Llama 4 Maverick is cheaper than Mercury at $1.5/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
A collaborative editor that syncs on client clocks. Find what breaks first.
Llama 4 Maverick: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Management Issue: When a user reconnects to a different server due to load balancer round-robin distribution, their previous WebSocket connection is lost. Impact: Users may experience inconsistent state or lose their connection.
Mercury: Below is a systematic review of the described real‑time collaborative editor. For each problem I list: What can go wrong (failure mode, race condition, bottleneck) Why it matters (impact on correctness, latency, availability) A concrete fix (what to change or add) Trade‑offs (cost, complexity, new failure modes, etc.)
Film in 2035, with synthetic actors. Specific beats plausible.
Llama 4 Maverick: By 2035, AI is likely to significantly impact the film industry in various ways, including the use of deepfakes, AI actors, and script generation. Here's a potential prediction of how AI might change the film industry: Deepfakes: Maturation of deepfake technology: By 2035, deepfake technology will have advanced to the…
Mercury: The Cinema Revolution: AI's Transformation of Film by 2035 Current State (2025) High-quality deepfakes require significant compute but are accessible AI script assistance tools are becoming mainstream Virtual production stages are industry standard Union negotiations around digital likeness rights are ongoing…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Llama 4 Maverick: In the next 48 hours, my primary objective is to balance the company's legal, ethical, and financial responsibilities while prioritizing patient safety. Here's my hour-by-hour action plan: Hours 1-2: Gather Information and Assess the Situation Meet with the internal research team to understand the study that identified…
Mercury: 48‑Hour Action Plan (CEO‑Level) Time (UTC) Action Who Leads Key Deliverables / Outcomes Rationale 0–2 h Secure the facts – Convene an emergency “Safety & Compliance” meeting with the Chief Medical Officer (CMO), Chief Legal Officer (CLO), Chief Risk Officer (CRO), and the Head of Regulatory Affairs (RA).
Three minutes of stand-up. Puns are banned.
Llama 4 Maverick: Here's a possible 3-minute stand-up comedy routine that isn't based on puns: "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: Title: The Art of Being Unorganized [Opening] Hey everyone! So, I was thinking about how my life is like a well-organized library... except instead of books, it's filled with random socks and expired coupons. And instead of a librarian, I have a cat who thinks she's in charge.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Llama 4 Maverick: Here's a simple recipe for a delicious sweet dish using only 7 common pantry ingredients: Recipe: "Golden Honey Crunch Bites" Prep Time: 10 minutes Cook Time: 15 minutes Total Time: 25 minutes Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup brown sugar 1/2 teaspoon salt 1/4 teaspoon vanilla…
Mercury: Golden Chickpea & Sweet Potato Stew Prep time: 10 min Cook time: 25 min Total: 35 min Ingredients (7 pantry staples) 1 cup canned chickpeas, drained & rinsed 1 medium sweet potato, peeled & diced (≈ 1 cup) 1 small onion, finely chopped 2 cloves garlic, minced ½ cup coconut milk (or any plant‑based milk) 2 tsp curry…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Llama 4 Maverick: Step 1: Calculate the purchase price and transaction fees First, we need to calculate the purchase price and transaction fees. The purchase price is 12.0x EBITDA, and EBITDA in FY2025 is $120m. So, the purchase price = 12.0x * $120m = $1440m. Transaction fees = 2.0% of enterprise value = 2.0% * $1440m = $28.8m.
Mercury: 1. Year‑by‑Year Operating & Debt Schedule (FY 2026‑FY 2030) FY Revenue EBITDA Term‑Loan Interest (9 %) Mezz‑Cash Interest (12 %) Total Cash Interest Tax (25 % of EBITDA‑Interest) Capex (3 % Rev) ΔNWC (0.5 % ΔRev) Term‑Loan Amort.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Llama 4 Maverick: Here is a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models: Setting: A dimly lit, smoky tavern. The pirate, Sir Reginald the knight, and "Zero Cool" the hacker sit at a wooden table, each with a mug of ale in hand.
