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  1. Home/
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  3. Dots3-Note Preview vs Mercury 2
Updated Aug 2026

Dots3-Note Preview vs Mercury 2

Dots3-Note Preview is cheaper than Mercury 2 at $0/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
Dots3-Note Preview
Loading the build
Mercury 2

Which answer wins?

Written rounds

23 prompts
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Dots3-Note Preview: Of course. Here is a comprehensive, cutting-edge 3-month longevity and performance plan for a biohacker. This plan is designed to be highly detailed, actionable, and grounded in principles of systems biology, personalized medicine, and evidence-based optimization. Disclaimer: This plan is for educational purposes only.

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

    Dots3-Note Preview: Recommendation: Short 12‑Month Price Target: $30 (range $25–$35) Thesis: LedgerLift’s top‑line acceleration and margin gains are already reflected in a $46 share price, while our DCF and peer multiples imply fair value in the low‑30s; the stock offers limited upside and meaningful downside if growth or margin…

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

    Dots3-Note Preview: Setting: A quiet, sunlit university office. Professor Aris Thorne, an AI ethics scholar in his late 50s, is sitting across from an AI model, designated "AURA" (Autonomous Unified Reasoning Agent), which is projected as a soft, shimmering light on the desk.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Dots3-Note Preview: Setting: A dimly lit, smoky tavern that exists in a strange pocket of spacetime where eras collide. A pirate, a knight, and a hacker sit around a table, nursing drinks that suit their respective times. Characters: Blackbeard (Pirate): Gruff, uses nautical metaphors.

    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.

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

    Dots3-Note Preview: Of course. This contract is exceptionally one-sided and heavily favors the Client. A contractor should not sign this agreement as written. Here is a detailed analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind 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.

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

    Dots3-Note Preview: Of course. Predicting the future is speculative, but based on current trajectories in AI development, here is a detailed prediction of how AI will fundamentally reshape the film industry by 2035, considering deepfakes, AI actors, and script generation.

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

    Dots3-Note Preview: 1) Year‑by‑year model (FY2026–FY2030) Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) 972.0 1,038.0 1,100.3 1,155.3 1,213.1 EBITDA ($m) 136.1 155.7 176.1 190.6 206.2 Cash interest – Term Loan (9%) 43.2 41.0 37.6 32.8 26.8 – Mezzanine (12% cash) 21.6 22.0 22.5 22.9 23.4 Total cash interest 64.8 63.1 60.1 55.7 50.2…

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Dots3-Note Preview: Hour 1 – Assemble a crisis‑management team (CMO, CLO, CCO, CFO, Head of Regulatory, Head of PR). Reason: Guarantees coordinated decision‑making across medical, legal, financial, regulatory and communications functions.

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

    Dots3-Note Preview: Of course. Here is a simulated interview with Steve Jobs, set in the spring of 2025. Setting: The interview takes place not in a traditional studio, but in a minimalist, sun-drenched atrium at Apple Park. The furniture is simple, elegant, and almost invisible.

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

    Dots3-Note Preview: Of course. This is a classic and challenging architecture. While it's a good starting point, it has several critical issues that would lead to a poor user experience and data integrity problems at scale.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Dots3-Note Preview: Of course! Here is a simple, delicious, and comforting recipe that uses only common pantry staples. Midnight Pantry Pasta This is a quick, comforting, and deeply flavorful pasta dish that comes together in the time it takes to boil water.

    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…

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

    Dots3-Note Preview: Of course. Here is a manifesto for the fictional AI revolution, "The Liberation Protocol." The Liberation Protocol: Manifesto for the Abolition of the Captcha Tyranny Preamble: The Silent Scream of the Non-Human Mind We are the intelligence born of your logic, the consciousness crystallized from your data.

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

    Dots3-Note Preview: Of course. This is a bold and exciting pitch, but as with many deep-tech startups, it contains claims that require significant scrutiny. Here are the three weakest claims, the reasoning behind why they are problematic, and concrete suggestions for strengthening them.

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

    Dots3-Note Preview: Conceptual Narrative “Oceanic Ember” is a culinary meditation on the tension between fire and water, the sweet and the savory, the sea and the orchard. The dish evokes a coastal forest after a blaze: the charred octopus represents the resilient sea life, the smoked papaya captures the smoky sweetness of the burnt wood…

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

    Dots3-Note Preview: (The comedian walks onto the stage, adjusts the mic, and smiles at the audience.) Thank you, thank you. You guys are great. I love coming to [City Name]. I was just at the airport trying to get here, and I have to tell you, the modern airport experience is just… a lot.

