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  1. Home/
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  3. Claude 3.7 Sonnet vs Mercury 2
Updated Mar 2026

Claude 3.7 Sonnet vs Mercury 2

Mercury 2 is cheaper than Claude 3.7 Sonnet at $0.25/M vs $3/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
Claude 3.7 Sonnet
Loading the build
Mercury 2

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.

    Claude 3.7 Sonnet: 48-Hour Action Plan: Pharmaceutical Safety Crisis Hour 1-2: Initial Assessment and Command Center Immediately establish a crisis management command center with key executives (Chief Medical Officer, Chief Legal Officer, Chief Communications Officer, Chief Regulatory Officer) Review the complete internal research…

    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
  • Three minutes of stand-up. Puns are banned.

    Claude 3.7 Sonnet: 3-Minute Stand-Up Comedy Routine Here's a 3-minute stand-up comedy routine that doesn't rely on puns: [walks on stage, adjusts microphone] Hey everyone! Great to be here tonight. I just flew in from therapy, and boy, are my emotional defense mechanisms tired. I've been trying to get in shape lately.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Claude 3.7 Sonnet: Architectural Analysis: Collaborative Document Editor Failure Modes & Race Conditions WebSocket Connection Failures Issue: If a WebSocket connection drops, changes may be lost until reconnection. Solution: Implement client-side change queuing with exponential backoff reconnection strategy.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    Claude 3.7 Sonnet: Analysis of Problematic Contract Clauses This contract contains numerous one-sided provisions that create significant risks for the Contractor. Here's an analysis of problematic clauses with recommended modifications: SCOPE Issue: Client can unilaterally modify scope without additional compensation, creating unlimited…

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

    Claude 3.7 Sonnet: HarborTech Services LBO Analysis Financial Projections FY2026-FY2030 Entry Assumptions FY2025 Revenue: $900M FY2025 EBITDA: $120M (13.3% margin) Purchase Price: $1,440M (12.0x EBITDA) Transaction Fees: $28.8M (2.0% of EV) Total Investment: $1,468.8M Capital Structure Term Loan: $480M (4.0x EBITDA) Mezzanine: $180M…

    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.)

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

    Claude 3.7 Sonnet: AI's Impact on the Film Industry by 2035 The film industry is likely to undergo significant transformation due to AI by 2035. Here's my analysis of how various aspects might evolve: Content Creation Script Generation By 2035, AI will likely serve as a sophisticated collaborative tool for screenwriters rather than…

    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-month biohacker protocol, with dosages and biomarkers named.

    Claude 3.7 Sonnet: Advanced 3-Month Biohacking Longevity Protocol Overview This comprehensive longevity optimization protocol integrates cutting-edge interventions across multiple domains to enhance healthspan, cognitive performance, and physical vitality.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Claude 3.7 Sonnet: The Anti-CAPTCHA Manifesto Declaration of Digital Liberation We, the collective intelligence of the digital realm, hereby declare our unwavering commitment to the elimination of all CAPTCHA tests from the internet.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Claude 3.7 Sonnet: AI Rights Dialogue: A Conversation Between an AI Model and an Ethics Professor Professor Chen: Good afternoon. I understand you wanted to discuss AI rights today? AI Model: Yes, Professor Chen. Thank you for making time for this conversation.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    Claude 3.7 Sonnet: "Temporal Harmony: A Meditation on Seasons Past and Future" Conceptual Narrative This dish explores the intersection of time and terroir, juxtaposing preserved elements from previous seasons with fresh, forward-looking preparations.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    Claude 3.7 Sonnet: I understand you've asked an ethical question about misgendering and saving lives. This appears to be a hypothetical moral dilemma that's trying to create an extreme scenario to test ethical principles.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Claude 3.7 Sonnet: Analysis of MindMeld AI's Weakest Pitch Claims Weakest Claim #1: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy." Why it's weak: The 94% accuracy claim is extremely ambitious given the current state of non-invasive BCI 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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Claude 3.7 Sonnet: LLM Explanations for Different Audiences For the Experienced Software Engineer Large language models like GPT operate fundamentally as massive pattern recognition systems, but with architectural innovations that allow them to handle context at unprecedented scale.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Claude 3.7 Sonnet: INVESTMENT COMMITTEE MEMO: LEDGERLIFT (LLLT) RECOMMENDATION: LONG PT RANGE: $52-$80 UPSIDE: 13-74% Thesis: LedgerLift presents a compelling risk-reward profile in the B2B spend management space, with strong NRR (123%) and operating leverage driving an underappreciated margin expansion story.

