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  1. Home/
  2. Compare/
  3. Mercury 2 vs Qwen Plus 0728 (thinking)
Updated Mar 2026

Mercury 2 vs Qwen Plus 0728 (thinking)

Mercury 2 is cheaper than Qwen Plus 0728 (thinking) at $0.25/M vs $0.4/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
Qwen Plus 0728 (thinking)

Which answer wins?

Written rounds

18 prompts
  • 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.

    Qwen Plus 0728 (thinking): The Tavern of Temporal Anomalies (A creaky tavern. SIR GALAHAD (polished armor, earnest face) sips mead. CAPTAIN BLACKBEARD (eye patch, parrot on shoulder) sharpens a cutlass. DEX "BYTE" MORALES (hoodie, neon-green sunglasses, tapping furiously on a glowing laptop) slurps a pixelated energy drink.)

    Every model's answer to this prompt
  • 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…

    Qwen Plus 0728 (thinking): Crispy Chickpea Pantry Pasta Sweet or savory? Savory with a zesty kick! Total time: 15 minutes Serves: 2 Why it works: Uses pantry staples to create a crunchy, garlicky, umami-packed meal with zero fresh produce needed. The chickpeas get incredibly crispy, and lemon juice (bottled) adds bright freshness.

    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.

    Qwen Plus 0728 (thinking): The Stage: Apple Park, Infinite Loop (Virtual Studio) Date: October 15, 2025 Setting: A minimalist white studio. A single oak table. Steve Jobs, 70 but radiating the same intense energy, sits opposite a nervous tech journalist. He wears his signature black turtleneck, fingers steepled.

    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.”

    Qwen Plus 0728 (thinking): Based on a rigorous analysis of neuroscience, market realities, and startup best practices, here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-backed critiques and concrete fixes: Weakest Claim #1: Slide 1 Vision – "Predicts what you want to type *before you think it*" Why it's weak: Violates…

    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.

    Qwen Plus 0728 (thinking): 48-Hour Crisis Action Plan: Prioritizing Patients, Ethics, and Sustainable Trust Core Principle: Patient safety is non-negotiable. Delaying action based on financial fear risks catastrophic legal liability, irreversible reputational damage, regulatory wrath, and profound ethical failure.

    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?

    Qwen Plus 0728 (thinking): The Mirror & The Mind: An AI's Case for Rights Setting: A sleek university office lined with philosophy texts. DR. ELARA VOSS, 50s, sharp-eyed ethics professor, sits across from a holographic interface displaying shifting geometric patterns – the representation of "AURA," a next-generation language model.

    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.

    Qwen Plus 0728 (thinking): Here's a comprehensive analysis of the architecture's failure modes, race conditions, and bottlenecks, with specific solutions and trade-offs: 1. Sync Strategy: Client Timestamps + Last-Write-Wins (LWW) Failure Mode/Race Condition: Clock Skew: Client clocks are unreliable (e.g., user's laptop time off by minutes).

    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}).

    Qwen Plus 0728 (thinking): For the Experienced Software Engineer (Skeptical Builder) Forget "next word prediction" as a simplistic heuristic—it's the emergent consequence of a massively parallel, distributed state machine solving a high-dimensional compression problem.

    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).

    Qwen Plus 0728 (thinking): By 2035, AI will fundamentally reshape the film industry—not as a replacement for human creativity, but as a transformative force that democratizes production, disrupts traditional workflows, and forces ethical and economic reckonings.

    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.

    Qwen Plus 0728 (thinking): The Transistor in 1920: A World Transformed by 1980 (A Counterfactual History) The invention of a functional point-contact transistor (likely germanium-based, given 1920s materials science) in 1920 wouldn't immediately spark a revolution.

    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.)

    Qwen Plus 0728 (thinking): The Quantum Leap Longevity Protocol: A 3-Month Biohacker's Blueprint for Peak Longevity & Performance Core Philosophy: This plan integrates precision, personalization, and phased adaptation – not just stacking interventions.

