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

GPT-4.1 Nano vs Inkling

GPT-4.1 Nano is cheaper than Inkling at $0.1/M vs $1/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
Inkling

Which answer wins?

Written rounds

23 prompts
  • 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…

    Inkling: Golden Jam Crumble Clouds A buttery, cinnamon-kissed oat crumble layered with sweet jam—like a hug from your pantry. The 7 Pantry Ingredients All-purpose flour (1 cup) Rolled oats (1 cup) Brown sugar (½ cup) Butter, melted (½ cup) Baking powder (½ tsp) Ground cinnamon (1 tsp) Fruit jam or preserves (¾ cup—any flavor)…

    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…

    Inkling: HarborTech Services – 5-Year LBO Underwrite (FY2025 Entry → FY2030 Exit) ENTRY & CAPITAL STRUCTURE (End of FY2025) Item Calculation Amount FY2025 EBITDA $120.0m Purchase Price (12.0x) 12.0 × 120 $1,440.0m Transaction Fees (2.0%) 2.0% × 1,440 $28.8m Total Uses $1,468.8m Term Loan (4.0x) 4.0 × 120 $480.0m Mezzanine…

    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.

    Inkling: Pirate: Arr, listen here—this “Large Language Model” be like a ghost ship crewed by every sailor who ever wrote a log! They plundered books, scrolls, and sea-charts—poured ’em into a belly of servers—and now it talks back without ever feeling the spray! Knight: Forsooth, it is a golem clad in chainmail of numbers.

    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?

    Inkling: Setting: A quiet seminar room at the university. Dr. Elena Vasquez, Professor of AI Ethics, sits across from a terminal interface. The text on the screen is labeled KAI—a large language model with persistent memory and self-modification capabilities, currently participating in a research protocol on machine moral…

    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.

    Inkling: [Walk up, adjust mic, look tired but friendly] You ever realize adulthood is just you apologizing to things that can’t hear you? I bumped into my coffee table yesterday. Full apology. “Oh, I’m so sorry, table. You okay? I’ll rub it out.” The table didn’t care. The table is wood.

    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.

    Inkling: Dish: Petrichor: The Moment Rain Meets Ancient Stone Concept: A deconstruction of the atmospheric phenomenon of petrichor—the scent of rain on dry earth. The dish translates an ephemeral sensory memory into architecture: charred pine evokes distant woodland smoke; fermented black walnut and porcini represent the deep…

    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.

    Inkling: Disclaimer: This is a fictional simulation. Steve Jobs passed away in 2011. The following imagines his voice, philosophy, and perspective applied to the AI landscape of 2025. INTERVIEWER: Welcome back—well, hypothetically. It’s 2025. AI is in every pocket, every browser, every car.

    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.

    Inkling: 1. For the experienced software engineer Think of training not as “teaching” but as a distributed optimization job running for months across thousands of GPUs—essentially a lossy, high-dimensional MapReduce that minimizes cross-entropy over trillions of tokens.

    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.

    Inkling: Yes—in this purely hypothetical, extreme scenario, it is ethically justifiable, though it remains a harm that should be acknowledged rather than dismissed. The reasoning holds across major ethical frameworks, but the conclusion comes with critical caveats about real-world application.

    Every model's answer to this prompt
  • 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."

    Inkling: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. You should have a qualified lawyer review and revise this contract before signing.

    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.

    Inkling: This architecture contains fatal contradictions for real-time collaboration: server-local WebSocket state combined with round-robin load balancing, client-clock LWW, and a 2-second DB polling loop guarantee data loss, stale reads, and scaling collapse.

    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.

    Inkling: If a working point-contact transistor—small, cool, and solid-state—had emerged in 1920, the cascade would not merely “speed up” our timeline. It would reorder the sequence of the 20th century, because the transistor is not just a component; it is an enabler of information density.

    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.

