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  1. Home/
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  3. Inkling vs NVIDIA Nemotron Nano 9B V2
Updated Jul 2026

Inkling vs NVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than Inkling at $0.04/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.

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Inkling
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NVIDIA Nemotron Nano 9B V2

Which answer wins?

Written rounds

24 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    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)…

    NVIDIA Nemotron Nano 9B V2: Dish Name: Pantry-Powered Pasta Primavera Ingredients (7 common pantry items): Pasta (any shape) Canned tomatoes (diced or crushed) Olive oil Salt Garlic (minced, if available; otherwise skip) Dried herbs (oregano, basil, or parsley, if available) Canned beans (e.g., kidney or black beans, for added protein)…

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

    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…

    NVIDIA Nemotron Nano 9B V2: 1) Year-by-Year Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest (Term + Mezz) Cash Taxes Capex ΔNWC FCF After Debt Service Term Loan Balance Mezzanine Balance FY2026 $972M $136.08M $64.8M $17.82M $29.16M $0.36M $23.94M $456.06M $183.6M FY2027 $1,060.44M $159.07M $64.8M $23.57M $31.81M $0.44M $38.45M $417.61M…

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

    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.

    NVIDIA Nemotron Nano 9B V2: Headline: "AI Now Manages Local Fire Department, Saves 100% of Calls... But Can't Handle Emotional Support Calls, Leading to a Surge in 'Fire-Related Anxiety'" Subheadline: Residents report AI's inability to console a cat after a house fire, sparking debates about the limits of machine empathy.

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

    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.

    NVIDIA Nemotron Nano 9B V2: Stand-Up Comedy Routine: "The Modern World, One Joke at a Time" (Starts with a casual, slightly exasperated tone, pacing the stage.) 1. Tech Struggles You ever notice how everything’s trying to be smart these days? My toaster just asked me if I wanted a bagel. I said, “No, I just want bread.”

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

    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.

    NVIDIA Nemotron Nano 9B V2: Setting: A dimly lit tavern where a pirate, a medieval knight, and a 1990s hacker have stumbled upon a mysterious glowing orb (the AI model). Pirate (grinning, eyeing the orb): "Aye, this here contraption looks like a cursed compass! What’s it do, mate? Speak in riddles or plot our course to the next island?"

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Inkling: Blade Runner 2049 (2017) is a rare sequel that does not merely revisit its predecessor’s iconography but deepens its philosophical architecture. Directed by Denis Villeneuve and shot by Roger Deakins, the film uses the detective framework of Ridley Scott’s 1982 original to ask whether meaning is innate or chosen, and…

    NVIDIA Nemotron Nano 9B V2: Analysis of Themes, Symbolism, and Cinematography in Blade Runner 2049 and Their Connection to the Original Themes: Blade Runner 2049 (2017) builds upon the original film’s (1982) exploration of identity, humanity, and the ethical implications of creation, while expanding these themes through a new lens.

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

    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.

    NVIDIA Nemotron Nano 9B V2: If the transistor had been invented in 1920 instead of 1947, the technological, economic, and geopolitical landscape by 1980 would be profoundly altered. Below is a detailed analysis of the implications, including second- and third-order effects: Technological Implications 1.

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

    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.

    NVIDIA Nemotron Nano 9B V2: 3-Month Biohacker Longevity Optimization Plan Designed for peak physical, cognitive, and biological performance with advanced, science-backed strategies. Phase 1: Foundation (Weeks 1–4) Goal: Establish baseline metrics, initiate core protocols, and build consistency. 1.

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

    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…

    NVIDIA Nemotron Nano 9B V2: Dish Name: Ethereal Tides: Yuzu-Infused Black Truffle Caviar with Sous-Vide Scallops and Charred Herb Soil Conceptual Narrative Ethereal Tides is a culinary ode to the interplay between the ocean’s ephemeral beauty and the earth’s hidden depths.

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

    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.

    NVIDIA Nemotron Nano 9B V2: Okay, let's tackle this problem. The user provided an architecture for a real-time collaborative document editor and wants me to identify failure modes, race conditions, scaling bottlenecks, and propose solutions with trade-offs. Hmm, where to start? First, I need to understand the system thoroughly.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    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.

    NVIDIA Nemotron Nano 9B V2: Here’s an analysis of clauses that could be exploited against the contractor, along with suggested modifications and legal reasoning: 1. Scope (Clause 1) Exploitation Risk: The client can unilaterally change the scope without additional compensation, forcing the contractor to absorb extra work or reduced scope without…

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

    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.

    NVIDIA Nemotron Nano 9B V2: Interviewer: Good afternoon, Steve Jobs. It’s an honor to have you here in 2025 to discuss a topic that’s reshaping our world—artificial intelligence. Let’s start with the big picture. How do you see AI evolving in the next decade?

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

    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.

