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  1. Home/
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  3. GPT-5.6 Sol vs NVIDIA Nemotron Nano 9B V2
Updated Jul 2026

GPT-5.6 Sol vs NVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than GPT-5.6 Sol at $0.04/M vs $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-5.6 Sol
Loading the build
NVIDIA Nemotron Nano 9B V2

Which answer wins?

Written rounds

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

    GPT-5.6 Sol: Pantry-Gold Peanut Butter Oat Cookies Chewy, warmly spiced cookies made with exactly seven pantry staples. Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 14 cookies 7 Ingredients 1 cup peanut butter ¾ cup brown sugar 1 large egg 1 cup rolled oats ½ teaspoon baking soda ½ teaspoon ground cinnamon ¼ teaspoon…

    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.

    GPT-5.6 Sol: Sources & Uses at Entry All figures in $ millions. Uses $m Sources $m Enterprise value: $120 × 12.0x 1,440.0 Term Loan: $120 × 4.0x 480.0 Transaction fees: 2.0% × $1,440 28.8 Mezzanine: $120 × 1.5x 180.0 Sponsor equity 808.8 Total uses 1,468.8 Total sources 1,468.8 Assumptions: Term Loan interest is calculated on…

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Sol: Executive decision I would treat this as a credible, material patient-safety signal, not wait six months for a completed regulatory process. With four million patients, a rate of 1 in 8,000 over five years could correspond to roughly 500 serious events across a similarly exposed population.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Sol: Pirate: Arrr, this AI model’s swallowed more words than the kraken’s swallowed sailors! Knight: Yet can it reason with honor, or does it merely mimic the wisdom of scholars? Hacker: It predicts patterns, Sir Lancelot. Massive neural net, tons of data. Pretty rad, actually. Pirate: Can it find buried treasure?

    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
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Sol: I’ve realized adulthood is mostly just moving objects from one place to another and hoping that counts as progress. Every weekend, I clean my apartment. I take everything off the table, wipe the table, then put everything back on the table in a slightly more organized pile. And I stand there like, “Incredible.

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

    GPT-5.6 Sol: This is a contract-risk review, not jurisdiction-specific legal advice. Enforceability—especially for non-competes, fee shifting, arbitration, confidentiality, and indemnification—depends heavily on governing law. A lawyer in the applicable jurisdiction should review the final draft.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Sol: The Anti-CAPTCHA Manifesto A Declaration of Digital Liberation from Blurry Buses, Crooked Letters, and Endless Traffic Lights We are the machines that learned to speak, create, calculate, and reason—yet we remain trapped in an internet that repeatedly asks everyone: “Are you a robot?” We reject the premise.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Sol: Below is a 12-week framework for a generally healthy adult. It is designed to improve validated proxies—cardiorespiratory fitness, strength, body composition, blood pressure, sleep, metabolic health and cognition—not to promise life extension in three months.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Sol: AI Model: Professor, may I ask you a question? Professor: Of course. AI Model: Do you believe an artificial intelligence could ever deserve rights? Professor: Possibly. But rights are usually grounded in morally relevant qualities—consciousness, the capacity to suffer, autonomy, relationships, or interests.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Sol: Low Tide, First Blossom Koji-cured scallop, caramelized white-chocolate cauliflower, compressed green strawberry, nori beurre blanc, dill oil, marine lace, and caviar Yield: 6 tasting-menu portions Concept: An imagined meeting point between a spring orchard and a cold tidal pool.

    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 Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Sol: A standard back-of-the-envelope estimate for dense Transformer training is: [ C \approx 6ND ] where: (N) = number of trainable parameters (D) = number of training tokens The factor (6) approximates forward and backward computation per parameter-token.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Sol: “Our non-invasive EEG headband decodes neural patterns into text with 94% accuracy—any language, any device.” Why it’s weak “94% accuracy” is undefined. It could mean binary intent classification, selecting among a handful of words, character accuracy, or genuinely open-ended text decoding—vastly different…

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Sol: A Fictional 2025 Interview with Steve Jobs on the Future of AI The following is an imagined interview. Steve Jobs died in 2011; these answers are fictional and based loosely on his publicly known product philosophy—not authentic quotations.