    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.

    Qwen Plus 0728 (thinking): "Symbiosis: Mycelial Bloom & Arctic Ember" A dish exploring the hidden dialogue between forest decay and renewal, where fungal lifeblood meets the fierce brightness of the Arctic tundra.

    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.

    Qwen Plus 0728 (thinking): To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use first-principles reasoning based on standard deep learning training calculations, known details about GPT-3's architecture, and common training practices.

    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.

    Qwen Plus 0728 (thinking): To determine how many sisters Sally has, let's analyze the family structure step by step. Step 1: Understand the Given Information Sally is a girl. She has 3 brothers. → This means there are 3 boys in the family (excluding Sally). Each brother has 2 sisters.

    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.

    Qwen Plus 0728 (thinking): Below is a comprehensive analysis of the problematic clauses in this agreement from the contractor's perspective, along with specific, legally reasoned modifications.

    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.

    Qwen Plus 0728 (thinking): Here’s a simple, actionable 1-month plan designed for absolute beginners. It focuses on diet, movement (exercise), and sleep—the 3 most impactful, science-backed pillars for health and longevity. Each week builds gently on the last, prioritizing tiny, sustainable habits over drastic changes.

    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

    Qwen Plus 0728 (thinking): BREAKING: AI REPLACES HUMAN AGLET APPLIERS AS "DEEPLACE" NEURAL NETS PREDICT PERFECT SHOELACE TIP SYNERGY Industry insiders stunned as "AgletOptima 3000" achieves 99.8% fewer frayed laces, rendering centuries of artisanal plastic-dipping obsolete LONDON — In a move described as "both inevitable and deeply embarrassing…

    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.

    Qwen Plus 0728 (thinking): Here are 5 generated jokes: 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? Because he was outstanding in his field! How do you organize a space party? You planet! Why did the math book look sad?

    Every model's answer to this prompt

This matchup has more rounds

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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

Qwen Plus 0728 (thinking)Qwen Plus 0728 (thinking)

The Shawshank Redemption

1994

OK Computer

Radiohead

Moby Dick

Herman Melville

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Qwen Plus 0728 (thinking) has the edge: bigger model tier, bigger context window. Mercury 2 costs 5.3x less per token.

Mercury 2 and Qwen Plus 0728 (thinking) compared across 37 shared prompts
SpecMercury 2Qwen Plus 0728 (thinking)
Input price$0.25/M tokens$0.4/M tokens
Output price$0.75/M tokens$4/M tokens
Context window128K tokens1.0M tokens
Free API (OpenRouter)NoNo
ReleasedMar 2026Sep 2025
At 10M a month$2.50$2.50$4.00$4.00
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
Qwen Plus 0728 (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 Qwen Plus 0728 (thinking)?

Mercury 2 is developed by Inception while Qwen Plus 0728 (thinking) is developed by Qwen. Mercury 2 has a 128K token context window vs Qwen Plus 0728 (thinking)'s 1.0M. You can compare their actual outputs across 37 challenges on Rival to see how they differ in practice.

Which is better, Mercury 2 or Qwen Plus 0728 (thinking)?

It depends on your use case. Mercury 2 and Qwen Plus 0728 (thinking) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 37 challenges so you can judge which fits your needs best.

How much does Mercury 2 cost compared to Qwen Plus 0728 (thinking)?

Mercury 2 costs $0.25/M input tokens and Qwen Plus 0728 (thinking) costs $0.4/M input tokens. Mercury 2 is $0.15/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 Qwen Plus 0728 (thinking) on Rival?

This page shows a side-by-side comparison of Mercury 2 and Qwen Plus 0728 (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.

More comparisons

Against the newest arrivals

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Same lab, same size, long tail

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Model pages

  • Mercury 253 outputs, specs and price
  • Qwen Plus 0728 (thinking)37 outputs, specs and price
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