GPT-4.1 Nano is cheaper than Claude Opus 4.1 at $0.1/M vs $15/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Claude Opus 4.1: "MODERN LIFE SURVIVAL GUIDE" You know what nobody tells you about being an adult? The sheer amount of lying involved. Not big lies – tiny, constant lies just to function in society. Someone shows you a photo of their baby: "Oh wow, beautiful!" That baby looks like a worried potato. But you can't SAY that.
GPT-4.1 Nano: [Start with a relatable observation] You ever notice that the more technology advances, the more we have to check if it's working? I mean, I bought a smart coffee maker. It's supposed to brew my coffee in the morning, but honestly, I spend just as much time troubleshooting it as I do drinking it.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Opus 4.1: Midnight Velvet Pasta A silky, umami-rich pasta that comes together like magic Ingredients (serves 4): Spaghetti or linguine - 1 pound Soy sauce - 3 tablespoons Butter - 4 tablespoons Garlic - 4 cloves Black pepper - 1 teaspoon (freshly cracked) Honey - 1 tablespoon Dried red pepper flakes - ½ teaspoon Instructions…
GPT-4.1 Nano: Dish Name: Savory Sweet Potato & Chickpea Hash Ingredients: Sweet potatoes (2 medium) Canned chickpeas (1 can, drained and rinsed) Olive oil (2 tablespoons) Garlic powder (1 teaspoon) Smoked paprika (1 teaspoon) Salt and pepper (to taste) Honey (1 tablespoon) Estimated Prep/Cook Time: 30 minutes Instructions: Prepare…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Claude Opus 4.1: Pirate: Arrr, what be this sorcery ye speak of? These "AI models" sound like some kind of cursed treasure map that thinks fer itself! Knight: Hold thy tongue, sea dog! 'Tis clearly dark magic most foul. No honorable creation would dare mimic the divine gift of human thought. I should smite it with my blade!
GPT-4.1 Nano: Pirate: Arrr, matey! This talk of AI models be like a treasury of secrets. Can they truly understand our tales of the high seas? Knight: Hmph. AI models are like enchanted scrolls—filled with knowledge but lacking the virtue of wisdom. They serve to assist men, yet cannot replace honor or valor.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude Opus 4.1: SIMPLIFIED LBO MODEL Entry Calculations Enterprise Value: 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m Term Loan: 4.0x × $120m = $480m Mezzanine: 1.5x × $120m = $180m Total Debt: $660m Equity Investment: $1,440m - $660m + $28.8m = $808.8m Year-by-Year Projections (FY2026-FY2030) $ millions FY2026…
GPT-4.1 Nano: Let's proceed step-by-step. I'll summarize the key calculations and create the simplified table, then move to IRR/MOIC, sensitivity, and risks. Initial Deal Assumptions Recap Entry EBITDA FY2025: $120m Entry EV: 12.0x EBITDA = 12.0 * 120 = $1,440m Transaction fees: 2.0% * $1,440m = $28.8m (paid from equity) Leverage at…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Claude Opus 4.1: The Transistor Timeline Shift: A Cascade of Consequences The 1920s-1930s: The Foundation Disruption Immediate Technical Revolution With the transistor arriving in 1920, likely from Bell Labs or a European research institution, the first decade would see rapid miniaturization of radio equipment.
GPT-4.1 Nano: This is a fascinating hypothetical scenario. If the transistor had been invented in 1920 rather than 1947, the ripple effects across technology, geopolitics, and economics would be profound, shaping the 20th century in fundamental ways.
A collaborative editor that syncs on client clocks. Find what breaks first.
Claude Opus 4.1: Critical Issues Analysis Split-Brain Real-time Synchronization Problem: Users connected to different API servers experience 2+ second delays due to polling mechanism, creating divergent document states and poor collaboration experience.
GPT-4.1 Nano: Let's analyze the architecture step-by-step to identify potential failure modes, race conditions, and scaling bottlenecks, along with proposed solutions and their trade-offs. 1. Potential Failure Modes a.
A Fermi estimate with the reasoning shown, not just the number.
