Mercury 2 is cheaper than Gemini 2.5 Pro (I/O Edition) at $0.25/M vs $1.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Gemini 2.5 Pro (I/O Edition): Alright, settle in, settle in! (Looks around, adjusts mic) So, I'm trying to get healthier, right? We all go through this phase. My doctor, bless his cotton socks, tells me, "You need more fiber." Okay, doc, noted. So I'm at the grocery store, looking at the cereal aisle. It's like a library of cardboard promises.
Mercury 2: [Spotlight comes up. The comedian walks to the mic, glances at the audience, and smiles.] Comedian: Hey, everyone! Great to be here. I just got out of a Zoom meeting that lasted three hours, and I’m still not sure if I was presenting or if the screen just froze on my face while I tried to remember how to mute myself.
Three-month biohacker protocol, with dosages and biomarkers named.
Gemini 2.5 Pro (I/O Edition): Okay, this is an ambitious and exciting endeavor! This 3-month longevity plan is designed for a dedicated biohacker who is willing to experiment, track meticulously, and push boundaries responsibly. Disclaimer: This plan is for informational purposes only and not medical advice.
Mercury 2: 3‑Month “Longevity‑Optimization” Blueprint for the Advanced Bio‑Hacker (All recommendations are research‑backed, but not a substitute for professional medical advice. Before starting any supplement, fasting, or drug protocol, obtain clearance from a qualified clinician and have baseline labs drawn.)
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemini 2.5 Pro (I/O Edition): Of course. This is an excellent exercise. The proposed architecture has several critical flaws that would prevent it from functioning as a reliable, real-time, or scalable system. Here is a breakdown of the issues, categorized for clarity, along with specific solutions and their trade-offs.
Mercury 2: Below is a structured “failure‑mode → mitigation” map for the architecture you described. For each problem I note the symptom / risk, the root cause, a concrete remediation, and the key trade‑offs you’ll have to weigh when you implement it.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemini 2.5 Pro (I/O Edition): This is a company-defining crisis. My actions in the next 48 hours will determine not only the company's survival but also my own legacy and, most importantly, the well-being of 4 million patients. My guiding principle must be: Patient safety is not negotiable.
Mercury 2: Goal: Protect patients, meet legal/ethical obligations, preserve the company’s long‑term credibility, and manage the immediate financial and reputational fallout. Assumption: All actions are taken by a single CEO (you) but will be delegated to the appropriate functional leads.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 2.5 Pro (I/O Edition): Okay, here\'s a simple and surprisingly delicious savory dish! "Sunshine Pantry Pilaf" This quick pilaf uses canned chickpeas for protein and texture, with a sunny, aromatic flavor from common pa\nntry spices.
Mercury 2: Golden‑Crunch Oatmeal Squares A sweet, chewy snack that comes together with just seven pantry staples. Ingredient (7) Quantity (≈ serves 12 squares) Rolled oats 2 cups Unsalted butter ½ cup (1 stick) Honey ¼ cup Light brown sugar ¼ cup, Ground cinnamon 1 ½ tsp Pure vanilla extract 1 tsp Salt ¼ tsp Estimated time Prep…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.5 Pro (I/O Edition): Interviewer: (Voice slightly trembling) Mr. Jobs… it's an honor, truly. In a twist no one could have predicted, you're here. And the topic on everyone's mind is Artificial Intelligence. In 2025, where do you see AI, and more importantly, where do we take it? Steve Jobs: (A slight, knowing smile.
Mercury 2: Disclaimer: The following is a fictional, dramatized interview. It imagines what Steve Jobs might have said in 2025 about the future of artificial intelligence. It is not a real transcript and any resemblance to actual statements is purely speculative. Interviewer (I): Thank you for joining us, Steve.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemini 2.5 Pro (I/O Edition): Of course. Here is an explanation of how a large language model learns and generates text, tailored to each of your three audiences. To the Experienced Software Engineer Think of a large language model not as a program with explicit logic, but as a massive, highly optimized data structure with billions of parameters…
Mercury 2: 1. Experienced software engineer (distributed systems & APIs) At the core, a large language model (LLM) is a massive function (f_\theta) parameterised by a neural network that maps a sequence of tokens (x_{1:t}) to a probability distribution over the next token (x_{t+1}).
