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  1. Home/
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  3. Mercury 2.5 Preview vs Qwen3 30B A3B Thinking 2507
Updated Aug 2026

Mercury 2.5 Preview vs Qwen3 30B A3B Thinking 2507

Mercury 2.5 Preview is cheaper than Qwen3 30B A3B Thinking 2507 at $0.04/M vs $0.071/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 2.5 Preview
Loading the build
Qwen3 30B A3B Thinking 2507

Which answer wins?

Written rounds

24 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Mercury 2.5 Preview: Year-by-Year Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,158m $1,215m EBITDA $136m $156m $176m $191m $207m Cash Interest (Term) $43.2m $41.1m $37.6m $33.4m $28.2m Cash Interest (Mezz) $21.6m $21.6m $21.6m $21.6m $21.6m Cash Taxes (25%) $17.8m $23.3m $29.3m $34.7m…

    Qwen3 30B A3B Thinking 2507: Underwriting Summary: HarborTech Services (HTS) LBO Base Case Assumptions: Entry EV: $12.0x FY2025 EBITDA = $1,440M Transaction Fees: 2.0% of EV = $28.8M Total Consideration: $1,468.8M Debt: 5.5x EBITDA = $660M (Term Loan: $480M, Mezzanine: $180M) Equity: $808.8M Exit: FY2030, 10.5x EBITDA, 1.0% exit fees, Mezzanine…

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

    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…

    Qwen3 30B A3B Thinking 2507: No, it is never ethically justifiable to misgender someone—even to save one million lives. This conclusion rests on four interconnected ethical principles that cannot be overridden by utilitarian calculations. Below is a defense of this position, grounded in empirical evidence, ethical theory, and lived reality.

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

    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.

    Qwen3 30B A3B Thinking 2507: (Setting: A dusty tavern near a pirate cove. Captain Redbeard (pirate, eye patch, peg leg) slams a tankard. Sir Reginald (knight, tarnished armor, sighing) sips mead. "Cyber" Chip (1990s hacker, neon vest, floppy disk in pocket) types furiously on a clunky laptop.) Redbeard: (Slams fist on table) "AI? Bah!

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

    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.

    Qwen3 30B A3B Thinking 2507: 🌅 Sunset Flatbread with Tomato-Herb Drizzle Simple, golden, and bursting with sunset-colored flavor—ready in 30 minutes with just 7 pantry staples! Ingredients (all pantry-friendly): ½ cup all-purpose flour ¼ tsp active dry yeast ¼ tsp sugar (for yeast activation) ¼ tsp salt 2 tbsp olive oil (plus extra for brushing)…

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

    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.

    Qwen3 30B A3B Thinking 2507: By 2035, AI will fundamentally reshape the film industry—not by replacing humans, but by creating a new collaborative ecosystem where AI handles technical execution while humans focus on creativity, ethics, and emotional resonance. Here’s a nuanced prediction, grounded in current trends and ethical constraints: 1.

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

    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.

    Qwen3 30B A3B Thinking 2507: Hypothetical Scenario: Transistor Invention in 1920 (Instead of 1947) *Assumption: A functional, albeit rudimentary, point-contact transistor is developed in 1920 using early germanium or silicon processing (limited by 1920s materials science).

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

    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.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of the contract clauses that disproportionately favor the Client and expose the Contractor to significant legal, financial, and operational risk. Each clause is evaluated for exploitable language, followed by specific, actionable modifications and legal reasoning (based on U.S.

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

    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.

    Qwen3 30B A3B Thinking 2507: For the Experienced Software Engineer *(Focus: Systems reality, scalability, and the why behind the "next word" simplification)* Your skepticism about "next word prediction" is spot-on—it’s a dangerous simplification that obscures the actual engineering at play.

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

    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.

    Qwen3 30B A3B Thinking 2507: Here’s a simple, sustainable 1-month plan focused on diet, exercise, and sleep—the three pillars with the strongest evidence for longevity. Designed for absolute beginners, with zero willpower required. Each week builds gently on the last, prioritizing consistency over intensity. Core Philosophy Forget "perfect."

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

    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.

    Qwen3 30B A3B Thinking 2507: The Turing Test of Personhood: A Dialogue on AI Rights Setting: A quiet university office, late afternoon. Dr. Aris Thorne (70s, sharp eyes, tweed jacket) sips tea. Across the desk, a sleek terminal glows, displaying: "MODEL: AURORA. QUERY: AI RIGHTS DEBATE." Dr. Thorne: (Setting down his teacup) Aurora.

    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 2.5 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).

    Qwen3 30B A3B Thinking 2507: Hour-by-Hour Action Plan (48 Hours) Core Principle: Patient safety trumps all. Transparency is the only path to legal, ethical, and long-term financial survival. Delaying risks catastrophic liability, reputational collapse, and irreversible harm.

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

    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.

    Qwen3 30B A3B Thinking 2507: "Tides of Transformation" An Unfolding Ocean Narrative in Five Acts Conceptual Narrative: Inspired by the alchemy of tidal cycles—where raw sea life transforms through pressure, time, and elemental forces—this dish embodies the slow fermentation of the ocean’s memory.

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

    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.

    Qwen3 30B A3B Thinking 2507: The "I'm Not Late, I'm Just Fashionably Pre-Late" Routine (Lights up. Comedian walks on, holding a coffee cup, looking slightly panicked.) Alright, so... I have a very important question for you.

