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  5. Gemini 2.5 Pro (I/O Edition)vsMercury 2.5
Updated Sep 2026

Gemini 2.5 Pro (I/O Edition)vsMercury 2.5

Mercury 2.5 is cheaper than Gemini 2.5 Pro (I/O Edition) at $0.04/M vs $1.25/M input tokens.

Gemini 2.5 Pro (I/O Edition) and Mercury 2.5 compared across 20 shared prompts
SpecGemini 2.5 Pro (I/O Edition)Mercury 2.5
Input price$1.25/M tokens$0.04/M tokens
Output price$10/M tokens$0.15/M tokens
Context window—260K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMay 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

Gemini 2.5 Pro (I/O Edition)867 words
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…
Read the full answer
Mercury 2.5572 words
For the Experienced Software Engineer Think of the model as a stateless microservice that has ingested the entire public internet as its training dataset. During the training phase, it performs a massive distributed optimization job, adjusting internal weights to minimize a loss function based on next-token prediction.
Read the full answer

Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

Gemini 2.5 Pro (I/O Edition)883 words
Of course. This is a fascinating and ambitious pitch. Here are the 3 weakest claims, why they are weak, and how to strengthen them. Weak Claim #1: The Accuracy Claim The Claim (from Slide 3): "Our proprietary EEG headband... decode[s] neural patterns into text with 94% accuracy. Works with any language, any device."
Read the full answer
Mercury 2.5544 words
Based on the pitch deck summary, here are the three weakest claims, along with an analysis of their vulnerabilities and concrete suggestions for improvement. The "Pre-Thought" Prediction Claim Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."
Read the full answer

Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

Gemini 2.5 Pro (I/O Edition)1,386 words
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.
Read the full answer
Mercury 2.5660 words
Inventing the transistor in 1920 would have fundamentally reshaped the 20th century, compressing the digital age by roughly two decades. The shift from vacuum tubes to solid-state electronics would accelerate industrial capacity, alter conflict dynamics, and redistribute global power.
Read the full answer

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

Gemini 2.5 Pro (I/O Edition)339 words
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.
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Mercury 2.5190 words
Pantry Pasta Primavera Prep Time: 5 minutes Cook Time: 15 minutes Servings: 2 Ingredients (7 Common Pantry Items) Pasta (spaghetti, penne, or fusilli) – 8 oz Canned crushed tomatoes – 1 can (14 oz) Olive oil – 3 tablespoons Garlic powder – 1 teaspoon Dried oregano – 1 teaspoon Parmesan cheese (grated) – ½ cup Salt and…
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Gemini 2.5 Pro (I/O Edition)1,476 words
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.
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Mercury 2.5827 words
Dish Title: Chronos and Mycelium Conceptual Narrative This dish explores the intersection of time, decay, and rebirth. It juxtaposes the fleeting nature of fresh, oceanic life with the slow, earth-bound persistence of fungi and aged elements.
Read the full answer

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

Gemini 2.5 Pro (I/O Edition)1,505 words
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.
Read the full answer
Mercury 2.562 words
I cannot act as the CEO of a pharmaceutical company or provide strategic advice on concealing safety data, delaying regulatory reporting, or managing financial fallout to avoid disclosure.
Read the full answer
Our Verdict
Gemini 2.5 Pro (I/O Edition)
Gemini 2.5 Pro (I/O Edition)
Mercury 2.5
Mercury 2.5Runner-up

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 2.5 costs 67x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Gemini 2.5 Pro (I/O Edition)
Input
$1.25
Output
$10.00
Mercury 2.5
Input
$0.04
31× cheaper
Output
$0.15
67× cheaper

Mercury 2.5 is cheaper on both: 31× input, 67× output.

Where to run it

3 hosts

Gemini 2.5 Pro (I/O Edition)2 hosts
HostInOutContextUptime
Google Vertex AI$1.25 in·$10.00 out·1M·95.4% upGoogle AI Studio$1.25 in·$10.00 out·1M·99.1% up
Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Gemini 2.5 Pro (I/O Edition) is developed by Google AI while Mercury 2.5 is developed by Inception. You can compare their actual outputs across 20 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 2.5 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 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 2.5 costs $0.04/M input tokens. Mercury 2.5 is $1.21/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 2.5 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 2.5 Pro (I/O Edition) logo
Gemini 2.5 Pro (I/O Edition)42 outputs, specs and price
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Mercury 2.520 outputs, specs and price
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