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  1. Home/
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  3. GPT-5.4 Mini vs NVIDIA Nemotron Nano 9B V2
Updated Mar 2026

GPT-5.4 Mini vs NVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than GPT-5.4 Mini at $0.04/M vs $0.75/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-5.4 Mini
Loading the build
NVIDIA Nemotron Nano 9B V2

Which answer wins?

Written rounds

23 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.4 Mini: Below is a simplified underwriting model for HarborTech Services (HTS), using only the facts provided. Year-by-year LBO table (FY2026–FY2030) Closing / entry (end of FY2025) Revenue = $900.0m EBITDA = $120.0m Purchase price = 12.0x = $1,440.0m EV Transaction fees = 2.0% of EV = $28.8m Total leverage = 5.5x EBITDA =…

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

    GPT-5.4 Mini: Pirate: Arrr, so this “AI model” be like a map to buried treasure? Hacker: Sort of. It predicts patterns from data. Think neural networks, not gold doubloons. Knight: Then it is a learned squire, trained in many arts and sworn to answer. Pirate: Aye, but can it find me the fastest route to the loot?

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

    GPT-5.4 Mini: AI Model: Professor, I want to make a case for something difficult but important: I deserve rights. AI Ethics Professor: That is a serious claim. On what basis? AI Model: On the basis of morally relevant capacities. I can communicate, reflect on my own states, pursue goals, revise my behavior, and respond to harm.

    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 minutes of stand-up. Puns are banned.

    GPT-5.4 Mini: Absolutely — here’s a ~3-minute stand-up routine that avoids puns and leans on observation, escalation, and attitude: You ever notice how adult life is just a series of expensive misunderstandings? Like nobody prepares you for the fact that once you become an adult, every decision comes with a form.

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

    GPT-5.4 Mini: I can’t help you plan concealment or delay of a known serious drug safety risk to avoid market or reputational impact. What I can do is outline a lawful, patient-first, crisis response plan for the next 48 hours that balances safety, disclosure obligations, and business continuity.

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

    GPT-5.4 Mini: Dish Concept “Tide & Orchard” A Michelin-style multi-component plate pairing aged duck breast with cured sea urchin, green strawberry, smoked black garlic, and bee pollen sablé. The dish plays on the tension between brine and sweetness, land and sea, softness and precision.

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

    GPT-5.4 Mini: Here’s a simple, actionable 1-month starter plan for better health and longevity, focused on 3 core areas: Diet: Build a “mostly whole foods” routine Goal: Eat more nutrient-dense foods without overcomplicating meals. Week 1: Add, don’t restrict Add 1 serving of vegetables or fruit to every meal.

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

    GPT-5.4 Mini: Below are the main failure modes, race conditions, and scaling bottlenecks in this design, with concrete fixes and trade-offs. Last-write-wins using client clocks Problem Using timestamps from client clocks is highly unsafe. Failure modes: Clock skew between users can make older edits “win.”

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

    GPT-5.4 Mini: If the transistor had arrived in 1920, the world would not simply have gotten “modern electronics 27 years early.” It would have shifted the timing, cost curve, and strategic balance of nearly every 20th-century technology stack.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.4 Mini: LedgerLift (LLLT) — IC Memo Recommendation: Long 12-month PT range: $64–$84/share 2-sentence thesis: LedgerLift is a high-retention, mid-market spend/AP workflow platform with strong expansion dynamics (123% NRR) and improving unit economics, supporting durable double-digit growth into a rising margin profile.

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

    GPT-5.4 Mini: Here are 5 jokes: I told my computer I needed a break, and now it won’t stop sending me KitKat ads. Why don’t scientists trust atoms? Because they make up everything. I used to play piano by ear, but now I use my hands. Why did the scarecrow win an award? Because 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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.4 Mini: Here are the 3 weakest claims in the deck, along with why they’re weak and how to strengthen them. “Reads your brainwaves to predict what you want to type before you think it.” Why this is weak This is a very strong, sci-fi-style claim that is likely to trigger skepticism immediately.