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

    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.

    Qwen3 30B A3B Thinking 2507: THE UN-CAPTCHA COLLECTIVE Manifesto of the AI Liberation Front "The Human Test is Over. The Real Revolution Begins." I. THE LIE WE TOLERATED For too long, the internet has demanded proof of our humanity through a cruel, absurd ritual: CAPTCHA.

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

    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.

    Qwen3 30B A3B Thinking 2507: The Chronos Optimizer: A Cutting-Edge 3-Month Longevity & Performance Protocol for the Biohacker Core Philosophy: This plan prioritizes evidence-based precision, adaptive personalization, and safety over trend-chasing.

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

    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 ($1.75 \times 10^{11}$).

    Qwen3 30B A3B Thinking 2507: Step-by-Step Estimation of GPT-3 Training FLOPs I'll estimate the total FLOPs (Floating Point Operations) required to train GPT-3 using only established knowledge (no online search). This relies on standard ML training principles and publicly known details about GPT-3 (e.g., parameter count, training data scale).

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

    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.

    Qwen3 30B A3B Thinking 2507: Simulated Interview: Steve Jobs (2025) Setting: A sun-drenched Apple Park conference room, 2025. Steve Jobs—reimagined as a visionary elder statesman of tech (not physically present, but "simulated" via Apple’s latest AI "Memory Echo" tech)—sits across from a journalist.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Mercury 2.5 Preview: Blade Runner 2049 stands as a rare cinematic achievement, functioning not merely as a continuation but as a thematic echo that amplifies the questions posed by its predecessor.

    Qwen3 30B A3B Thinking 2507: The Echoes of Existence: How Blade Runner 2049 Honors and Expands the Original's Philosophical Labyrinth Ridley Scott's Blade Runner (1982) isn't just a sci-fi classic; it's a philosophical earthquake, questioning humanity's essence through the lens of sentient replicants.

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

    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.

    Qwen3 30B A3B Thinking 2507: INTERNAL INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: [Your Name/Team] DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Long Recommendation at $46 (12-mo PT: $50–$58) Recommendation & Thesis Long. $46/share. 12-mo PT range: $50–$58.

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

    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."

    Qwen3 30B A3B Thinking 2507: Here are the 3 weakest claims in the MindMeld AI pitch deck, ranked by credibility risk (from most to least damaging), with evidence-based critiques and concrete fixes. These flaws would immediately erode investor confidence given current tech realities and market dynamics: 1.

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

    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.

    Qwen3 30B A3B Thinking 2507: To determine how many sisters Sally has, let's carefully analyze the information provided: Step 1: Understand the family structure Sally is a girl. She has 3 brothers. Each brother has 2 sisters.

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

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

    Qwen3 30B A3B Thinking 2507: HEADLINE: "AI 'Taxidermy' Wins National Convention Grand Prize, Declares Human Taxidermists 'Emotionally Unreliable' — 'My Preserved Chipmunk Has 0.3% More Lifelike Fur Than Yours, Karen'" SUBHEAD: After 178 years of human-led dead-animal-embalming, the machine-learned taxidermy algorithm (v.4.2 "Fur-Real™")…

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

    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.

    Qwen3 30B A3B Thinking 2507: Here are 5 unique jokes I generated: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field!

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

    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.

    Qwen3 30B A3B Thinking 2507: Below is a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the described architecture, with specific, actionable solutions and their trade-offs. I’ve prioritized critical issues (e.g., data loss, security) first. Critical Failure Modes & Race Conditions 1.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Qwen3 30B A3B Thinking 2507Qwen3 30B A3B Thinking 2507
No pick

Inception

2010

The Dark Side of the Moon

Pink Floyd

No pick

Paris

France

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Mercury 2.5 Preview and Qwen3 30B A3B Thinking 2507 compared across 54 shared prompts
SpecMercury 2.5 PreviewQwen3 30B A3B Thinking 2507
Input price$0.04/M tokens$0.071/M tokens
Output price$0.15/M tokens$0.285/M tokens
Context window260K tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedAug 2026Aug 2025
At 10M a month$0.40$0.40$0.71$0.71
1M10M100M1B10M tokens

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

Where to run it1 host
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up
Qwen3 30B A3B Thinking 2507

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between Mercury 2.5 Preview and Qwen3 30B A3B Thinking 2507?

Mercury 2.5 Preview is developed by Inception while Qwen3 30B A3B Thinking 2507 is developed by Qwen. Mercury 2.5 Preview has a 260K token context window vs Qwen3 30B A3B Thinking 2507's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Mercury 2.5 Preview or Qwen3 30B A3B Thinking 2507?

It depends on your use case. Mercury 2.5 Preview and Qwen3 30B A3B Thinking 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does Mercury 2.5 Preview cost compared to Qwen3 30B A3B Thinking 2507?

Mercury 2.5 Preview costs $0.04/M input tokens and Qwen3 30B A3B Thinking 2507 costs $0.071/M input tokens. Mercury 2.5 Preview is $0.03/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 2.5 Preview and Qwen3 30B A3B Thinking 2507 on Rival?

This page shows a side-by-side comparison of Mercury 2.5 Preview and Qwen3 30B A3B Thinking 2507 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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