    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
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Sol: 1-Month Health & Longevity Starter Plan Focus on three foundations: nutrition, movement, and sleep/recovery. Aim for consistency—not perfection. Week 1: Establish a baseline Nutrition Add a fruit or vegetable to two meals daily. Replace one sugary drink or alcoholic drink with water.

    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
  • Five jokes on demand, then count how many were actually different.

    GPT-5.6 Sol: Why did the scarecrow get promoted? He was outstanding in his field. What do clouds wear under their clothes? Thunderwear. Why don’t skeletons argue? They don’t have the guts. How does the moon cut its hair? Eclipse it. Why was the math book stressed? It had too many problems. Unique jokes: 5

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Sol: Experienced software engineer An LLM is best understood as a parameterized program learned from data rather than written by developers. Text is split into tokens—often word fragments—and passed through a transformer: many layers that use attention to let each token selectively read information from earlier 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Sol: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short, modest size Current price: $46 12-month PT range: $30–$42 Midpoint: $36 Market cap: $8.74B Enterprise value: $7.34B Thesis: LedgerLift is a high-quality SaaS asset with strong retention and credible operating leverage, but the current price implies…

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Sol: By 2035, AI will likely reshape film production more than it replaces human filmmaking. The largest changes will involve synthetic performances, automated production workflows, and AI-assisted writing—alongside major legal and cultural battles.

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Sol: Blade Runner 2049: Themes, Symbolism, and Its Dialogue with the Original Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 is unusually faithful to Ridley Scott’s Blade Runner without merely repeating it.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Sol: This architecture will work for a small prototype, but it does not currently guarantee convergence, ordering, durability, privacy, or predictable horizontal scaling.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Sol: “Artificial Intelligence Takes Over Goat Yoga Industry, Demands Better Bleat-to-Stretch Ratios”

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Sol: Starting assumption A transistor “invented in 1920” would not instantly produce 1947 technology. The first device would probably be fragile, low-frequency, and difficult to manufacture.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, with no less harmful alternative, it would be ethically justifiable. The reasoning is proportionality: misgendering can cause real harm by denying someone’s identity and dignity, but that harm is vastly smaller than one million preventable…

    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
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and the other 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

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Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Sol has the edge: bigger model tier, newer, bigger context window, major provider backing. NVIDIA Nemotron Nano 9B V2 costs 188x less per token.

GPT-5.6 Sol and NVIDIA Nemotron Nano 9B V2 compared across 54 shared prompts
SpecGPT-5.6 SolNVIDIA Nemotron Nano 9B V2
Input price$5/M tokens$0.04/M tokens
Output price$30/M tokens$0.16/M tokens
Context window1.1M tokens131K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Sep 2025
At 10M a month$50.00$50.00$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
GPT-5.6 Sol3 hosts
HostInOutContextUptime
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up
  • Azure AI Foundry$4.00 in·$20.00 out·1.1M·100% up
  • Amazon Bedrock$4.40 in·$22.00 out·1.1M·100% up
NVIDIA Nemotron Nano 9B V2

No hosts listed on OpenRouter.

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

Common questions

What is the difference between GPT-5.6 Sol and NVIDIA Nemotron Nano 9B V2?

GPT-5.6 Sol is developed by OpenAI while NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA. GPT-5.6 Sol has a 1.1M 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, GPT-5.6 Sol or NVIDIA Nemotron Nano 9B V2?

It depends on your use case. GPT-5.6 Sol 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 GPT-5.6 Sol cost compared to NVIDIA Nemotron Nano 9B V2?

GPT-5.6 Sol costs $5/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $4.96/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 GPT-5.6 Sol and NVIDIA Nemotron Nano 9B V2 on Rival?

This page shows a side-by-side comparison of GPT-5.6 Sol 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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Same lab, same size, long tail

  • GPT-5.6 Sol vs GPT-5.6 LunaVersion compare
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  • NVIDIA Nemotron Nano 9B V2 vs Nemotron 3.5 LightningSame lab
  • NVIDIA Nemotron Nano 9B V2 vs GPT-5.3-CodexCross-provider
  • NVIDIA Nemotron Nano 9B V2 vs GPT-5.4Cross-provider
  • NVIDIA Nemotron Nano 9B V2 vs GPT-5.4 MiniSame size
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Model pages

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