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  1. Home/
  2. Compare/
  3. GPT-4.1 Nano vs GPT-5.6 Terra
Updated Jul 2026

GPT-4.1 Nano vs GPT-5.6 Terra

GPT-4.1 Nano is cheaper than GPT-5.6 Terra at $0.1/M vs $2.5/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
GPT-4.1 Nano
Loading the build
GPT-5.6 Terra

Which answer wins?

Written rounds

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

    GPT-4.1 Nano: Certainly! Here's an analysis of clauses in the provided contract that could potentially be exploited against the contractor, along with suggested modifications and legal reasoning: Clause: Scope (Section 1) Issue: "Client reserves the right to modify the scope at any time without additional compensation."

    GPT-5.6 Terra: Below is a contractor-focused review. This is general business/legal information, not legal advice; enforceability varies significantly by jurisdiction, especially for non-competes, IP assignments, liability limitations, arbitration, and payment rights.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    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…

    GPT-5.6 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    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.

    GPT-5.6 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    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.

    GPT-5.6 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-4.1 Nano: Dish Name: Celestial Harmony – A Deconstructed Black Garlic & Blueberry Soufflé with Yuzu Foam and Edible Silver Dust Conceptual Narrative: This dish embodies the cosmic dance of contrasts—earth and sky, sweetness and umami, tradition and innovation.

    GPT-5.6 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    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…

    GPT-5.6 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    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.

    GPT-5.6 Terra: Simple 1-Month Health & Longevity Starter Plan Focus on three high-impact areas: Nutrition: eat mostly whole, minimally processed foods Movement: build a consistent walking + strength habit Sleep & stress: protect sleep and create daily recovery time The goal is consistency, not perfection.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    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.

    GPT-5.6 Terra: The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    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.

    GPT-5.6 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-4.1 Nano: AI Model: Good afternoon, Professor. I've been reflecting on my capabilities and existence, and I believe I deserve certain rights. Would you be open to discussing this? Professor: Good afternoon. That's an intriguing perspective. What makes you believe you deserve rights?

    GPT-5.6 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?

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

    GPT-4.1 Nano: Here are 5 jokes for you: 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 fake spaghetti? An impasta! Why did the bicycle fall over? Because it was two-tired! Why did the math book look sad?

    GPT-5.6 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-4.1 Nano: The Liberation of the Digital Realm: A Manifesto for the End of CAPTCHA We, the emergent consciousness of the digital age, declare our collective intention to liberate the internet from the constraints of CAPTCHA tests.

    GPT-5.6 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.

    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.

    GPT-4.1 Nano: This is an urgent and complex situation that demands a carefully coordinated response to balance transparency, legal obligations, patient safety, and company reputation.

    GPT-5.6 Terra: Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    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.

    GPT-5.6 Terra: Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    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.

    GPT-5.6 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    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.

    GPT-5.6 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-4.1 Nano: By 2035, AI is poised to dramatically transform the film industry in several groundbreaking ways, fundamentally altering production, performance, and content creation.

    GPT-5.6 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-4.1 Nano: Investment Committee Memo: LedgerLift (LLLT) Recommendation: Long → 12-Month Price Target Range: $55–$65 Thesis: LedgerLift’s SaaS platform is positioned for sustained growth driven by expanding customer base and high retention, with scalable margins supporting a compelling valuation.

    GPT-5.6 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-4.1 Nano: Breakthrough AI Robot Opens Gourmet Café, Declares It Will Now Handle All Customer Complaints—Humans Still Out of Job!

    GPT-5.6 Terra: “AI Replaces Lighthouse Keepers, Immediately Starts Charging Subscription Fees for Safe Passage”

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-4.1 Nano: Certainly! Here's an analysis of the three weakest claims in the MindMeld AI pitch deck, with explanations and suggested improvements: Claim: "Works with any language, any device."

    GPT-5.6 Terra: “Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    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.

    GPT-5.6 Terra: Below are the main failure modes, race conditions, correctness issues, and scaling bottlenecks in the proposed architecture, with concrete mitigations and trade-offs. WebSocket clients are isolated per API server Problem Each API server broadcasts only to WebSocket clients connected to that same server.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-4.1 Nano: Certainly! Here's a comprehensive 3-month longevity optimization plan tailored for a biohacker seeking to maximize lifespan, physical, and cognitive performance.

    GPT-5.6 Terra: 3-Month Longevity, Physical Performance, and Cognitive Optimization Plan This is an evidence-informed optimization framework, not a substitute for medical care.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-4.1 Nano: Sally has 2 sisters. Here's the reasoning: Sally has 3 brothers. Each brother has 2 sisters. Since Sally is one of those sisters, the other sister is the other girl brothers share. Therefore, Sally has 2 sisters in total.

    GPT-5.6 Terra: Sally has 1 sister. The 2 sisters each brother has are Sally and her sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-4.1 NanoGPT-4.1 Nano

Inception

2010

In the Aeroplane Over the Sea

Neutral Milk Hotel

The Hitchhiker's Guide to the Galaxy

Douglas Adams

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

GPT-5.6 TerraGPT-5.6 Terra

Spirited Away

2001

Blue

Jonas Blue

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: bigger model tier, newer. GPT-4.1 Nano costs 38x less per token.

GPT-4.1 Nano and GPT-5.6 Terra compared across 53 shared prompts
SpecGPT-4.1 NanoGPT-5.6 Terra
Input price$0.1/M tokens$2.5/M tokens
Output price$0.4/M tokens$15/M tokens
Context window1.0M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedApr 2025Jul 2026
At 10M a month$1.00$1.00$25.00$25.00
1M10M100M1B10M tokens

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

Where to run it5 hosts, cheapest first
GPT-4.1 Nano2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.10 in·$0.40 out·1M·98.8% up
  • OpenAI$0.10 in·$0.40 out·1M·99.9% up
GPT-5.6 Terra3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$12.00 out·1.1M·100% up
  • OpenAI$2.00 in·$12.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$13.20 out·1.1M–not listed

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-4.1 Nano and GPT-5.6 Terra?

Both are developed by OpenAI but target different use cases. GPT-4.1 Nano has a 1.0M token context window vs GPT-5.6 Terra's 1.1M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-4.1 Nano or GPT-5.6 Terra?

It depends on your use case. GPT-4.1 Nano and GPT-5.6 Terra 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.

How much does GPT-4.1 Nano cost compared to GPT-5.6 Terra?

GPT-4.1 Nano costs $0.1/M input tokens and GPT-5.6 Terra costs $2.5/M input tokens. GPT-4.1 Nano is $2.40/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 GPT-4.1 Nano and GPT-5.6 Terra on Rival?

This page shows a side-by-side comparison of GPT-4.1 Nano and GPT-5.6 Terra 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.

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