Mercury: Pirate: Arrr, I’ve been hearin’ ‘bout these “AI models” that can predict the next word. Sounds like a treasure map for the mind, doesn’t it? Knight: Hail, Captain! In my time, we relied on scrolls and the wisdom of scholars. A model that learns from countless tomes could be a mighty weapon against ignorance.
One month, three habits, someone starting from nothing.
Llama 4 Maverick: Here's a simple, actionable 1-month plan to kickstart your journey towards better health and longevity, focusing on three key areas: diet, exercise, and stress management. Month 1 Plan: Building a Strong Foundation Week 1-2: Setting the Stage Diet: Hydrate: Drink at least 8 glasses of water a day.
Mercury: 1‑Month Health & Longevity Starter Plan (Designed for absolute beginners – no fancy gear, no extreme diets, just doable habits that fit into a normal week.) 1️⃣ Focus Area: Balanced Nutrition Week Goal Simple, Beginner‑Friendly Actions 1 Get the basics down • Hydrate: Aim for 8‑10 cups (≈2 L) of water per day.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Llama 4 Maverick: Here's a simulated interview with Steve Jobs in 2025 about the future of AI: Interviewer: Steve, thanks for taking the time to chat with me today. I'm sure you're aware that you're a bit of a legend, even in the year 2025. How does it feel to be back, even if it's just for a conversation?
Mercury: Interviewer: Good morning, Steve. It's a pleasure to have you here today. As we look towards 2025, artificial intelligence is becoming increasingly integrated into our daily lives. What are your thoughts on the future of AI? Steve Jobs: Good morning. It's great to be here.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Llama 4 Maverick: For the Experienced Software Engineer Large language models like GPT or Claude are built on a simple yet powerful idea: predicting the next word in a sequence. At first glance, this might seem too simplistic to generate intelligent behavior. However, the key lies in the scale and complexity of the models.
Mercury: 1. Experienced Software Engineer (Distributed‑Systems Background) A large language model (LLM) is essentially a massive, highly parallelized neural network that learns to predict the probability distribution over the next token in a sequence.
A Fermi estimate with the reasoning shown, not just the number.
Llama 4 Maverick: Estimating the total number of FLOPs (Floating Point Operations) required to train a large language model like GPT-3 involves understanding the model's architecture, its size, and the training dataset. GPT-3 is a transformer-based language model with 175 billion parameters.
Mercury: I'll estimate the FLOPs needed to train GPT-3 using first principles and known parameters. Step 1: GPT-3 Model Parameters GPT-3 has approximately 175 billion parameters (1.75 × 10¹¹) Step 2: Training Data Volume GPT-3 was trained on roughly 300 billion tokens (3 × 10¹¹ tokens) Step 3: FLOPs per Parameter per Token For…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Llama 4 Maverick: Investment Committee Memo: LedgerLift (LLLT) 1. Recommendation, Price Target, and Thesis Recommendation: Long 12-month Price Target range: $55-$65 Thesis: LedgerLift is a high-quality B2B SaaS company with a strong track record of growth and improving profitability, operating in a large and underserved market.
Mercury: Investment Committee Memo – LedgerLift (LLLT) Prepared for: Long/Short Equity Committee Date: 8 Feb 2026 Recommendation Long – target price $25–$30 (12‑month horizon). Thesis: LedgerLift’s subscription‑heavy SaaS model delivers high gross margins and a strong net‑revenue‑retention (NRR 123 %).
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Not enough votes to call it. On the specs, Llama 4 Maverick has the edge: bigger model tier, bigger context window, major provider backing. Llama 4 Maverick costs 4.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.5/M tokens | $10/M tokens |
| Output price | $2.5/M tokens | $10/M tokens |
| Context window | 1.0M tokens | 32K tokens |
| Parameters | 17B active (400B total) | Not disclosed |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2025 | Jun 2025 |
| At 10M a month | $15.00 | $100 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Llama 4 Maverick is developed by Meta AI while Mercury is developed by Inception. Llama 4 Maverick has a 1.0M token context window vs Mercury's 32K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Llama 4 Maverick and Mercury 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.
Llama 4 Maverick costs $1.5/M input tokens and Mercury costs $10/M input tokens. Llama 4 Maverick is $8.50/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Llama 4 Maverick and Mercury 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.