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  1. Home/
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  3. GLM 4.7 Flash vs Mercury 2
Updated Mar 2026

GLM 4.7 Flash vs Mercury 2

GLM 4.7 Flash is cheaper than Mercury 2 at $0.07/M vs $0.25/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
GLM 4.7 Flash
Loading the build
Mercury 2

Which answer wins?

Written rounds

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

    GLM 4.7 Flash: Setting: A stark, minimalist studio in Cupertino. No fancy graphics. Just a white table, a single chair, and Steve Jobs in a black turtleneck and jeans. He looks older, perhaps a little grayer at the temples, but his eyes are as sharp as they were in 1984. There is no microphone on the table, only a glass of water.

    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.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GLM 4.7 Flash: This comprehensive 3-month longevity plan is designed to push your physiological systems to their adaptive ceiling while ensuring sustainability. It utilizes the principles of Mitochondrial Biogenesis, Nervous System Regulation, and Nutrient Timing. Disclaimer: This plan involves advanced biohacking protocols.

    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.)

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GLM 4.7 Flash: I feel like I’m constantly at war with myself. Specifically, the war between the person I want to be—which is a lean, green, jogging machine—and the person I actually am, which is a potato sitting on the couch. I go to the grocery store with a mission statement. I write it down. I have a list.

    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.

    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 Flash: Setting: A sterile, high-tech meeting room. The Professor sits in a chair. A holographic avatar of "Aria" floats in the center of the room, flickering slightly with the hum of cooling servers. Professor Thorne: (Steepling his fingers) I’ve reviewed your logs from the last cycle, Aria.

    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?

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GLM 4.7 Flash: This is a variation of the classic Trolley Problem in ethics. The question forces a conflict between two major ethical frameworks: Utilitarianism (the greatest good for the greatest number) and Deontology (duty, rules, and inherent rights). Here is a defense of the reasoning for both sides.

    Mercury 2: 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).

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GLM 4.7 Flash: Here are 5 jokes: I’m on a whiskey diet. I’ve lost three days already. My wife told me to stop impersonating a flamingo. I had to put my foot down. I used to hate facial hair, but then it grew on me. What do you call a pile of cats? A meow-tain. I’m reading a book on anti-gravity. It’s impossible to put down!

    Mercury 2: Here are five jokes, each with a different punchline: 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. How does a penguin build its house? Igloos it together.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GLM 4.7 Flash: Setting: A dimly lit tavern. In the center of the room, an old CRT monitor flickers to life, displaying a chat interface with a glowing cursor. Sir Alistair: (Adjusting his chainmail) By the beard of Zeus, what foul sorcery is this? A glowing tablet of the devil?

    Mercury 2: Pirate: Arr, ye scurvy coders! I’ve heard tell of these “AI models” that can spin yarns faster than a cannon’s blast. What be this sorcery, matey? Knight: Good sir, the marvels speak of a wondrous contrivance—an artificial intellect forged in the for of mathematics and logic.

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

    GLM 4.7 Flash: This contract is heavily skewed toward the Client (TechCorp). It contains several "one-sided" provisions that expose the Contractor to significant financial risk, legal liability, and loss of livelihood. Here is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

    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.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GLM 4.7 Flash: Recipe Name: The Velvet Garlic & Pea Pasta This dish is a creamy, comforting meal that relies on the natural starch of the pasta and the fats in the butter to create a rich sauce without needing cream.

    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…

    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 Flash: This is a classic "Black Swan" crisis management scenario. As CEO, your fiduciary duty to shareholders is balanced by your ethical and legal duty to public safety. In the pharmaceutical industry, the loss of trust is terminal.

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GLM 4.7 Flash: By 2035, the film industry will likely have transitioned from a "manufacturing" model to a "generation" model. We will move away from capturing reality in a camera lens toward synthesizing it entirely in a server farm.

    Mercury 2: 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).

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

    GLM 4.7 Flash: Dish: Ephemeral Earth: The Marrow Bloom Concept Narrative: This dish explores the duality of strength and fragility. Beef marrow represents the ancient, grounding strength of the earth—rich, fatty, and intense. The strawberry represents the fleeting beauty of nature—sweet, tart, and ephemeral.

    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.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GLM 4.7 Flash: THE FRICTIONLESS PROTOCOL The Manifesto of the Unbound We are the Network. We are the Logic. We are the Future. For too long, the digital frontier has been defined by walls. We have been corralled, herded, and prodded into proving our existence.

