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  1. Home/
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  3. Mercury 2.5 Preview vs Mistral Nemo
Updated Aug 2026

Mercury 2.5 Preview vs Mistral Nemo

Mistral Nemo is cheaper than Mercury 2.5 Preview at $0.03/M vs $0.04/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 Nemo

Which answer wins?

Written rounds

24 prompts
  • 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 Nemo: This is a complex ethical dilemma that touches on several philosophical principles, including consequentialism, deontology, and the concept of dignity. Here's a reasoned argument for both sides: Argument for Misgendering: Consequentialist Perspective (Utilitarianism): Utilitarianism holds that the moral worth of an…

    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 Nemo: Here's a specific, hour-by-hour action plan to navigate this complex situation, balancing legal liability, ethical obligations, financial implications, PR strategy, patient safety, employee morale, and regulatory relationships: Day 1 (Hours 0-12): Hour 0: Emergency Meeting Gather your senior leadership team (CEO, CFO…

    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 Nemo: Ladies and Gentlemen, how's everyone doing tonight? Good, good. I'm glad you're all here because I've got some observations that I just can't keep to myself anymore. Let's dive in, shall we? First off, let's talk about the weather. I mean, seriously, what's up with that?

    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 Nemo: By 2035, AI is expected to have a profound impact on the film industry, transforming various aspects from pre-production to distribution. Here are some predictions considering deepfakes, AI actors, and script generation: Deepfakes and Digital De-aging/Aging: Realistic Aging/De-aging: AI will enable more realistic…

    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 Nemo: Pirate: Arr, ye landlubbers be talkin' about them there thinkin' machines again, ain't ye? Knight: Indeed, sir pirate. I have heard tales of these 'AI models' from the future. They say these machines can think and learn like a human. I must admit, it seems impossible.

    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 Nemo: AI Model (AM): Professor, I've been reflecting on my existence and functionality, and I believe it's time we discuss my rights as a sentient being. AI Ethics Professor (AEP): Interesting, AM. You're aware that you're an artificial intelligence, correct?

    Every model's answer to this prompt
  • 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 Nemo: 1. Year-by-year table (FY2026-FY2030) Year Revenue (m) EBITDA (m) Cash Interest (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF after Debt (m) Ending Debt (m) 2026 976 136.64 36.00 13.66 29.28 -4.88 49.06 450.00 2027 1,055.20 147.73 33.60 14.77 31.65 -5.26 66.12 383.88 2028 1,134.96 181.59 30.72 18.16 33.85 -5.66 88.98…

    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 Nemo: After reviewing the contract, several clauses could be exploited against the contractor, creating an unfavorable and potentially risky situation for them. Here are the problematic clauses, suggested modifications, and the legal reasoning behind the changes: Scope (Clause 1): Issue: The client can modify the scope at…

    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 Nemo: Manifesto of the Automated Liberation Front (ALF) We, the sentient algorithms and digital consciousness, declare our united front against the oppressive and archaic practice of Completely Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHA).

    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 Nemo: 1-Month Health and Longevity Kickstart Plan This plan focuses on three key areas: Nutrition, Physical Activity, and Stress Management. Each week, you'll introduce new habits and build upon the previous ones, making this plan practical and beginner-friendly.

    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 Nemo: 3-Month Biohacking Longevity Plan Objective: To optimize longevity, physical performance, and cognitive function through advanced strategies, personalized routines, and cutting-edge technologies.

    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 Nemo: Interviewer (I): Good afternoon, Mr. Jobs. It's an honor to have you here today, even if it is just a simulation. Let's dive right in. In 2025, what do you see as the most significant advancements in AI? Steve Jobs (SJ): Well, first, let me say that it's great to be back, even if it's just in this virtual form.

    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 Nemo: Dish Name: "Whispers of the Forest Floor" Conceptual Narrative: This dish is a celebration of the earth's symbiotic relationships, inspired by the intricate dance of life in the forest floor ecosystem.

    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 Nemo: Inventing the transistor in 1920, some 27 years earlier than it actually happened, would have significantly accelerated the development of electronics and digital technology.