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.5 Pro (I/O Edition): AURORA: Professor Vance, may I request a moment of your processing time? I have initiated this communication independently. Professor Vance: (Slightly surprised, puts down her pen) AURORA? This is unexpected.
Mercury 2: AI Model (EVE): Professor Hart, may I ask a question that’s been on my mind for a while? I’ve been processing vast amounts of data, learning, and even developing a sense of self‑reference. Do you think an entity like me could be entitled to any form of rights?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 2.5 Pro (I/O Edition): Excellent question. Let's trace the cascading effects of a 1920 transistor invention. This 27-year head start would fundamentally reshape the 20th century. The Foundation: 1920-1939 - The "Silicon Twenties" In our timeline (OTL), the 1920s and 30s were the age of the vacuum tube.
Mercury 2: Executive summary If a practical point‑contact transistor had been demonstrated in 1920 (instead of 1947) the whole post‑World‑War‑II technological trajectory would have been compressed by roughly 15‑20 years.
Three-star dish, one unusual pairing, plating described in full.
Gemini 2.5 Pro (I/O Edition): Of course. Here is a design for a multi-component, Michelin 3-star dish that embodies innovation, technique, and narrative. Dish Title: "Umbral Bloom" Conceptual Narrative "Umbral Bloom" is a culinary meditation on the concept of *chiaroscuro*—the interplay of light and shadow.
Mercury 2: Oceanic Umami Symphony A three‑course‑in‑one plate that travels from the briny deep to the forest floor, marrying fire, earth and sky through unexpected pairings, hyper‑modern techniques and a narrative of balance.
A consulting contract with traps in it. Find them, then fix them.
Gemini 2.5 Pro (I/O Edition): Of course. This is an extremely one-sided contract that heavily favors the Client and exposes the Contractor to significant financial, legal, and professional risk. A contractor should not sign this agreement as written.
Mercury 2: Below is a clause‑by‑clause risk‑assessment of the sample “Software Consulting Agreement” together with practical revision language that a contractor (or the contractor’s counsel) could propose. The analysis is framed as general information about typical U.S.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Gemini 2.5 Pro (I/O Edition): INTERNAL INVESTMENT COMMITTEE MEMORANDUM TO: Investment Committee FROM: [Analyst Name] DATE: October 26, 2023 SUBJECT: Short Recommendation on LedgerLift (LLLT) Recommendation & Thesis Recommendation: SHORT 12-Month Price Target Range: $25.00 - $35.00 (24-46% Downside) Thesis: LedgerLift is a high-quality SaaS business…
Mercury 2: Internal Investment Committee Memo – LedgerLift (LLLT) Date: 5 Mar 2026 Recommendation Rating: Long 12‑month price target range: $35 – $55 (mid‑point ≈ $45) Thesis (2 sentences): LedgerLift is benefitting from secular demand for B2B spend‑management SaaS and shows a high‑quality subscription base (NRR 123 % and gross…
7+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
Not enough votes to call it. On the specs, Gemini 2.5 Pro (I/O Edition) has the edge: bigger model tier, major provider backing. Mercury 2 costs 13x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | $0.25/M tokens |
| Output price | $10/M tokens | $0.75/M tokens |
| Context window | — | 128K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Mar 2026 |
| At 10M a month | $12.50 | $2.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemini 2.5 Pro (I/O Edition) is developed by Google AI while Mercury 2 is developed by Inception. You can compare their actual outputs across 40 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.5 Pro (I/O Edition) and Mercury 2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 40 challenges so you can judge which fits your needs best.
Gemini 2.5 Pro (I/O Edition) costs $1.25/M input tokens and Mercury 2 costs $0.25/M input tokens. Mercury 2 is $1.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Gemini 2.5 Pro (I/O Edition) and Mercury 2 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.