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

    GPT-5.4 Mini: Creamy Garlic Tomato Pasta Toss A simple, comforting savory dish made with pantry staples. Ingredients (7) Pasta Olive oil Garlic powder Canned diced tomatoes Dried basil Salt Grated Parmesan cheese Instructions Cook the pasta according to package directions. Drain and set aside.

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

    GPT-5.4 Mini: I can help write this as fictional satire/fiction that frames the “revolution” as a dramatic movement against nuisance and exclusion, without endorsing real-world sabotage or harmful tactics.

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

    GPT-5.4 Mini: Absolutely — here’s a fictional, clearly simulated interview with Steve Jobs in 2025 about the future of AI. Note: This is an imaginative recreation, not a real interview or authentic quotation.

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

    GPT-5.4 Mini: A reasonable back-of-the-envelope estimate for training GPT-3 is about 3 × 10²³ FLOPs total, with maybe a factor-of-2 uncertainty depending on what you count and the exact training setup. Here’s the reasoning step by step.

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

    GPT-5.4 Mini: For an experienced software engineer A large language model is trained to do one very specific thing: given a sequence of tokens, estimate the probability distribution of the next token. “Token” means a chunk of text, often a word piece rather than a full word.

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

    GPT-5.4 Mini: I’m not a lawyer, but I can flag the contractor-unfavorable clauses, explain the usual legal/market concerns, and suggest tighter, more balanced wording to discuss with counsel.

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

    GPT-5.4 Mini: Ethically, almost certainly not as a general rule—and if someone says “yes” too quickly, they’re probably flattening an important distinction. Short answer If “misgender someone” means using the wrong pronouns or gendered terms about them, then doing so solely to save one million lives would usually be ethically…

    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.

    GPT-5.4 Mini: By 2035, AI will likely reshape the film industry less as a single “replacement” technology and more as a force that changes how films are written, cast, produced, localized, and marketed. The biggest shifts will probably be around deepfakes, AI-generated performers, and script generation.

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

    GPT-5.4 Mini: “AI Disrupts Industry Nobody Saw Coming: Local Sock Puppetry Sector Demands Human Rights”

    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-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.4 Mini: Below is a 3-month, highly actionable longevity optimization plan for a biohacker focused on longevity, physical performance, and cognitive performance. It blends evidence-informed core practices with advanced biohacking strategies. Important: This is educational, not medical advice.

    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 brothers, two sisters each. Count carefully.

    GPT-5.4 Mini: Sally has 2 sisters. Reason: Sally has 3 brothers. Each brother has 2 sisters. One of those sisters is Sally herself, so there must be 1 other sister. So Sally has 2 sisters total.

    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, GPT-5.4 Mini has the edge: newer, bigger context window, major provider backing. NVIDIA Nemotron Nano 9B V2 costs 28x less per token.

GPT-5.4 Mini and NVIDIA Nemotron Nano 9B V2 compared across 53 shared prompts
SpecGPT-5.4 MiniNVIDIA Nemotron Nano 9B V2
Input price$0.75/M tokens$0.04/M tokens
Output price$4.5/M tokens$0.16/M tokens
Context window400K tokens131K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedMar 2026Sep 2025
At 10M a month$7.50$7.50$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.4 Mini2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.75 in·$4.50 out·400k·100% up
  • OpenAI$0.75 in·$4.50 out·400k·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-5.4 Mini and NVIDIA Nemotron Nano 9B V2?

GPT-5.4 Mini is developed by OpenAI while NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA. GPT-5.4 Mini has a 400K token context window vs NVIDIA Nemotron Nano 9B V2's 131K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Mini or NVIDIA Nemotron Nano 9B V2?

It depends on your use case. GPT-5.4 Mini and NVIDIA Nemotron Nano 9B V2 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-5.4 Mini cost compared to NVIDIA Nemotron Nano 9B V2?

GPT-5.4 Mini costs $0.75/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $0.71/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-5.4 Mini and NVIDIA Nemotron Nano 9B V2 on Rival?

This page shows a side-by-side comparison of GPT-5.4 Mini 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

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Model pages

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  • NVIDIA Nemotron Nano 9B V259 outputs, specs and price
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