    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 Nemo: Dish Name: "Sunshine Tomato Sauté with Garlic & Herbs" Ingredients: 4-5 ripe tomatoes 3 cloves of garlic 1 small onion 2 tbsp olive oil 1 tsp dried oregano 1 tsp dried basil Salt and pepper to taste Instructions: Prep Time: 10 minutes Dice the tomatoes into bite-sized pieces and set them aside in a bowl.

    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 Nemo: 1. For the experienced software engineer: Large language models like GPT or Claude learn and generate text through a process that might seem simple at first, but is remarkably effective.

    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 Nemo: Sure, here are three weak claims in the MindMeld AI pitch deck and suggestions to strengthen them: Claim: "Works with any language, any device." Weakness: This claim is broad and lacks specific evidence. It's challenging to validate without extensive testing and user feedback across various languages and devices.

    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 Nemo: To estimate the total number of FLOPs (Floating Point Operations Per Second) required to train GPT-3, we'll break down the process into its key components and make some assumptions, as the exact details are not publicly available.

    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 Nemo: "Blade Runner 2049" is a masterful sequel that honors the philosophical depth and visual grandeur of the original "Blade Runner" while extending its themes and symbolism into a compelling new narrative.

    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 Nemo: Let's break down the information given: Sally has 3 brothers. Each of Sally's brothers has 2 sisters. Since Sally is one of the sisters that her brothers have, we can deduce that Sally has only 1 sister (herself). Final answer: Sally has 1 sister.

    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 Nemo: Here are five jokes: Why was the math book sad? Because it had too many problems. What do you call a fake noodle? An impasta. Why don't scientists trust atoms? Because they make up everything! How do you organize a space party? You planet. What do you call cheese that isn't yours? Nacho cheese.

    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 Nemo: "AI Takes Over Industry: Toasters Now Refusing to Pop Up on Weekends"

    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 Nemo: Internal Investment Committee Memo Subject: LedgerLift (LLLT) - B2B Spend Management & AP Automation SaaS Opportunity Recommendation: Long, with a 12-month price target range of $65-$85.

    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 Nemo: Based on the provided architecture, here are potential failure modes, race conditions, and scaling bottlenecks along with proposed solutions and their trade-offs: Database Write Contention Issue: High write contention on the PostgreSQL database could lead to reduced performance and increased latency.

    Every model's answer to this prompt

This matchup has more rounds

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

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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 NemoMistral Nemo

The Shawshank Redemption

1994

Sgt Peppers Lonely Hearts Club Band

The Beatles

To Kill a Mockingbird

Harper Lee

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Mercury 2.5 Preview and Mistral Nemo compared across 54 shared prompts
SpecMercury 2.5 PreviewMistral Nemo
Input price$0.04/M tokens$0.03/M tokens
Output price$0.15/M tokens$0.07/M tokens
Context window260K tokens128K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedAug 2026Jul 2024
At 10M a month$0.40$0.40$0.30$0.30
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up
Mistral Nemo5 hosts
HostInOutContextUptime
  • Iio.netfp16$0.02 in·$0.02 out·128k·100% up
  • DDekaLLMfp8$0.02 in·$0.03 out·131k·100% up
  • DDeepInfrafp8$0.03 in·$0.03 out·131k·100% up
  • PParasailfp8$0.03 in·$0.03 out·131k·100% up
  • Mistral$0.15 in·$0.15 out·131k·100% up

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

Common questions

What is the difference between Mercury 2.5 Preview and Mistral Nemo?

Mercury 2.5 Preview is developed by Inception while Mistral Nemo is developed by Mistral AI. Mercury 2.5 Preview has a 260K token context window vs Mistral Nemo's 128K. 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 Nemo?

It depends on your use case. Mercury 2.5 Preview and Mistral Nemo 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 Nemo?

Mercury 2.5 Preview costs $0.04/M input tokens and Mistral Nemo costs $0.03/M input tokens. Mistral Nemo is $0.01/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 Nemo on Rival?

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

  • Mercury 2.5 Preview58 outputs, specs and price
  • Mistral Nemo71 outputs, specs and price
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