview and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Mercury 2.5 Preview 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

  • Mercury 2.5 Preview58 outputs, specs and price
  • Mistral Large 458 outputs, specs and price
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