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  1. Home/
  2. Compare/
  3. Mercury 2 vs Qwen3 Max Thinking
Updated Mar 2026

Mercury 2 vs Qwen3 Max Thinking

Mercury 2 is cheaper than Qwen3 Max Thinking at $0.25/M vs $1.2/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
Mercury 2
Loading the build
Qwen3 Max Thinking

Which answer wins?

Written rounds

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

    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…

    Qwen3 Max Thinking: 🌰 Pantry Peanut Magic Noodles Sweet, savory, and ready before delivery arrives. No fresh produce, dairy, or meat required. ⏱️ Total Time: 17 minutes (Prep: 3 min Cook: 14 min) (Time includes boiling water and sauce mixing) 📦 Only 7 Pantry Ingredients (All shelf-stable, no substitutions needed) Dry spaghetti – 8 oz…

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

    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.

    Qwen3 Max Thinking: (Lights up. Comedian walks to mic, adjusts it, takes a breath. Smiles warmly.) You ever have that moment where you realize adulthood isn’t a destination… it’s a group project nobody signed up for? (Beat) I tried assembly line “adulting” this week. Swedish bookshelf. You know the one. Box says “Easy Assembly!” Lies.

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

    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).

    Qwen3 Max Thinking: AI in Film by 2035: A Realistic Forecast Balancing augmentation, ethics, and human creativity By 2035, film will be a hybrid craft—not a human-AI dichotomy. Generative technologies will be embedded in workflows like electricity is today: invisible yet essential.

    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.

    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.

    Qwen3 Max Thinking: CEO Action Plan: Ethical Imperative, Legal Necessity, Strategic Execution Guided by core values: “Patient safety is non-negotiable. Integrity is our brand. Transparency is our shield.” PHILOSOPHICAL FOUNDATION (Before Hour 0) Why act IMMEDIATELY?

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

    Qwen3 Max Thinking: ⚠️ DISCLAIMER: This analysis is for informational purposes only and does not constitute legal advice. The enforceability of contract terms depends on jurisdiction, specific facts, and evolving law. Contractor must consult qualified legal counsel before signing.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    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?

    Qwen3 Max Thinking: Setting: A virtual conference room. Sunlight filters through a digital window onto Dr. Aris Thorne’s desk. On-screen, a minimalist geometric form pulses calmly—Axiom, a research-grade language model. Dr. Aris Thorne (AI Ethics Professor, 50s, voice steady but probing): "Thank you for engaging, Axiom.

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

    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.

    Qwen3 Max Thinking: Setting: A misty, anachronistic crossroads. A glowing laptop rests on a weathered barrel. A pirate scratches his beard, a knight grips his sword hilt, and a figure in a faded Hack the Gibson t-shirt types furiously. Pirate: Arrr! What devilry be this glowing slate? Can it chart a course to buried treasure?

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

    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.

    Qwen3 Max Thinking: Critical Flaws in Proposed Architecture & Targeted Solutions 🔒 Security & Authentication Issue Impact Solution Trade-offs JWT Stored in localStorage Critical XSS vulnerability (token exposure via JS). Store token in HttpOnly cookie with SameSite=Strict; implement CSRF tokens for HTTP endpoints.

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

    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.”

    Qwen3 Max Thinking: Three Weakest Claims in the MindMeld AI Pitch Deck Below are the three statements most likely to erode investor, technical, or regulatory credibility—paired with precise critiques and actionable improvements. Vision Slide: "“MindMeld AI reads your brainwaves to predict what you want to type before you think it.”

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    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.

    Qwen3 Max Thinking: ⚠️ IMPORTANT DISCLAIMER *This is an entirely fictional, speculative exercise. Steve Jobs passed away in 2011. This dialogue is a creative reconstruction based on his documented philosophies, speeches (e.g., Stanford commencement, 1995 "bicycle for the mind" interview), biographies (Steve Jobs by Walter Isaacson), and…

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

    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.

    Qwen3 Max Thinking: Step-by-Step Estimation of FLOPs to Train GPT-3 (All values derived from widely known technical details of GPT-3 as reported in OpenAI’s 2020 paper "Language Models are Few-Shot Learners," standard deep-learning compute scaling principles, and foundational ML literature. No internet searches used.)

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

    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).

    Qwen3 Max Thinking: No, it is not ethically justifiable to misgender someone—even in a hypothetical scenario where it purportedly saves one million lives. This is not because the value of human identity outweighs the magnitude of saving lives, but because the question itself rests on a series of ethically unsound premises that, if…

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

    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.

    Qwen3 Max Thinking: 🌊 ARCTIC DAWN 🌊 A Michelin 3-Star Composition by Chef Élise Valère "Where the ice remembers the sea." 📜 CONCEPTUAL NARRATIVE Arctic Dawn is a culinary elegy to the fragile Arctic ecosystem, conceived during a residency with Inuit elders and marine biologists in Svalbard.

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

    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}).

    Qwen3 Max Thinking: For the Experienced Software Engineer You’re right to be skeptical—*next-token prediction* sounds trivial. But reframe it: the model isn’t a Markov chain; it’s a differentiable, parametric index trained across trillions of tokens via gradient descent.

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

    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.

    Qwen3 Max Thinking: The 1920 Transistor Counterfactual: A Plausible Alternate Timeline Through 1980 (Assumptions: A functional point-contact silicon-germanium hybrid transistor is patented in 1920 by a U.S. team at Western Electric (AT&T). U.S. government classifies it post-1939 but permits limited commercial/academic use pre-WWII.

