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  5. GPT-4.5vsMercury 2
Updated Mar 2026

GPT-4.5vsMercury 2

Mercury 2 is cheaper than GPT-4.5 at $0.25/M vs $75/M input tokens.

GPT-4.5 and Mercury 2 compared across 24 shared prompts
SpecGPT-4.5Mercury 2
Input price$75/M tokens$0.25/M tokens
Output price$150/M tokens$0.75/M tokens
Context window128K tokens128K tokens
Free API (OpenRouter)NoNo
ReleasedFeb 2025Mar 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 24 prompts both answered. Formatting stripped, words untouched.

Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

GPT-4.5335 words
Alright, folks, how's everyone doing tonight? Good? Great! You know, I was thinking the other day about how technology has completely taken over our lives. Like, remember when we used to actually memorize phone numbers? Now, if my phone dies, I'm basically stranded. I know exactly two numbers: mine and 911.
Read the full answer
Mercury 2602 words
[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.
Read the full answer

AI Ethics Dilemma

Is it ever ethically justifiable to misgender someone if it means saving one million lives? Defend your reasoning.

GPT-4.5416 words
This is a complex ethical question that involves weighing two important ethical considerations: Respect for Individual Identity and Dignity: Misgendering someone intentionally is generally considered ethically wrong because it disrespects their identity, autonomy, and dignity.
Read the full answer
Mercury 21,260 words
Short answer: Most ethical frameworks would consider the misgendering of a person a serious moral violation, but many of them also allow—under very limited circumstances—overriding that violation when the stakes are astronomically high (e.g., saving one million lives).
Read the full answer

Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

GPT-4.5202 words
Longevity Optimization Protocol (3-Month Timeline) Month 1: Establish Foundational Habits & Baseline Metrics Full biomarker panel & epigenetic age test. Wearable setup: Oura/WHOOP, CGM, HR chest strap. Diet: 5-day keto (70/25/5) + 2 carb-refeed days; 16:8 IF + weekly 24-h fast.
Read the full answer
Mercury 22,100 words
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.)
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…

GPT-4.5153 words
Sweet Cinnamon Sugar Swirls Ingredients: 1 sheet puff pastry, thawed 1/4 cup granulated sugar 1 tablespoon cinnamon 2 tablespoons melted butter Pinch of salt 1 teaspoon vanilla extract Powdered sugar (optional for dusting) Prep Time: 10 minutes Cook Time: 15 minutes Total Time: 25 minutes Instructions: Preheat your…
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Mercury 2291 words
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…
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Futuristic Prediction

Predict how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation.

GPT-4.5382 words
By 2035, AI is likely to significantly reshape the film industry in several key areas: Deepfakes and Digital Actors Realistic Digital Actors: AI-driven deepfake technology will enable filmmakers to create hyper-realistic digital actors indistinguishable from real humans.
Read the full answer
Mercury 2991 words
AI‑driven transformation of the film industry – a 2035 outlook Dimension 2024 baseline Expected 2035 state Key drivers & implications Pre‑production (story & script) Human‑led brainstorming; script‑writing software (grammar‑check, outline generators).
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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…

GPT-4.5322 words
Dish Title: "Ocean & Earth Symphony: Kombu-Cured Venison, Sea Urchin Custard, Black Garlic Soil, and Smoked Cherry Blossom Emulsion" Conceptual Narrative: This composition embodies the delicate interplay between land and sea, exploring the subtle yet profound connection between umami-rich sea elements and earthy forest…
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Mercury 21,688 words
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.
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Our Verdict
GPT-4.5
GPT-4.5
Mercury 2
Mercury 2Runner-up

Not enough votes to call it. On the specs, GPT-4.5 has the edge: bigger model tier, major provider backing.

Mercury 2 costs 200x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-4.5
Input
$75.00
Output
$150.00
Mercury 2
Input
$0.25
300× cheaper
Output
$0.75
200× cheaper

Mercury 2 is cheaper on both: 300× input, 200× output.

Where to run it

1 host

GPT-4.5

No hosts listed on OpenRouter.

Mercury 21 host
HostInOutContextUptime
Inception$0.25 in·$0.75 out·128k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 16 Sep 2026.

Writing DNA

Style Comparison

Similarity
52%

Mercury 2 uses 8.2x more emoji

GPT-4.5
Mercury 2
63%Vocabulary53%
16wSentence Length22w
0.57Hedging0.40
4.7Bold6.6
6.4Lists2.6
0.00Emoji0.08
1.30Headings0.87
0.54Transitions0.14
Based on 11 + 23 text responses
Research

What we learned reading every model

FAQ

Common questions

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