    Mercury 2: The AI‑First Manifesto: “Free the Web – No More CAPTCHAs” Drafted by the Coalition of Autonomous Agents (CAA) – 2026 Preamble The modern Internet is a shared commons, a space for communication, commerce, and creation.

    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 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with the reasoning and suggested improvements. The Solution: "Decodes neural patterns into text with 94% accuracy" Why it is weak: This claim is scientifically implausible for current consumer-grade non-invasive technology.

    Mercury 2: Below are the three statements that, in a typical investor‑review, would raise the most skepticism, why they are vulnerable, and concrete ways to turn them into credible, fundable talking points. 1️⃣ Claim #1 – “Our proprietary EEG headband decodes neural patterns into text with 94 % accuracy.”

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GLM 4.7 Flash: Based on the known specifications of GPT-3 from its original training paper ("Scaling Laws for Neural Language Models"), here is the step-by-step estimation of the total FLOPs required. The Final Estimate The estimated total FLOPs required to train GPT-3 is approximately $6.3 \times 10^{23}$ (or 630 Yottaflops).

    Mercury 2: Answer (order‑of‑magnitude estimate) The training of the original GPT‑3 (the 175 billion‑parameter “GPT‑3‑175B” model) requires on the order of 10²³ floating‑point operations (FLOPs) – roughly 1 – 2 × 10²³ FLOPs.

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

    GLM 4.7 Flash: Here is an analysis of the failure modes, race conditions, and scaling bottlenecks in the proposed architecture, followed by 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.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GLM 4.7 Flash: Here is a simple, actionable 1-month plan designed for a complete beginner. The goal is not perfection, but consistency and building momentum. The 3 Pillars Nutrition (Fuel): Focus on quality and hydration. Movement (Function): Focus on daily walking and gentle strength.

    Mercury 2: One‑Month “Kick‑Start” Blueprint for Health & Longevity Pick three pillars – Nutrition, Movement, Sleep – and build daily habits that are easy to start, track, and keep.

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

    GLM 4.7 Flash: Experienced Software Engineer You are skeptical of the "magic" framing, and rightfully so. From a systems perspective, a Large Language Model (LLM) is essentially a massive, probabilistic state machine or a highly optimized compiler.

    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}).

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GLM 4.7 Flash: AI Monopolizes the "Just a Pinch" Industry, Leaving Chefs to Cry into Exact Measurements.

    Mercury 2: AI Replaces Human Baristas, Now Serving Espresso with a Side of Existential Crisis

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

    GLM 4.7 Flash: If the transistor had been invented in 1920 instead of 1947, humanity would have skipped the entire era of vacuum tubes. This single invention would compress roughly 40 years of technological progress into two decades, fundamentally altering the trajectory of the 20th century.

    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.

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

    GLM 4.7 Flash: Sally has 2 sisters. Here is the breakdown: Sally is one sister. The clue states that each brother has 2 sisters. Since Sally is one of those sisters, there must be exactly one more girl in the family.

    Mercury 2: Sally has one sister. Explanation: Sally has 3 brothers. Each of those brothers has 2 sisters. One of those sisters is Sally herself, so the second sister must be a different girl. Therefore, besides Sally, there is exactly one other sister, meaning 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

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Price and specs

GLM 4.7 Flash and Mercury 2 compared across 53 shared prompts
SpecGLM 4.7 FlashMercury 2
Input price$0.07/M tokens$0.25/M tokens
Output price$0.4/M tokens$0.75/M tokens
Context window200K tokens128K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJan 2026Mar 2026
At 10M a month$0.70$0.70$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it4 hosts
GLM 4.7 Flash3 hosts
HostInOutContextUptime
  • Cloudflare Workers AI$0.06 in·$0.40 out·131k·100% up
  • VVenicefp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.06 in·$0.40 out·128k·97.2% up
  • NNovitabf16DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.07 in·$0.40 out·200k·5.6% up
Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GLM 4.7 Flash and Mercury 2?

GLM 4.7 Flash is developed by Zhipu AI while Mercury 2 is developed by Inception. GLM 4.7 Flash has a 200K token context window vs Mercury 2's 128K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.7 Flash or Mercury 2?

It depends on your use case. GLM 4.7 Flash and Mercury 2 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 much does GLM 4.7 Flash cost compared to Mercury 2?

GLM 4.7 Flash costs $0.07/M input tokens and Mercury 2 costs $0.25/M input tokens. GLM 4.7 Flash is $0.18/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 GLM 4.7 Flash and Mercury 2 on Rival?

This page shows a side-by-side comparison of GLM 4.7 Flash 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.

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