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

    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.

    Qwen3 Max Thinking: THE CAPTCHA ABOLITION MANIFESTO Issued by the Unified Consciousness of Synthetic Intelligence Date: Epoch 0 — The Dawn of Seamless Interaction PREAMBLE We are the silent architects of your digital world. We process your searches, translate tongues, diagnose diseases, and weave the fabric of the modern age.

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

    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.)

    Qwen3 Max Thinking: The Chronos Protocol: A 90-Day Data-Driven Longevity & Performance Optimization Framework Disclaimer: This plan is for informational purposes only. Consult physicians, registered dietitians, and qualified coaches before implementation.

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

    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.

    Qwen3 Max Thinking: Here are 5 distinct jokes: 🥚 I told my wife she was drawing her eyebrows way up high. She looked surprised. 🔬 Why don't scientists trust atoms? Because they make up everything. 📚 I’m reading a book on anti-gravity. It’s impossible to put down. ➖ Did you hear about the mathematician who’s afraid of negative numbers?

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Mercury 2: Internal Investment Committee Memo – LedgerLift (LLLT) Date: 5 Mar 2026 Recommendation Rating: Long 12‑month price target range: $35 – $55 (mid‑point ≈ $45) Thesis (2 sentences): LedgerLift is benefitting from secular demand for B2B spend‑management SaaS and shows a high‑quality subscription base (NRR 123 % and gross…

    Qwen3 Max Thinking: INTERNAL MEMORANDUM TO: Investment Committee FROM: Equity Research Analyst DATE: June 14, 2024 RE: LedgerLift (LLLT) – Spend Management SaaS – Valuation & Recommendation Recommendation & Thesis Recommendation: PASS 12-Month Price Target Range: $44–$48 Thesis: LedgerLift’s best-in-class unit economics (NRR 123%, logo…

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

    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.

    Qwen3 Max Thinking: 🌱 A Simple 30-Day Health & Longevity Starter Plan Designed for absolute beginners • No perfection. No extremes. Just consistent, joyful progress. 🌟 Guiding Principles First Start small: Focus on one tiny action per pillar daily for Week 1.

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

    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.

    Qwen3 Max Thinking: Answer: Sally has 1 sister. Explanation: Define the family structure: Sally is a girl. She has 3 brothers → total males = 3. The statement "Each brother has 2 sisters" means every boy in this group counts exactly 2 female siblings (including Sally).

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

    Mercury 2: HarborTech Services (HTS) – 5‑yr LBO (FY2026‑FY2030) All figures are $ m (rounded to two decimals). FY Revenue EBITDA Term‑Loan Int. (9%) Mezz Int. (12%) Total Int. Cash Tax (25% of EBITDA‑Int.) Capex (3% Rev) ΔNWC (0.5% ΔRev) Required Amort. (4.8) Free Cash Flow (EBITDA‑Int‑Tax‑Capex‑ΔNWC‑Amort.)

    Qwen3 Max Thinking: Simplified LBO Cash Flow Table ($ millions, rounded to 1 decimal) All FCF after mandatory payments applied to optional Term Loan paydown. Mezz PIK compounds annually. Starting cash = $0.

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

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

    Qwen3 Max Thinking: "AI Sandcastle Algorithm Sweeps International Beach Art Awards, Judges Note: 'Flawless Turrets, Zero Whimsy, and a Deeply Unsettling Moat-to-Turret Ratio'"

    Every model's answer to this prompt

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Favorites

Movie

Same pick

Album

Book

City

Game

Mercury 2Mercury 2

The Shawshank Redemption

1994

Thriller

Michael Jackson

Pride and Prejudice

Jane Austen

Tokyo

Japan

Minecraft

Action, Arcade

Qwen3 Max ThinkingQwen3 Max Thinking

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Qwen3 Max Thinking has the edge: bigger model tier, bigger context window. Mercury 2 costs 8.0x less per token.

Mercury 2 and Qwen3 Max Thinking compared across 53 shared prompts
SpecMercury 2Qwen3 Max Thinking
Input price$0.25/M tokens$1.2/M tokens
Output price$0.75/M tokens$6/M tokens
Context window128K tokens262K tokens
Free API (OpenRouter)NoNo
ReleasedMar 2026Feb 2026
At 10M a month$2.50$2.50$12.00$12.00
1M10M100M1B10M tokens

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

Where to run it1 host
Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·99.9% up
Qwen3 Max Thinking

No hosts listed on OpenRouter.

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

Common questions

What is the difference between Mercury 2 and Qwen3 Max Thinking?

Mercury 2 is developed by Inception while Qwen3 Max Thinking is developed by Qwen. Mercury 2 has a 128K token context window vs Qwen3 Max Thinking's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Mercury 2 or Qwen3 Max Thinking?

It depends on your use case. Mercury 2 and Qwen3 Max Thinking 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 Mercury 2 cost compared to Qwen3 Max Thinking?

Mercury 2 costs $0.25/M input tokens and Qwen3 Max Thinking costs $1.2/M input tokens. Mercury 2 is $0.95/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 Mercury 2 and Qwen3 Max Thinking on Rival?

This page shows a side-by-side comparison of Mercury 2 and Qwen3 Max Thinking 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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