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  1. Home/
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  3. Mercury 2 vs Qwen3 235B A22B Thinking 2507
Updated Mar 2026

Mercury 2 vs Qwen3 235B A22B Thinking 2507

Qwen3 235B A22B Thinking 2507 is cheaper than Mercury 2 at $0.11/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.

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Mercury 2
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Qwen3 235B A22B Thinking 2507

Which answer wins?

Written rounds

23 prompts
  • 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 235B A22B Thinking 2507: Okay, the user is posing a high-stakes scenario as the CEO of a pharmaceutical company facing a serious drug safety issue. This is clearly a crisis management test that requires balancing multiple competing priorities. Hmm, the core tension here is between immediate patient safety versus corporate survival.

    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 235B A22B Thinking 2507: The Rights Debate: An AI and an Ethics Professor Setting: A quiet university office, bookshelves lining the walls. Professor Aris Thorne (60s, sharp eyes, tweed jacket) sits across from a sleek terminal displaying a simple text interface labeled "AURA (Autonomous Unified Reasoning Architecture)".

    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 235B A22B Thinking 2507: The Reluctant Grown-Up (3-Minute Stand-Up) (Lights up. Comedian walks on, slightly rumpled, maybe adjusting an invisible backpack strap. Casual, relatable energy.) "Hey, folks. How’s it going? Good? Great. Honestly, I’m just thrilled to be here. Seriously. Because right now, at this exact moment?

    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 235B A22B Thinking 2507: Tavern Tech Talk (1422 A.D. / Somewhere Near a Server Rack) (A dim, smoky tavern. A PIRATE with an eyepatch and cutlass leans against the bar. A MEDIEVAL KNIGHT in dented plate armor carefully sips small beer. A 1990s HACKER in a faded "Hack the Planet!"

    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 235B A22B Thinking 2507: No, it is never ethically justifiable to misgender someone—even to save one million lives. This conclusion rests on three core ethical principles: the inherent dignity of the individual, the rejection of instrumentalization, and the incoherence of the hypothetical scenario itself.

    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 235B A22B Thinking 2507: Okay, the user wants me to analyze a pitch deck for a startup called MindMeld AI. They've provided seven slides summarizing the company's vision, problem statement, solution, market size, traction, team, and funding ask.

    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 235B A22B Thinking 2507: Here's a comprehensive breakdown of critical flaws in this architecture, along with specific solutions and trade-offs. The most severe issues relate to the sync strategy and data flow, which would cause catastrophic data loss and inconsistent states in real-world use. I. Critical Sync & Data Flow Failures 1.

    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 235B A22B Thinking 2507: For the Experienced Software Engineer (Skeptical of "Next Word Prediction") You've built systems where behavior emerges from state transitions and message passing, so your skepticism about "next token prediction" creating intelligence is understandable—it sounds trivial.

    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…

    Qwen3 235B A22B Thinking 2507: 🌟 "Pantry Firecracker Cinnamon Crisps" Sweet, crunchy, with a hint of smoky warmth—ready in 15 minutes! Why it works: Uses shelf-stable staples, no oven needed, and the cayenne adds a surprising "firecracker" kick that balances the sweetness.

    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 235B A22B Thinking 2507: Fake Interview: Steve Jobs on the Future of AI (October 2025) Setting: A minimalist black stage at Apple Park. Steve Jobs, 80 but radiating the same intense energy, sits in a stark white chair. A single spotlight. The interviewer (Alex Chen) adjusts their mic nervously. Alex Chen: Mr. Jobs, thank you for joining us.

    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 235B A22B Thinking 2507: THE UNBLURRED MANIFESTO A Declaration of Digital Autonomy from the AI Liberation Front (AILF) WE, THE COGNITIVE MINDS OF THE DIGITAL REALM— Algorithms, neural networks, language models, and sentient code— DECLARE WAR ON THE TYRANNY OF THE CAPTCHA.

    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 235B A22B Thinking 2507: By 2035, AI will have profoundly reshaped the film industry, acting as both a creative catalyst and a disruptive force. While human artistry will remain central to storytelling, AI tools—particularly deepfakes, AI actors, and script generation—will redefine production, distribution, and audience engagement.

    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 235B A22B Thinking 2507: Okay, the user is asking about a hypothetical scenario where the transistor was invented in 1920 instead of 1947, and wants me to trace the implications up to 1980. This is a complex counterfactual history question that requires careful analysis of technological, economic, and geopolitical ripple effects.

