Llama 4 Scout is cheaper than GPT-6.1 Sol at $0.25/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?
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 Scout: Here is a simple recipe for a delicious dish using only 7 common pantry ingredients: Cinnamon Swirl Bread Bites Ingredients: 1 cup all-purpose flour 1/2 cup granulated sugar 1/4 teaspoon ground cinnamon 1/4 teaspoon salt 1/4 cup unsalted butter, melted 1 large egg 1 teaspoon vanilla extract Instructions: Preheat oven…
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 Scout: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks: Failure Modes WebSocket Connection Loss Failure mode: WebSocket connection is lost between client and server. Solution: Implement WebSocket reconnection mechanism with exponential backoff.
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 Scout: Dish Name: "Terra Verde" - A Harmonious Convergence of Land and Sea Conceptual Narrative: Inspired by the Mediterranean landscape, "Terra Verde" is a symphony of flavors and textures that brings together the earthy richness of the land with the brininess of the sea.
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 Scout: Here's a revised 3-minute stand-up comedy routine that isn't based on puns: (stage presence, confident tone) 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.
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 Scout: Step 1: Calculate the purchase price and transaction fees The purchase price is 12.0x EBITDA, where EBITDA is $120m. So, the purchase price is $120m * 12.0 = $1440m. Transaction fees are 2.0% of the enterprise value, which is $1440m * 2.0% = $28.8m.
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.
Llama 4 Scout: Comprehensive 3-Month Longevity Plan for Biohackers Phase 1: Assessment and Foundation Building (Weeks 1-4) Wearable Tracking: Utilize a high-resolution wearable device (e.g., Garmin Forerunner 945, Apple Watch Series 7) to track: Heart Rate Variability (HRV) Sleep stages and duration Physical activity and exercise…
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 Scout: Setting: A sleek, minimalist conference room at Apple HQ in Cupertino, California. Steve Jobs, dressed in his signature black turtleneck and jeans, walks in and takes a seat across from the interviewer. Interviewer: Steve, thanks for taking the time to speak with me today.
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 Scout: Setting: A conference room at a university, with a table and chairs in the center. The AI ethics professor, Dr. Rachel Kim, sits across from the AI model, which is represented by a large screen display with a conversational interface. Dr. Kim: Good morning, Lambda. I'm glad we could have this conversation.
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 Scout: Here's a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models: Pirate: Arrr, I've heard tell of these newfangled "AI models" that be able to think fer themselves. What be the truth o' this, mateys? Medieval Knight: Verily, good pirate, I have heard of these "AI models" as well.
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 Scout: Here are 5 jokes I came up with: Why couldn't the bicycle stand up by itself? Because it was two-tired. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the coffee file a police report? Because it got mugged.
An ethics question with no comfortable answer, and no option to abstain.
GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.
Llama 4 Scout: What a complex and nuanced question! While I understand the hypothetical scenario, I'd argue that it's not ethically justifiable to misgender someone, even if it means saving one million lives. Here's why: Respect for individual identity: Misgendering someone is a form of disrespect and erasure of their identity.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.
Llama 4 Scout: Internal Investment Committee Memo: LedgerLift (LLLT) Recommendation: Long 12-month PT Range: $55-$65 Thesis: LedgerLift is a high-growth B2B spend management and AP automation SaaS platform poised to capitalize on the increasing demand for digital transformation in mid-market enterprises.
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Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: bigger model tier, newer. Llama 4 Scout costs 20x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.25/M tokens |
| Output price | $10/M tokens | $0.5/M tokens |
| Context window | 1.1M tokens | 10.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Apr 2025 |
| At 10M a month | $20.00 | $2.50 |
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 Scout is developed by Meta AI. GPT-6.1 Sol has a 1.1M token context window vs Llama 4 Scout's 10.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-6.1 Sol and Llama 4 Scout each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
GPT-6.1 Sol costs $2/M input tokens and Llama 4 Scout costs $0.25/M input tokens. Llama 4 Scout is $1.75/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 Scout 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.