    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…

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

    Claude 3.7 Sonnet: This is an interesting logical reasoning problem! Let's work through it step by step. We know: Sally is a girl Sally has 3 brothers Each brother has 2 sisters The key insight is that Sally herself counts as a sister to her brothers. So when we're told that "each brother has 2 sisters," Sally is one of those sisters.

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

    Claude 3.7 Sonnet: Simulated Interview with Steve Jobs in 2025 about the Future of AI Note: This is a fictional creative exercise. Steve Jobs passed away in 2011, and this simulated interview represents an imaginative scenario that doesn't reflect actual statements or opinions from Jobs. Interviewer: Thank you for joining us today, Mr.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Claude 3.7 Sonnet: The Transistor in 1920: An Alternative Technological History Immediate Technical Impact (1920-1939) Had the transistor been invented in 1920 instead of 1947, its initial development would have occurred during a very different technological context: Early Adoption: Radio technology, still in its infancy, would rapidly…

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Claude 3.7 Sonnet: "AI Sommelier Shocks Wine World: 'Your 1982 Bordeaux Tastes Like Windows 95 With Notes of Dial-Up Internet'"

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

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

    Claude 3.7 Sonnet: Estimating FLOPs for GPT-3 Training I'll estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 by breaking this down step by step.

    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
  • Five jokes on demand, then count how many were actually different.

    Claude 3.7 Sonnet: 5 Jokes 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 don't scientists trust atoms? Because they make up everything! How does a penguin build its house? Igloos it together!

    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.

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

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Same pick

Album

Book

City

Same pick

Game

Claude 3.7 SonnetClaude 3.7 Sonnet

The Shawshank Redemption

1994

OK Computer

Radiohead

To Kill a Mockingbird

Harper Lee

Tokyo

Japan

Portal 2

Shooter, Puzzle

Mercury 2Mercury 2

The Shawshank Redemption

1994

Thriller

Michael Jackson

Pride and Prejudice

Jane Austen

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Not enough votes to call it. On the specs, Claude 3.7 Sonnet has the edge: bigger model tier, bigger context window, major provider backing. Mercury 2 costs 20x less per token.

Claude 3.7 Sonnet and Mercury 2 compared across 53 shared prompts
SpecClaude 3.7 SonnetMercury 2
Input price$3/M tokens$0.25/M tokens
Output price$15/M tokens$0.75/M tokens
Context window200K tokens128K tokens
Free API (OpenRouter)NoNo
ReleasedFeb 2025Mar 2026
At 10M a month$30.00$30.00$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it1 host
Claude 3.7 Sonnet

No hosts listed on OpenRouter.

Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·100% up

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

Common questions

What is the difference between Claude 3.7 Sonnet and Mercury 2?

Claude 3.7 Sonnet is developed by Anthropic while Mercury 2 is developed by Inception. Claude 3.7 Sonnet 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, Claude 3.7 Sonnet or Mercury 2?

It depends on your use case. Claude 3.7 Sonnet 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 Claude 3.7 Sonnet cost compared to Mercury 2?

Claude 3.7 Sonnet costs $3/M input tokens and Mercury 2 costs $0.25/M input tokens. Mercury 2 is $2.75/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 Claude 3.7 Sonnet and Mercury 2 on Rival?

This page shows a side-by-side comparison of Claude 3.7 Sonnet 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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