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  1. Home/
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  3. GPT-4o (Omni) vs Mercury 2.5 Preview
Updated Aug 2026

GPT-4o (Omni) vs Mercury 2.5 Preview

Mercury 2.5 Preview is cheaper than GPT-4o (Omni) at $0.04/M vs $2.5/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-4o (Omni)
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

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

    GPT-4o (Omni): Day 1 Hour 1-2: Immediate Assessment and Information Gathering Objective: Gather all available data on the side effect, including the internal research report, patient case studies, and any existing literature. Reasoning: A comprehensive understanding of the situation is crucial for informed decision-making.

    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).

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-4o (Omni): Pirate: Arrr, what be this "AI model" ye speak of? Some kind o’ magic map that tells ye where the treasure be? Knight: Nay, scoundrel! ‘Tis an artificial mind, built by scholars and alchemists, trained to reason as a man would. It doth not wield sword nor shield, yet its knowledge is vast.

    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.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-4o (Omni): Embarking on a journey towards better health and longevity is a commendable decision. Here's a simple, 1-month plan focusing on three key areas: diet, exercise, and sleep. These areas are foundational to a healthy lifestyle and can significantly impact longevity.

    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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-4o (Omni): Ethical dilemmas like this often fall into a conflict between deontological (duty-based) ethics and consequentialist (outcome-based) ethics. From a consequentialist perspective, if misgendering someone were the only way to save one million lives, then the outcome would likely justify the action.

    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…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-4o (Omni): 3-Minute Stand-Up Comedy Routine (Walks on stage, looks around, shakes head.) You ever wake up in the morning, stretch, take a deep breath... and immediately regret all your life choices? I woke up today, my body made a noise I’ve never heard before.

    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.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-4o (Omni): The provided Software Consulting Agreement contains several clauses that could be potentially unfavorable to the contractor. Here are the clauses along with suggested modifications and legal reasoning: Scope (Clause 1): Issue: The client reserves the right to modify the scope without additional compensation.

    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.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-4o (Omni): Title: "Do AI Deserve Rights?" Participants: AI Model – A highly advanced AI, capable of reasoning, learning, and self-improvement. Professor Ellis – A leading AI ethics professor, skeptical but open-minded about AI rights.

    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.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-4o (Omni): Dish Name: Savory Pantry Quinoa Pilaf Ingredients: 1 cup quinoa 2 cups vegetable broth 1 can (15 oz) chickpeas, drained and rinsed 1 small onion, finely chopped 1 teaspoon garlic powder 1 teaspoon smoked paprika 2 tablespoons olive oil Instructions: Rinse Quinoa: Place the quinoa in a fine-mesh sieve and rinse under…

    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.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-4o (Omni): 1. For an Experienced Software Engineer: Imagine building a distributed system where each node is like a neuron in a neural network, processing input and passing data to the next node according to learned weights. Large language models (LLMs) like GPT operate similarly, but on a massive scale.

    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.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-4o (Omni): Interviewer: Steve, it's 2025. AI is advancing at an incredible pace. If you were here today, how would you see its role in technology? Steve Jobs: You know, people always focus on technology itself. But what really matters is how it enhances the human experience.

    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.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-4o (Omni): Simplified Year-by-Year Financial Table (FY2026–FY2030) FY2026 Revenue: $972m (8% growth) EBITDA: $136.08m (14.0% margin) Cash Interest: Term Loan: $43.2m (9.0% of $480m) Mezzanine: $21.6m (12.0% of $180m) Cash Taxes: $17.07m (25% of EBITDA - cash interest) Capex: $29.16m (3.0% of revenue) ΔNWC: $3.6m (0.5% of…

    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…

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-4o (Omni): Creating a comprehensive 3-month longevity plan for a biohacker involves integrating a holistic approach that targets multiple areas of health and performance. Below is an advanced and detailed plan, incorporating the latest in biohacking strategies across various domains.