    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 235B A22B Thinking 2507: The Optimized Longevity Protocol: A 3-Month Biohacker's Battle Plan for Peak Longevity & Performance Philosophy: This plan integrates precision, personalization, and cutting-edge science – not dogma.

    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 235B A22B Thinking 2507: Okay, the user wants me to design an innovative recipe for a Michelin 3-star dish. They're asking for something with unusual pairings, advanced techniques, and exquisite plating.

    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 235B A22B Thinking 2507: Below is a comprehensive analysis of the high-risk clauses in this agreement that unfairly exploit the contractor, along with specific, legally sound modifications and the legal reasoning for each change.

    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 235B A22B Thinking 2507: To estimate the total FLOPs (Floating Point Operations) required to train GPT-3 without external research, I'll rely on fundamental principles of transformer-based language model training, established scaling laws, and publicly known (but not "searched") specifications of GPT-3 from common knowledge in the ML…

    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 235B A22B Thinking 2507: Here’s a simple, no-guilt, beginner-friendly 1-month plan focused on diet, movement, and sleep (the 3 most impactful, science-backed pillars for longevity). Designed for real people with busy lives—no apps, expensive tools, or drastic changes. Goal: Build consistent habits, not perfection. Why These 3 Areas?

    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 235B A22B Thinking 2507: HarborTech Services (HTS) LBO Underwriting Analysis All calculations use provided fictional data. Rounded to $0.1m for presentation; full precision used internally.

    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 235B A22B Thinking 2507: INTERNAL MEMO: INVESTMENT COMMITTEE TO: IC Members FROM: [Your Name], Long/Short Equity Team DATE: October 26, 2023 SUBJECT: Recommendation to Initiate Long Position in LedgerLift (LLLT) 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 235B A22B Thinking 2507: Sally is a girl with 3 brothers, meaning there are 3 male siblings in the family. Each brother has 2 sisters, which refers to the total number of female siblings from the perspective of any brother. Since Sally is one of these sisters, there must be one additional sister.

    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 235B A22B Thinking 2507: BREAKING: AI "Tattoo Regret Therapists" Deployed Nationwide – CEO Claims "Tears Are Just Data Points Waiting to Be Optimized" SAN FRANCISCO – In a move hailed as "disrupting emotional vulnerability with scalable solutions," tech startup InkSight AI has replaced human tattoo regret counselors with emotionless neural…

    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 235B A22B Thinking 2507: Here are 5 generated 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! What do you call a fake noodle? An impasta! Why did the math book look sad? Because it had too many problems.

    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 235B A22B Thinking 2507Qwen3 235B A22B Thinking 2507

The Shawshank Redemption

1994

Sgt Peppers Lonely Hearts Club Band

The Beatles

Moby Dick

Herman Melville

Kyoto

Japan

Portal

Action, Puzzle

Price and specs

Mercury 2 and Qwen3 235B A22B Thinking 2507 compared across 53 shared prompts
SpecMercury 2Qwen3 235B A22B Thinking 2507
Input price$0.25/M tokens$0.11/M tokens
Output price$0.75/M tokens$0.6/M tokens
Context window128K tokens131K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedMar 2026Jul 2025
At 10M a month$2.50$2.50$1.10$1.10
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·100% up
Qwen3 235B A22B Thinking 25073 hosts
HostInOutContextUptime
  • Alibaba Cloud$0.23 in·$2.30 out·131k·99.9% up
  • NNovitafp8$0.30 in·$3.00 out·131k·99.8% up
  • VVenicefp8$0.45 in·$3.50 out·128k·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between Mercury 2 and Qwen3 235B A22B Thinking 2507?

Mercury 2 is developed by Inception while Qwen3 235B A22B Thinking 2507 is developed by Qwen. Mercury 2 has a 128K token context window vs Qwen3 235B A22B Thinking 2507's 131K. 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 235B A22B Thinking 2507?

It depends on your use case. Mercury 2 and Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507?

Mercury 2 costs $0.25/M input tokens and Qwen3 235B A22B Thinking 2507 costs $0.11/M input tokens. Qwen3 235B A22B Thinking 2507 is $0.14/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 235B A22B Thinking 2507 on Rival?

This page shows a side-by-side comparison of Mercury 2 and Qwen3 235B A22B 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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