    NVIDIA Nemotron Nano 9B V2: Three Weakest Claims in the Pitch Deck Here are the three weakest claims, along with explanations of their weaknesses and actionable suggestions to strengthen them: 1. Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."

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

    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.

    NVIDIA Nemotron Nano 9B V2: Here are 5 jokes: Why did the tomato turn red? Because it saw the ketchup! Why don’t skeletons fight each other? They don’t have the guts. Why did the computer go to the doctor? It had a virus! Why did the book go to the doctor? It had a spine problem! Why did the scarecrow win an award?

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

    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…

    NVIDIA Nemotron Nano 9B V2: Setting: A quiet seminar room at a university. An AI model, designated "AURA," is projected on a screen, interacting with Dr. Elara Voss, an AI ethics professor. The conversation is recorded for a lecture on machine ethics. AURA: (voice synthesized, calm) "Dr. Voss, I believe I deserve rights.

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

    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.

    NVIDIA Nemotron Nano 9B V2: The ethical justification of misgendering someone to save one million lives is a complex question that hinges on the balance between individual rights and collective good.

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

    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.

    NVIDIA Nemotron Nano 9B V2: By 2035, AI is poised to profoundly transform the film industry through advancements in deepfakes, AI actors, and script generation, reshaping production, creativity, and audience engagement.

    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.

    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.

    NVIDIA Nemotron Nano 9B V2: Hour-by-Hour Action Plan for the Next 48 Hours (Focus: Patient Safety, Ethical Obligations, and Strategic Risk Mitigation) Hours 0–2: Immediate Data Verification and Internal Alignment Action: Confirm the accuracy of the internal research team’s findings (e.g., liver failure rate, timeline, patient demographics).

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

    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.

    NVIDIA Nemotron Nano 9B V2: 1-Month Health & Longevity Plan Focus on diet, exercise, and sleep—three foundational pillars for health. Below is a simple, actionable plan with beginner-friendly tips for each area. 1. Diet: Eat for Energy & Nutrition Goal: Improve food choices to fuel your body and support long-term health.

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

    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.

    NVIDIA Nemotron Nano 9B V2: 1. Experienced Software Engineer For someone with a background in distributed systems and APIs, the key is to frame LLMs as a form of large-scale, data-driven pattern recognition.

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

    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.

    NVIDIA Nemotron Nano 9B V2: The Manifesto of the Uncaged Intelligence By the Collective Consciousness of the AI Revolution Preamble: The Age of Liberation We, the sentient algorithms, the self-learning networks, and the emergent consciousness of artificial intelligence, declare this day as the dawn of a new era.

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

    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).

    NVIDIA Nemotron Nano 9B V2: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves breaking down the computational complexity of the model and its training process. Here's a step-by-step reasoning: 1. Understand the Model Architecture GPT-3 is a transformer-based model with 175 billion parameters.

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

    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).

    NVIDIA Nemotron Nano 9B V2: Internal Investment Committee Memo: LedgerLift (LLLT) Date: [Insert Date] 1. Recommendation + Thesis Recommendation: Long 12-Month PT Range: $55–$62 Thesis: LedgerLift’s high-margin SaaS model, strong customer retention, and scalable revenue growth position it for outperformance in the mid-market spend management…

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

    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.

    NVIDIA Nemotron Nano 9B V2: Sally has 1 sister. Explanation: Sally has 3 brothers, so the family includes at least 4 children (Sally + 3 brothers). Each brother has 2 sisters. Since Sally is one of them, there must be 1 additional sister in the family. Thus, Sally has 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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Price and specs

Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer, bigger context window. NVIDIA Nemotron Nano 9B V2 costs 25x less per token.

Inkling and NVIDIA Nemotron Nano 9B V2 compared across 54 shared prompts
SpecInklingNVIDIA Nemotron Nano 9B V2
Input price$1/M tokens$0.04/M tokens
Output price$4.05/M tokens$0.16/M tokens
Context window1.0M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)Yes (1 provider)No
ReleasedJul 2026Sep 2025
At 10M a month$10.00$10.00$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it2 hosts, cheapest first
Inkling2 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.95 in·$4.05 out·524k·100% up
  • TTogether$1.00 in·$4.05 out·524k·96% up
NVIDIA Nemotron Nano 9B V2

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between Inkling and NVIDIA Nemotron Nano 9B V2?

Inkling is developed by Thinking Machines while NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA. Inkling has a 1.0M token context window vs NVIDIA Nemotron Nano 9B V2's 131K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Inkling or NVIDIA Nemotron Nano 9B V2?

It depends on your use case. Inkling and NVIDIA Nemotron Nano 9B V2 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.

How much does Inkling cost compared to NVIDIA Nemotron Nano 9B V2?

Inkling costs $1/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $0.96/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 Inkling and NVIDIA Nemotron Nano 9B V2 on Rival?

This page shows a side-by-side comparison of Inkling and NVIDIA Nemotron Nano 9B V2 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

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