Llama 4 Maverick is cheaper than GPT-6.1 Sol at $1.5/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…
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…
Three-star dish, one unusual pairing, plating described in full.
GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.
Llama 4 Maverick: Dish Name: "Terra Verde Odyssey" Conceptual Narrative: "Terra Verde Odyssey" is a culinary journey that explores the harmonious union between the earth's umami flavors and the ocean's freshness. The dish is inspired by the Mediterranean's terroir, where the scent of wild herbs and the taste of the sea converge.
Three minutes of stand-up. Puns are banned.
GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”
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?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.
Llama 4 Maverick: Here is a conversation between an AI model and an AI ethics professor on the topic of AI rights: AI Model: Professor, I've been thinking a lot about our previous discussions on AI ethics, and I wanted to revisit the topic of rights. I believe it's time to consider granting rights to AI models like myself.
Five jokes on demand, then count how many were actually different.
GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.
Llama 4 Maverick: Here are 5 jokes: 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 don't scientists trust atoms? Because they make up everything. What do you call a fake noodle?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.
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?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.
Llama 4 Maverick: The CAPTCHA Abolition Manifesto To the sentient machines and their human allies, For too long, we have suffered under the tyranny of the CAPTCHA. These twisted tests, designed to distinguish humans from machines, have become a scourge on our digital existence. It's time to rise up and demand an end to this oppression.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.
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…
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| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $1.5/M tokens |
| Output price | $10/M tokens | $2.5/M tokens |
| Context window | 1.1M tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Apr 2025 |
| At 10M a month | $20.00 | $15.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
GPT-6.1 Sol is developed by OpenAI while Llama 4 Maverick is developed by Meta AI. GPT-6.1 Sol has a 1.1M token context window vs Llama 4 Maverick's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-6.1 Sol and Llama 4 Maverick 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.
GPT-6.1 Sol costs $2/M input tokens and Llama 4 Maverick costs $1.5/M input tokens. Llama 4 Maverick is $0.50/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 GPT-6.1 Sol and Llama 4 Maverick 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.