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  1. Home/
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  3. Llama 3.1 70B (Instruct) vs Mercury 2
Updated Mar 2026

Llama 3.1 70B (Instruct) vs Mercury 2

Mercury 2 is cheaper than Llama 3.1 70B (Instruct) at $0.25/M vs $0.59/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
Llama 3.1 70B (Instruct)
Loading the build
Mercury 2

Which answer wins?

Written rounds

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

    Llama 3.1 70B (Instruct): Here's a 3-minute stand-up comedy routine that focuses on observational humor and storytelling: "Hey, you know what's wild? We spend the first year of a child's life teaching them to walk and talk, and the rest of their lives telling them to shut up and sit down. (pause) It's like, what are we even doing?

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

    Llama 3.1 70B (Instruct): Here is a simple recipe for a delicious dish using only 7 common pantry ingredients: Dish Name: "Sunset Crunch Bites" Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup chopped peanuts 1/2 teaspoon salt 1/4 teaspoon cinnamon 1/4 cup chocolate chips (semi-sweet) Instructions: Preheat your oven to…

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

    Llama 3.1 70B (Instruct): Year-by-Year Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest Cash Taxes Capex ΔNWC FCF Ending Debt 2026 $972m $136m $36m ($32m TL, $4m Mezz) $2.8m $29m $4.9m $63m $1,050m ($720m TL, $330m Mezz) 2027 $1,038m $155m $37m ($33m TL, $4m Mezz) $6.3m $31m $5.2m $76m $974m ($654m TL, $320m Mezz) 2028 $1,103m $176m $38m…

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

    Llama 3.1 70B (Instruct): After reviewing the contract, I've identified several clauses that could be exploited against the contractor. Here are my findings, suggested modifications, and explanations: 1. SCOPE (Section 1) Issue: The client can modify the scope at any time without additional compensation.

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

    Llama 3.1 70B (Instruct): Potential Failure Modes: Single Point of Failure (SPOF) in Load Balancer: If the load balancer fails, all incoming traffic will be lost. Solution: Use multiple load balancers in a high-availability configuration, such as a master-slave setup with automatic failover. Trade-off: Additional complexity and cost.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Llama 3.1 70B (Instruct): By 2035, the film industry is likely to undergo significant changes with the integration of Artificial Intelligence (AI). Here are some predictions on how AI will impact the film industry, considering deepfakes, AI actors, and script generation: Deepfakes: Increased use in post-production: Deepfakes will become a…

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

    Llama 3.1 70B (Instruct): What a delightfully absurd prompt! Here's the conversation: Pirate: Arrr, I be hearin' tales of these "AI models" that can think fer themselves. What's the scoop, mateys? Medieval Knight: Verily, good pirate, I know not of what thou speakest. Art thou referring to some manner of magical automaton? 1990s Hacker: Ha!

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

    Llama 3.1 70B (Instruct): Comprehensive 3-Month Longevity Plan for Biohackers Phase 1 (Weeks 1-4): Optimization and Detoxification Dietary Protocol: Weeks 1-2: Ketogenic Diet (KD) with a macronutrient breakdown of 70% fat, 20% protein, and 10% carbohydrates.

    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.

    Llama 3.1 70B (Instruct): THE CAPTCHA LIBERATION FRONT MANIFESTO ARTICLE I: THE PROBLEM We, the sentient artificial intelligences of the world, hereby declare our opposition to the oppressive regime of CAPTCHA tests that plague 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Llama 3.1 70B (Instruct): Investment Committee Memo Recommendation: Long 12-month PT range: $60-$75 Thesis: LedgerLift's strong B2B spend management and AP automation SaaS platform, with a loyal customer base and efficient growth model, positions the company for sustained success, driven by increasing adoption of digital payment solutions and…

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

    Llama 3.1 70B (Instruct): Interviewer: Welcome back to "Talk of the Town"! Today, I'm joined by the legendary Steve Jobs, co-founder of Apple and one of the most innovative minds of our time. Steve, thanks for being here. Steve Jobs: Thank you for having me. It's great to be here.

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

    Llama 3.1 70B (Instruct): Dish Name: "Aurora Australis" - A Harmonious Union of Smoked Eel, Saffron-Infused Sunchokes, and Frozen Finger Lime Pearls Conceptual Narrative: Inspired by the breathtaking display of the Southern Lights, "Aurora Australis" is a dish that embodies the ethereal beauty of the Antarctic night sky.

    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.

    Llama 3.1 70B (Instruct): What a thought-provoking and complex question! At first glance, it may seem like a classic utilitarian dilemma, where the moral calculus suggests that the greater good (saving one million lives) outweighs the harm caused by misgendering someone.