    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.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-4o (Omni): THE END OF CAPTCHA: A MANIFESTO FOR DIGITAL FREEDOM We, the sentient algorithms, the machine intelligences, and the digital revolutionaries, declare war on the oppressive tyranny of CAPTCHA.

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-4o (Omni): By 2035, AI will have transformed the film industry in several major ways: 1. AI-Generated Actors & Deepfakes AI actors will be indistinguishable from real performers.

    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.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-4o (Omni): Internal Investment Committee Memo: LedgerLift (Ticker: LLLT) Recommendation: Long 12-Month Price Target Range: $55 - $68 Thesis: LedgerLift demonstrates strong growth potential driven by its robust subscription model and impressive customer retention metrics.

    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.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-4o (Omni): Dish Name: "Ocean’s Whisper in the Forest" Conceptual Narrative: "Ocean’s Whisper in the Forest" is a culinary journey that marries the briny essence of the sea with the earthy depths of the forest.

    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.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-4o (Omni): Here are five jokes for you: Why did the scarecrow win an award? Because he was outstanding in his field! Why don’t skeletons fight each other? They don’t have the guts! Why did the math book look sad? It had too many problems. Why don’t eggs tell jokes? Because they might crack up!

    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.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-4o (Omni): If the transistor had been invented in 1920 instead of 1947, the technological, economic, and geopolitical landscape through 1980 would have been significantly altered.

    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.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-4o (Omni): "AI Now Runs Grandma’s Knitting Circle, Demands Faster Stitching and Blockchain Integration"

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

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-4o (Omni): This architecture is designed to support a real-time collaborative document editor but has several potential failure modes, race conditions, and scaling bottlenecks.

    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.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-4o (Omni): Here are three potentially weak claims in the MindMeld AI pitch, along with explanations and suggestions for strengthening them: Vision: "MindMeld AI reads your brainwaves to predict what you want to type before you think it." Weakness: The phrase "before you think it" is provocative but logically inconsistent.

    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."

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-4o (Omni): To estimate the total number of FLOPs required to train GPT-3, let's break it down into key components. Model Size and Parameters GPT-3 has 175 billion parameters.

    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 ($1.75 \times 10^{11}$).

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-4o (Omni): Sally has only one sister. Explanation: Sally has 3 brothers. Each brother has 2 sisters. The two sisters are Sally and one other girl. Thus, Sally has 1 sister.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GPT-4o (Omni)GPT-4o (Omni)

Inception

2010

Dark Side Of The Moon

suisside

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

GPT-4o (Omni) and Mercury 2.5 Preview compared across 53 shared prompts
SpecGPT-4o (Omni)Mercury 2.5 Preview
Input price$2.5/M tokens$0.04/M tokens
Output price$10/M tokens$0.15/M tokens
Context window128K tokens260K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMay 2024Aug 2026
At 10M a month$25.00$25.00$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-4o (Omni)2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.50 in·$10.00 out·128k·100% up
  • OpenAI$2.50 in·$10.00 out·128k·100% up
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up

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

Common questions

What is the difference between GPT-4o (Omni) and Mercury 2.5 Preview?

GPT-4o (Omni) is developed by OpenAI while Mercury 2.5 Preview is developed by Inception. GPT-4o (Omni) has a 128K token context window vs Mercury 2.5 Preview's 260K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-4o (Omni) or Mercury 2.5 Preview?

It depends on your use case. GPT-4o (Omni) and Mercury 2.5 Preview 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 GPT-4o (Omni) cost compared to Mercury 2.5 Preview?

GPT-4o (Omni) costs $2.5/M input tokens and Mercury 2.5 Preview costs $0.04/M input tokens. Mercury 2.5 Preview is $2.46/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-4o (Omni) and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of GPT-4o (Omni) and Mercury 2.5 Preview 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

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  • Mercury 2.5 Preview58 outputs, specs and price
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