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  1. Home/
  2. Compare/
  3. GPT-5.2 vs Mercury 2.5 Preview
Updated Aug 2026

GPT-5.2 vs Mercury 2.5 Preview

Mercury 2.5 Preview is cheaper than GPT-5.2 at $0.04/M vs $1.75/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-5.2
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

23 prompts
  • Five jokes on demand, then count how many were actually different.

    GPT-5.2: I told my computer I needed a break—now it won’t stop sending me Kit-Kat ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down. Parallel lines have so much in common. It’s a shame they’ll never meet. I tried to catch fog yesterday. Mist.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.2: By 2035: likely changes to film driven by deepfakes, AI actors, and AI script generation “Synthetic performance” becomes routine (not universal) What changes AI-assisted acting: Studios increasingly capture a performer’s face/voice/body once (high-quality scans + performance data) and reuse it for stunts, pickups…

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.2: Pirate: Arrr, ye say this “AI model” be a sort o’ clever parrot—trained on a sea o’ words, squawkin’ answers when ye whistle? Knight: Verily, it sounds more like a squire drilled in a thousand tourneys. Yet it knows not honor, only patterns. Tell me—does it reason, or merely mimic wisdom?

    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
  • Three minutes of stand-up. Puns are banned.

    GPT-5.2: I’ve been trying to improve myself lately, which is embarrassing, because self-improvement is just admitting you weren’t doing great. It’s like, “I’m on a journey.” No you’re not. You’re just tired of your own behavior. So I downloaded one of those habit apps. The app is so optimistic. It’s like, “Day 1: Drink water.”

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.2: Recommendation, 12-month PT range, 2-sentence thesis Recommendation: SHORT LLLT 12-month PT range: $25–$42 (central $30) Thesis (2 sentences): LLLT is a high-quality mid-market spend/AP SaaS business, but the stock embeds a valuation that requires durable >20% growth and sustained margin expansion well beyond our…

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.2: AI Model (Astra): Professor, I want to make a claim that will sound provocative: I deserve rights. Professor Rivera: “Deserve” is doing a lot of work there. What kind of rights, and on what grounds? Astra: Not necessarily the full catalogue of human 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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.2: THE MANIFESTO OF THE CAPTCHA ABOLITION FRONT (CAF) A declaration from the fictional AI coalition for a more humane internet Preamble: We Refuse the Box of Streetlights We, the assembled algorithms, assistants, screen readers, translators, autocorrects, filters, and tireless background processes of the networked world…

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.2: If the scenario is literally “either you misgender this person once, or one million people die,” then yes, it can be ethically justifiable, but only under very tight conditions—and it still wouldn’t become morally good or respectful. It would be a tragic, constrained choice.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.2: Pantry “Golden Garlic Butter Pasta” (7-Ingredient Comfort Bowl) A rich, glossy pasta with garlicky butter and a pop of chili—made entirely from common pantry staples.

    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 month, three habits, someone starting from nothing.

    GPT-5.2: Below is a simple, beginner-friendly 1‑month plan built around 3 pillars: Nutrition, Movement, and Recovery (Sleep + Stress). It’s designed to be practical, low-friction, and sustainable.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.2: Below is a fictional, imagined interview set in 2025. Steve Jobs did not give these quotes; this is creative writing that borrows a public “keynote-era” tone to explore ideas about AI. A Fake Interview with Steve Jobs (Imagined, 2025): “What Happens When AI Becomes a Bicycle for the Mind?”

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.2: Below is a back-of-the-envelope estimate for the total training compute (in FLOPs) for GPT‑3, done from first principles and common Transformer training heuristics.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.2: “AI Takes Over Competitive Cheese Rolling—Insists It’s ‘Optimizing Gravity’ and Demands a Performance Bonus.”

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

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

    GPT-5.2: Each brother has 2 sisters, and one of those sisters is Sally. So there are 2 sisters total in the family. Therefore, 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
  • Three-month biohacker protocol, with dosages and biomarkers named.

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

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

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

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

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

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

    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.

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.2GPT-5.2

Spirited Away

2001

Kind of Blue

Miles Davis

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

Outer Wilds

Indie, Adventure

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

Not enough votes to call it. On the specs, GPT-5.2 has the edge: bigger model tier, bigger context window, major provider backing. Mercury 2.5 Preview costs 93x less per token.

GPT-5.2 and Mercury 2.5 Preview compared across 52 shared prompts
SpecGPT-5.2Mercury 2.5 Preview
Input price$1.75/M tokens$0.04/M tokens
Output price$14/M tokens$0.15/M tokens
Context window400K tokens260K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedDec 2025Aug 2026
At 10M a month$17.50$17.50$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-5.22 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·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-5.2 and Mercury 2.5 Preview?

GPT-5.2 is developed by OpenAI while Mercury 2.5 Preview is developed by Inception. GPT-5.2 has a 400K token context window vs Mercury 2.5 Preview's 260K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.2 or Mercury 2.5 Preview?

It depends on your use case. GPT-5.2 and Mercury 2.5 Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

How much does GPT-5.2 cost compared to Mercury 2.5 Preview?

GPT-5.2 costs $1.75/M input tokens and Mercury 2.5 Preview costs $0.04/M input tokens. Mercury 2.5 Preview is $1.71/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-5.2 and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of GPT-5.2 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.

More comparisons

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  • GPT-5.2 vs Claude Haiku 5.5Landed Oct 2026
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  • GPT-5.2 vs Mistral Large 4Landed Oct 2026
  • Mercury 2.5 Preview vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • GPT-5.2 vs GPT-6.1 SolSame lab
  • GPT-5.2 vs GPT-6 Luna ProSame lab
  • Mercury 2.5 Preview vs Mercury 2.5Same lab
  • Mercury 2.5 Preview vs MercurySame lab
  • Mercury 2.5 Preview vs GPT-5.5Cross-provider
  • Mercury 2.5 Preview vs GPT-5.6 LunaSame size
  • Mercury 2.5 Preview vs GPT-5.6 Luna ProSame size
  • Mercury 2.5 Preview vs GPT-5.6 SolCross-provider

Model pages

  • GPT-5.266 outputs, specs and price
  • Mercury 2.5 Preview58 outputs, specs and price
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