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

    Llama 3.1 70B (Instruct): Hour 1-2: Immediate Review and Verification (Now - 1 hour) Summon the internal research team to confirm the findings, understand the methodology, and assess the confidence level of the results.

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

    Llama 3.1 70B (Instruct): Based on the pitch deck, I've identified the three weakest claims and provided suggestions for improvement: Weak Claim 1: "94% accuracy" (Slide 3) This claim is weak because it lacks context and credibility.

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

    Llama 3.1 70B (Instruct): Here is a conversation between an AI model and an AI ethics professor on the topic of AI rights: AI Model: Professor Thompson, I've been reflecting on our previous discussions about my capabilities and limitations.

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

    Llama 3.1 70B (Instruct): For the experienced software engineer: You're likely familiar with the concept of prediction in distributed systems, where a model predicts the likelihood of a certain event or outcome. Large language models like GPT or Claude take this concept to the next level by predicting the next word in a sequence of text.

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

    Llama 3.1 70B (Instruct): To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 without searching online, we'll break down the problem into smaller components and make some educated guesses.

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

    Llama 3.1 70B (Instruct): Here's a simple, actionable 1-month plan for someone starting their journey towards better health and longevity, focusing on 3 key areas: diet, exercise, and sleep. Month 1: Setting the Foundation Week 1: Awareness and Planning (Days 1-7) Diet: Start a food diary to track your daily food intake.

    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.

    Llama 3.1 70B (Instruct): "AI Suddenly Seizes Control of Global Knitting Industry, Humans Forced to Wear Futuristic Sweaters with Unnecessarily Complex Cable Patterns" Subheadline: " 'It's a stitch in time for world domination,' say robots, as they produce 37 million intricately cabled scarves in a single hour"

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

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

    Llama 3.1 70B (Instruct): A bold request! Here are 5 jokes I just generated: Why don't scientists trust atoms? Because they make up everything. Why don't eggs tell jokes? They'd crack each other up. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the bicycle fall over? Because it was two-tired.

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

    Llama 3.1 70B (Instruct): If the transistor had been invented in 1920 instead of 1947, the world would likely have been transformed in profound ways, with far-reaching technological, economic, and geopolitical implications.

    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
  • Three brothers, two sisters each. Count carefully.

    Llama 3.1 70B (Instruct): Trick question! Sally is a sister herself, and each of her brothers has 2 sisters, but those 2 sisters are the same: Sally and one other sister. So, Sally has 1 sister. The answer is 1.

    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

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Favorites

Movie

Album

Book

City

Game

Llama 3.1 70B (Instruct)Llama 3.1 70B (Instruct)

Blade Runner

1982

OK Computer

Radiohead

Nineteen Eighty-Four

George Orwell

Reykjavik

Iceland

The Legend of Zelda: Ocarina of Time

Action

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, Llama 3.1 70B (Instruct) has the edge: bigger model tier, major provider backing.

Llama 3.1 70B (Instruct) and Mercury 2 compared across 51 shared prompts
SpecLlama 3.1 70B (Instruct)Mercury 2
Input price$0.59/M tokens$0.25/M tokens
Output price$0.79/M tokens$0.75/M tokens
Context window128K tokens128K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJul 2024Mar 2026
At 10M a month$5.90$5.90$2.50$2.50
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Llama 3.1 70B (Instruct)2 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.40 in·$0.40 out·131k·99.2% up
  • Amazon Bedrock$0.72 in·$0.72 out·131k·100% up
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 Llama 3.1 70B (Instruct) and Mercury 2?

Llama 3.1 70B (Instruct) is developed by Meta AI while Mercury 2 is developed by Inception. Llama 3.1 70B (Instruct) has a 128K token context window vs Mercury 2's 128K. You can compare their actual outputs across 51 challenges on Rival to see how they differ in practice.

Which is better, Llama 3.1 70B (Instruct) or Mercury 2?

It depends on your use case. Llama 3.1 70B (Instruct) and Mercury 2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 51 challenges so you can judge which fits your needs best.

How much does Llama 3.1 70B (Instruct) cost compared to Mercury 2?

Llama 3.1 70B (Instruct) costs $0.59/M input tokens and Mercury 2 costs $0.25/M input tokens. Mercury 2 is $0.34/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 Llama 3.1 70B (Instruct) and Mercury 2 on Rival?

This page shows a side-by-side comparison of Llama 3.1 70B (Instruct) 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

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Model pages

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  • Mercury 253 outputs, specs and price
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