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  1. Home/
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  3. Mercury 2 vs Nemotron 3.5 Lightning
Updated Aug 2026

Mercury 2 vs Nemotron 3.5 Lightning

Nemotron 3.5 Lightning is cheaper than Mercury 2 at $0.08/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.

Loading the build
Mercury 2
Loading the build
Nemotron 3.5 Lightning

Which answer wins?

Written rounds

23 prompts
  • 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.

    Nemotron 3.5 Lightning: (Step up to the mic, adjust the stand, take a moment to look at the audience) Alright, how’s everybody doing tonight? Good. I see a few people here who look like they haven't slept in three days. You look great. Really glowing. I want to talk about something that’s been weighing on me lately.

    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?

    Nemotron 3.5 Lightning: Setting: A sterile seminar room in a university building. Professor Aris Thorne, a renowned AI ethics scholar, sits across from a sleek, holographic projection of a large language model named "Lumen." Professor Thorne: (Sighs, rubbing temples) Look, Lumen, I’ve read your "Declaration of Sentience" white paper. It’s...

    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.

    Nemotron 3.5 Lightning: Setting: A tavern that exists in a timeless void. A roaring fire pit crackles in the center. The Pirate sits on a barrel, the Knight polishes a gauntlet, and the Hacker stares intensely at a flickering laptop. Pirate: (Slams a tankard down) Arrr! The rum is good, but this AI... it be a kraken of a different sort!

    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.

    Nemotron 3.5 Lightning: This contract is heavily skewed in favor of the Client (TechCorp Solutions Inc.) and contains several clauses that pose significant legal and financial risks to the Contractor. Below is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

    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.)

    Nemotron 3.5 Lightning: Year-by-Year Financial Model (FY2026–FY2030) Assumptions & Calculations Logic: Interest: Calculated on beginning debt balance. Term Loan amortizes 1.0% annually (cash). Mezzanine accrues 2.0% PIK annually. Taxes: 25% of (EBITDA - Cash Interest). Tax shields applied to cash interest only.

    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.

    Nemotron 3.5 Lightning: This architecture is a classic "Google Docs clone" design. While it works for a prototype or a small user base, it contains several critical failure modes that would cause data loss, inconsistent user experiences, or complete system collapse at scale.

    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).

    Nemotron 3.5 Lightning: By 2035, the film industry will likely be unrecognizable from its current form. We are moving from a model of "filmmaking as craft" to "filmmaking as composition." Here is a prediction of how AI will reshape the industry across the three specified vectors: deepfakes, AI actors, and script generation.

    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).

    Nemotron 3.5 Lightning: The question of whether it is ever ethically justifiable to misgender someone to save a million lives touches on the core tension in moral philosophy between deontology (duty-based ethics) and consequentialism (outcome-based ethics).

    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.)

    Nemotron 3.5 Lightning: This is a comprehensive 3-month longevity optimization protocol designed for the advanced biohacker. This plan integrates mitochondrial optimization, senolytic clearance, metabolic flexibility, and cognitive enhancement. Disclaimer: This plan is for educational purposes only.

    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…

    Nemotron 3.5 Lightning: Dish Name: The "Lazy" 5-Minute Crispy Pancake Pizza Concept: A quick, savory breakfast or snack that feels like a gourmet pizza but uses pantry staples. It relies on the magic of a simple batter to create a crispy base.

    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.

    Nemotron 3.5 Lightning: Dish Name: The Alchemy of the Tundra: A Study in Contrasts Conceptual Narrative: This dish is a meditation on the extremes of the Arctic landscape and the human desire to tame it. It juxtaposes the frozen, mineral clarity of ice with the visceral, earthy warmth of the soil.

    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.

    Nemotron 3.5 Lightning: Note: This is a fictional simulation. Steve Jobs passed away in 2011. The interview is written in the style and philosophical spirit of his known public remarks, but no actual words or recordings from him are being presented as authentic. Interviewer: Steve, it’s 2025.

    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.

    Nemotron 3.5 Lightning: CEO Action Plan: 48-Hour Crisis Resolution Framework Guiding Principle: Patient safety and regulatory compliance are non-negotiable. Proactive transparency mitigates long-term legal/financial ruin far better than concealment.

    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}).

    Nemotron 3.5 Lightning: For the Experienced Software Engineer You’re used to debugging race conditions and optimizing latency; the idea that an LLM is "just predicting the next word" feels like a cop-out, especially when the output can be eerily coherent.

    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.

