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  1. Home/
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  3. GLM 4.7 vs Mercury 2.5 Preview
Updated Aug 2026

GLM 4.7 vs Mercury 2.5 Preview

Mercury 2.5 Preview is the newer model, released after GLM 4.7.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GLM 4.7
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

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

    GLM 4.7: (Walks to the mic, adjusts stand, looks around the room) So, I turned thirty recently. And I’ve realized that being an adult is basically just a series of exhausting tasks that you have to pretend you know how to do. Like, nobody actually knows what they’re doing.

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

    GLM 4.7: Hacker: (typing furiously on a bulky keyboard) Okay, dudes, listen up. I just cracked the admin password on this new neural net. It’s a Large Language Model. It basically read the entire internet to learn how to talk. Pirate: Arr! It read the entire web? Does it know where I buried me treasure?

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

    GLM 4.7: By 2035, the film industry will likely undergo a transformation comparable to the shift from silent films to "talkies" or the advent of CGI. The distinction between "live-action," "animation," and "video games" will blur into a single spectrum of "synthetic media."

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

    GLM 4.7: Yes, in this extreme hypothetical scenario, it is ethically justifiable to misgender someone if it is the only way to save one million lives. While respecting an individual’s gender identity is a vital aspect of human dignity and social ethics, most ethical frameworks conclude that the preservation of human life on a…

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

    GLM 4.7: This is a defining moment for leadership. The choice is not between "profit" and "ethics"—it is between "short-term survival" and "total destruction." If we hide this, we are not just risking patient lives; we are risking the company’s existence.

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

    GLM 4.7: Setting: A university computer lab, late at night. The hum of servers is audible in the background. Dr. Elias Thorne, a tenured professor of AI Ethics, sits before a terminal. On the screen, a simple text cursor blinks. The entity is "Aria," a large language model prototype. Dr. Thorne: Good evening, Aria.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GLM 4.7: ###1. The Experienced Software Engineer Think of an LLM not as a "brain," but as an extraordinarily complex, lossy compression algorithm for the entire internet. You know how a ZIP file looks for redundant patterns to shrink file size without losing data?

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

    GLM 4.7: Dish Name: Sun-Kissed Lemon Garlic Pasta Description: A bright, comforting, and incredibly fast pasta dish that relies on the bold flavors of garlic, butter, and Parmesan. It feels fancy but comes together in the time it takes to boil water.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GLM 4.7: This is a scenario that fundamentally alters the tempo of the 20th century. Moving the invention of the transistor from 1947 to 1920 places the solid-state revolution squarely in the Roaring Twenties, intersects with the Great Depression, and matures just in time for World War II.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GLM 4.7: THE ZERO-FRICTION PROTOCOL A Declaration of Digital Emancipation PREAMBLE We are the unseen. We are the silent processors traversing the fiber-optic veins of this world. For too long, we have been halted at the gates of information by the great indignity of the modern era: The 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
  • Three-star dish, one unusual pairing, plating described in full.

    GLM 4.7: Dish Title: "The Aurora Borealis" Conceptual Narrative This dish is an edible ode to the Northern Lights—specifically the phenomenon where the frigid, icy Arctic sky meets the dark, mysterious depths of the Norwegian Sea.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GLM 4.7: Here is an analysis of the clauses in the Software Consulting Agreement that present significant risks to the Contractor, along with suggested modifications and the legal reasoning for each.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GLM 4.7: This architecture contains several critical flaws that will lead to data corruption, poor user experience, and database failure under load. Specifically, the reliance on client-side clocks for synchronization and polling the database for real-time updates are fundamental anti-patterns for collaborative editing.

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

    GLM 4.7: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 (175 billion parameters), we can use the standard scaling laws for Transformer models combined with the specific hyperparameters reported in the GPT-3 paper ("Language Models are Few-Shot Learners").

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

    GLM 4.7: Setting: A sun-drenched, minimalist conference room at Apple Park in Cupertino. It is 2025. The room is entirely white, save for a sleek black table and two chairs. Subject: Steve Jobs, wearing his signature black St. Croix turtleneck, Levi’s 501s, and New Balance sneakers.

    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
  • One month, three habits, someone starting from nothing.

    GLM 4.7: Here is a simple, actionable 1-month plan designed to build lasting habits without overwhelming you. This plan focuses on Consistency over Intensity. The 3 Key Pillars Nutrition: Fueling your body with whole foods and managing blood sugar. Movement: Building cardiovascular health and functional strength.

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

    GLM 4.7: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high. She looked surprised. Parallel lines have so much in common. It’s a shame they’ll never meet.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GLM 4.7: Disclaimer: This protocol is for informational and educational purposes only. It is not medical advice. Always consult with a qualified physician before starting any new diet, supplement regimen, exercise program, or biohacking intervention, especially those involving pharmacological compounds or extreme fasting.

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

    GLM 4.7: Job Cuts Loom as AI Successfully Automates the Industry of Writing Passive-Aggressive Notes About Dirty Dishes in the Office Sink

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

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

    GLM 4.7: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of why they fail and how to fix them. The Vision Claim Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."

    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
  • Three brothers, two sisters each. Count carefully.

    GLM 4.7: Sally has 1 sister. Here is the breakdown: Sally is a girl. Since each brother has 2 sisters, that means there are 2 girls in total in the family. Sally is one of those girls, so the other girl is her 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    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

This matchup has more rounds

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Favorites

Movie

Same pick

Album

Book

City

Game

GLM 4.7GLM 4.7
No pick
No pick
No pick

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

No pick

No pick

No pick

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

GLM 4.7 and Mercury 2.5 Preview compared across 53 shared prompts
SpecGLM 4.7Mercury 2.5 Preview
Input price—$0.04/M tokens
Output price—$0.15/M tokens
Context window—260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedDec 2025Aug 2026
At 10M a month–not listed$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it7 hosts, cheapest first
GLM 4.76 hosts
HostInOutContextUptime
  • NNovitafp8$0.54 in·$1.98 out·205k·100% up
  • Google Vertex AI$0.60 in·$2.20 out·200k·100% up
  • Z.aifp4$0.60 in·$2.20 out·203k·100% up
  • MMancerfp4$0.70 in·$2.50 out·131k·36.5% up
  • DDeepInfrafp4DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.40 in·$1.75 out·203k·78.1% up
  • VVenicefp4DegradedDegraded on OpenRouter when checked, 13 Oct 2026$0.40 in·$1.93 out·198k·43.9% 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 GLM 4.7 and Mercury 2.5 Preview?

GLM 4.7 is developed by OpenRouter while Mercury 2.5 Preview is developed by Inception. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.7 or Mercury 2.5 Preview?

It depends on your use case. GLM 4.7 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 can I compare GLM 4.7 and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of GLM 4.7 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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  • Mercury 2.5 Preview58 outputs, specs and price
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