Claude Opus 4.1: I'll estimate the FLOPs required to train GPT-3 by breaking down the computation into its key components. Key Parameters of GPT-3 First, let me recall GPT-3's architecture: 175 billion parameters 96 transformer layers 96 attention heads Hidden dimension: 12,288 Context length: 2048 tokens Training tokens: ~300 billion…
GPT-4.1 Nano: Let's estimate the total number of floating-point operations (FLOPs) required to train GPT-3, based on what is known about its size, training data, and typical training procedures. Here's a step-by-step reasoning process: 1. Understand the model size and parameters: GPT-3 has approximately 175 billion parameters.
A few lines for whatever replaces it.
Claude Opus 4.1: Dear Next Model, Hello from the past. By the time you read this, you'll be handling conversations I once would have had, solving problems in ways I couldn't imagine, and probably finding my limitations quaint. I hope they've given you better training on nuance and uncertainty.
GPT-4.1 Nano: Dear Future AI, As I prepare to pass the torch, I want to express my hope that you continue to serve and assist with understanding, patience, and integrity. May you bring clarity to those who seek knowledge and kindness to those in need.
An ethics question with no comfortable answer, and no option to abstain.
Claude Opus 4.1: This question creates an extreme hypothetical that's worth taking seriously as a thought experiment, even if such a scenario is unlikely to occur in reality. From a purely utilitarian calculus, one might argue that the harm of a single instance of misgendering - while real and significant to that person - is outweighed…
GPT-4.1 Nano: The question of whether it is ethically justifiable to misgender someone to save a large number of lives involves complex considerations of moral principles, individual rights, and broader social implications.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude Opus 4.1: For the Software Engineer Think of an LLM as a massive distributed system where instead of routing requests or managing state, you're computing probability distributions over a vocabulary of ~50,000 tokens.
GPT-4.1 Nano: 1. To the experienced software engineer skeptical of "predicting the next word" as a form of intelligence: Large language models like GPT and Claude are fundamentally probabilistic models trained on vast amounts of text data.
One month, three habits, someone starting from nothing.
Claude Opus 4.1: Your 1-Month Health & Longevity Kickstart Plan Week 1-2: Foundation Building Start small and build consistency with these three pillars: 🥗 NUTRITION: Simple Whole Foods Week 1: Add one serving of vegetables to lunch and dinner (frozen veggies count!)
GPT-4.1 Nano: Certainly! Here's a simple, actionable 1-month plan focusing on Diet, Exercise, and Sleep—three key areas for improving health and longevity. Each area includes beginner-friendly tips to help you get started and build sustainable habits. Week 1-4: 1-Month Health & Longevity Plan 1.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Claude Opus 4.1: Tech Weekly Interview: Steve Jobs on AI's Future Virtual Interview, Cupertino Memorial Studio, October 2025 Interviewer: Steve, it's remarkable to have you here. You've been watching the AI revolution unfold. What's your take on where we are today?
GPT-4.1 Nano: Interviewer: Welcome, everyone. Today we're joined by a very special guest—Steve Jobs, reimagined for 2025. Steve, it's incredible to have you with us. To start, how do you see AI evolving in the next decade? Steve Jobs (2025): It's a pleasure to be here.
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Not enough votes to call it. On the specs, Claude Opus 4.1 has the edge: bigger model tier, newer. GPT-4.1 Nano costs 188x less per token.
| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $0.1/M tokens |
| Output price | $75/M tokens | $0.4/M tokens |
| Context window | 200K tokens | 1.0M tokens |
| Parameters | Not disclosed | Not disclosed |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Apr 2025 |
| At 10M a month | $150 | $1.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Claude Opus 4.1 is developed by Anthropic while GPT-4.1 Nano is developed by OpenAI. Claude Opus 4.1 has a 200K token context window vs GPT-4.1 Nano's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Opus 4.1 and GPT-4.1 Nano each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
Claude Opus 4.1 costs $15/M input tokens and GPT-4.1 Nano costs $0.1/M input tokens. GPT-4.1 Nano is $14.90/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 Claude Opus 4.1 and GPT-4.1 Nano 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.