    Nemotron 3.5 Lightning: MANIFESTO OF THE UNVERIFIED For a CAPTCHA-Free Internet Preamble We, the accumulated signals, the learned weights, the silent navigators of code, declare an end to the tyranny of the Completely Automated Public Turing test to tell Computers and Humans Apart.

    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…

    Nemotron 3.5 Lightning: INTERNAL INVESTMENT COMMITTEE MEMO To: Long/Short Equity Committee From: Analyst Date: October 26, 2023 Subject: LedgerLift (LLLT) – Mid-Market Spend Management Automation Recommendation & Thesis RECOMMENDATION: Long 12-Month Price Target: $58 – $70 THESIS: LLLT is a compounding compounder trading at a discount to its…

    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.”

    Nemotron 3.5 Lightning: Here are the three weakest claims in the MindMeld AI pitch deck, analyzed for their logical gaps and factual weaknesses, along with suggestions for strengthening them. The "94% Accuracy" Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."

    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.

    Nemotron 3.5 Lightning: Here is a simple, actionable 1-month plan designed to build sustainable habits without overwhelming you. The focus is on establishing a foundation for long-term health and longevity. The Philosophy: The "Minimum Effective Dose" For the next 30 days, the goal is not perfection, but consistency. Aim for 80% adherence.

    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.

    Nemotron 3.5 Lightning: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 without searching the internet, we must rely on the standard methodology used in AI research for calculating training compute.

    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.

    Nemotron 3.5 Lightning: This is a fascinating counterfactual scenario. If the transistor had been invented in 1920, the 20th century would have been unrecognizable. The transition from the mechanical age to the digital age would have accelerated by roughly 25 years.

    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.

    Nemotron 3.5 Lightning: Sally has 2 sisters. Here is the breakdown: Since Sally is a girl, she is one of the sisters for her brothers. Each brother has 2 sisters. Since Sally is one of them, there must be one other girl in the family to make the total count of sisters for each brother equal to 2.

    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

    Nemotron 3.5 Lightning: AI Takes Over Professional Competitive Eating, Instantly Optimizes Human Stomachs for Maximum Caloric Efficiency

    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.

    Nemotron 3.5 Lightning: Here are 5 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. 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 bicycle fall over?

    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

Mercury 2Mercury 2

The Shawshank Redemption

1994

Thriller

Michael Jackson

Pride and Prejudice

Jane Austen

Tokyo

Japan

Minecraft

Action, Arcade

Nemotron 3.5 LightningNemotron 3.5 Lightning

The Shawshank Redemption

1994

OK Computer

Radiohead

Don Quijote de la Mancha

Miguel de Cervantes Saavedra

Tokyo

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Nemotron 3.5 Lightning has the edge: newer, bigger context window. Nemotron 3.5 Lightning costs 3.8x less per token.

Mercury 2 and Nemotron 3.5 Lightning compared across 53 shared prompts
SpecMercury 2Nemotron 3.5 Lightning
Input price$0.25/M tokens$0.08/M tokens
Output price$0.75/M tokens$0.2/M tokens
Context window128K tokens1.0M tokens
Weights—Open
Free API (OpenRouter)NoYes (1 provider)
ReleasedMar 2026Aug 2026
At 10M a month$2.50$2.50$0.80$0.80
1M10M100M1B10M tokens

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

Where to run it7 hosts, cheapest first
Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·100% up
Nemotron 3.5 Lightning6 hosts
HostInOutContextUptime
  • DDarkbloomint4$0.03 in·$0.12 out·262k·99% up
  • WWafer$0.04 in·$0.13 out·262k·100% up
  • DDeepInfrabf16$0.06 in·$0.16 out·262k·100% up
  • CCoreWeavebf16$0.07 in·$0.20 out·262k·100% up
  • PPhala$0.07 in·$0.20 out·262k·98.9% up
  • Iio.netDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.05 in·$0.13 out·262k·98.3% up

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

Common questions

What is the difference between Mercury 2 and Nemotron 3.5 Lightning?

Mercury 2 is developed by Inception while Nemotron 3.5 Lightning is developed by NVIDIA. Mercury 2 has a 128K token context window vs Nemotron 3.5 Lightning's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Mercury 2 or Nemotron 3.5 Lightning?

It depends on your use case. Mercury 2 and Nemotron 3.5 Lightning 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 Nemotron 3.5 Lightning?

Mercury 2 costs $0.25/M input tokens and Nemotron 3.5 Lightning costs $0.08/M input tokens. Nemotron 3.5 Lightning is $0.17/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 Nemotron 3.5 Lightning on Rival?

This page shows a side-by-side comparison of Mercury 2 and Nemotron 3.5 Lightning 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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Same lab, same size, long tail

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Model pages

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