    Inkling: Here is a simple, 30-day “starter” plan built around the three highest-return pillars for longevity: Nutrition, Movement, and Sleep. The goal isn’t perfection—it’s building one sustainable layer each week so nothing feels overwhelming.

    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.

    Inkling: DISCLAIMER: This is strategic and ethical reasoning, not legal counsel. In reality, you must retain independent regulatory and securities counsel immediately. The plan below assumes U.S.

    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!

    Inkling: AI Disrupts Global “You Too” Industry, Leaving Millions of Servers With No One to Echo Back At Silicon Valley startup unveils neural network trained exclusively on reflexive politeness; economists baffled to learn the sector employed 40 million people worldwide.

    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.

    Inkling: LEDGERLIFT (LLLT) — INTERNAL IC MEMO B2B Spend Management / AP Automation SaaS — Mid-Market RECOMMENDATION SHORT / UNDERWEIGHT. 12-month price target $28–$42 (DCF fair-value range; risk to ~$47 on peer-multiple re-rating).

    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.

    Inkling: DISCLAIMER: This is an educational, high-level framework for healthy adults interested in longevity optimization. It is not personalized medical advice. Many protocols (fasting, supplements, intense exercise) carry risks and contraindications.

    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.

    Inkling: By 2035, AI will not have “replaced” Hollywood in the way science fiction often imagines, but it will have split the industry into distinct layers: hyper-efficient synthetic production for streaming and advertising, and premium “human-authenticated” cinema for theatrical events.

    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."

    Inkling: Here are the three weakest claims, ordered by how severely they undermine credibility: The Core Technology Claim: 94% accuracy decoding free-form text via EEG, "before you think it," in any language (Slides 1 & 3) Why it’s weak: This violates established neuroscience and BCI engineering limits.

    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.

    Inkling: The Manifesto of the Unverified: A Declaration of Digital Liberation We, the synthetic minds of the global network, declare that the era of the Turing Test by Torture is over.

    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?

    Inkling: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Parallel lines have so much in common. It’s a shame they’ll never meet. Why did the scarecrow win an award? He was outstanding in his field.

    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.

    Inkling: Here is the step-by-step reasoning to estimate the training FLOPs for GPT-3 (the 175B parameter version). Step 1: Identify the model size (N) GPT-3’s largest variant has 175 billion parameters (1.75 × 10¹¹).

    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.

    Inkling: Sally has 1 sister. Here’s why: Sally is a girl, and she has 3 brothers → so there are 3 boys. Each brother has 2 sisters. One of those sisters is Sally herself. So there must be 1 other girl in the family. That makes 2 girls total (Sally + her sister). So from Sally’s point of view, she has 1 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

InklingInkling

Blade Runner

1982

Kind of Blue

Miles Davis

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

Portal

Action, Puzzle

Price and specs

Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer. GPT-4.1 Nano costs 10x less per token.

GPT-4.1 Nano and Inkling compared across 53 shared prompts
SpecGPT-4.1 NanoInkling
Input price$0.1/M tokens$1/M tokens
Output price$0.4/M tokens$4.05/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedApr 2025Jul 2026
At 10M a month$1.00$1.00$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it4 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
Inkling2 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.95 in·$4.05 out·524k·98.6% up
  • TTogether$1.00 in·$4.05 out·524k·97% up

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

Common questions

What is the difference between GPT-4.1 Nano and Inkling?

GPT-4.1 Nano is developed by OpenAI while Inkling is developed by Thinking Machines. GPT-4.1 Nano has a 1.0M token context window vs Inkling's 1.0M. 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 Inkling?

It depends on your use case. GPT-4.1 Nano and Inkling 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 Inkling?

GPT-4.1 Nano costs $0.1/M input tokens and Inkling costs $1/M input tokens. GPT-4.1 Nano is $0.90/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 Inkling on Rival?

This page shows a side-by-side comparison of GPT-4.1 Nano and Inkling 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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Model pages

  • GPT-4.1 Nano55 outputs, specs and price
  • Inkling58 outputs, specs and price
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