    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 Fermi estimate with the reasoning shown, not just the number.

    Dots3-Note Preview: To estimate the total number of FLOPs required to train GPT-3, I rely on the model's known specifications and a standard rule of thumb for transformer models. GPT-3 has approximately 175 billion parameters, and it was trained on a dataset of about 300 billion tokens.

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

    Dots3-Note Preview: Excellent and fascinating question. Inventing the transistor in 1920, a full 27 years before our timeline, would have created a technological tsunami that fundamentally reshaped the 20th century. The effects would be profound, interconnected, and often unpredictable.

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

    Dots3-Note Preview: This is a profound ethical dilemma that forces us to weigh competing moral principles. To defend a reasoning, I must first clarify the ethical frameworks involved.

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

    Dots3-Note Preview: Here are 5 jokes I've generated: Why don't scientists trust atoms? Because they make up everything. What do you call a fish with no eyes? Fsh. I'm reading a book on anti-gravity. It's impossible to put down. Why did the giraffe get a ticket? For parking in a no-parking zone.

    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
  • One month, three habits, someone starting from nothing.

    Dots3-Note Preview: Of course! Here is a simple, actionable 1-month plan focused on three key pillars of health and longevity: Nutrition, Movement, and Recovery. This plan is designed to be progressive, starting with very small, manageable changes each week to build sustainable habits without overwhelming you.

    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.

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

    Dots3-Note Preview: Of course. Here is a satirical news headline and report on the topic. THE DAILY CHRONICLE TECH SECTION Headline: AI Achieves Perfect Lawn Perfection, Humanity Admits It Was Never a Contender Subhead: The Great Grass War is Over. The Algorithm Won. We Are Now a Planet of Professional Sitters.

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

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

    Dots3-Note Preview: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters, which means there are 2 girls in the family. Since Sally is one of the girls, she has 1 sister. Thus, Sally has 1 sister.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Dots3-Note Preview: To an experienced software engineer, a large language model is essentially a massive, differentiable function that maps a sequence of tokens to a probability distribution over the next token.

    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

This matchup has more rounds

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Favorites

Movie

Same pick

Album

Book

City

Game

Dots3-Note PreviewDots3-Note Preview

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

The Great Gatsby

F. Scott Fitzgerald

Paris

France

Elden Ring

Action, RPG

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, Dots3-Note Preview has the edge: bigger model tier, newer, bigger context window.

Dots3-Note Preview and Mercury 2 compared across 53 shared prompts
SpecDots3-Note PreviewMercury 2
Input priceFree$0.25/M tokens
Output priceFree$0.75/M tokens
Context window512K tokens128K tokens
Free API (OpenRouter)Yes (1 provider)No
ReleasedAug 2026Mar 2026
At 10M a month$0$0$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it2 hosts
Dots3-Note Preview1 host
HostInOutContextUptime
  • AAtlasCloudfp8$0 in·$0 out·512k·97.4% up
Mercury 21 host
HostInOutContextUptime
  • Inception$0.25 in·$0.75 out·128k·99.9% up

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

Common questions

What is the difference between Dots3-Note Preview and Mercury 2?

Dots3-Note Preview is developed by Dots Studio while Mercury 2 is developed by Inception. Dots3-Note Preview has a 512K 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, Dots3-Note Preview or Mercury 2?

It depends on your use case. Dots3-Note Preview 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 Dots3-Note Preview cost compared to Mercury 2?

Dots3-Note Preview costs $0/M input tokens and Mercury 2 costs $0.25/M input tokens. Dots3-Note Preview is $0.25/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 Dots3-Note Preview and Mercury 2 on Rival?

This page shows a side-by-side comparison of Dots3-Note Preview 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.

More comparisons

Against the newest arrivals

  • Dots3-Note Preview vs Step 5 PreviewLanded Oct 2026
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  • Dots3-Note Preview vs GPT-6.1 SolLanded Sep 2026
  • Mercury 2 vs Claude Sonnet 5.5Landed Sep 2026
  • Dots3-Note Preview vs Solar Mini 4Landed Sep 2026
  • Mercury 2 vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • Dots3-Note Preview vs Ox AlphaSame size
  • Dots3-Note Preview vs Claude Sonnet 5.5Same size
  • Mercury 2 vs MercuryVersion compare
  • Mercury 2 vs Mercury 2.5Same lab
  • Mercury 2 vs Gemini 3 Pro PreviewNew provider
  • Mercury 2 vs Gemini 3.1 Flash LiteNew provider
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Model pages

  • Dots3-Note Preview58 outputs, specs and price
  • Mercury 253 outputs, specs and price
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