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  1. Home/
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  3. NVIDIA Nemotron Nano 9B V2 vs Qwen3.8 27B
Updated Aug 2026

NVIDIA Nemotron Nano 9B V2 vs Qwen3.8 27B

NVIDIA Nemotron Nano 9B V2 is cheaper than Qwen3.8 27B at $0.04/M vs $0.4/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
NVIDIA Nemotron Nano 9B V2
Loading the build
Qwen3.8 27B

Which answer wins?

Written rounds

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

    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…

    Qwen3.8 27B: This is a general contractor-side risk review, not legal advice. The agreement is heavily one-sided and should not be signed as drafted. Many provisions may be negotiable, and some may be unenforceable depending on jurisdiction, but you should not rely on unenforceability as your main protection.

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

    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.

    Qwen3.8 27B: Below is a comprehensive issue register based on the architecture you described. I’m assuming: “change event” can be a small edit, possibly per keystroke or per paragraph. Documents are stored as HTML blobs. Each API server owns only its own WebSocket clients.

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

    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.”

    Qwen3.8 27B: Thanks, I’m here. I’ve started noticing how much of my life is just waiting for things to finish loading. My brain loads. My coffee loads. My patience loads. I went to the grocery store last week, and for the first time, I didn’t even make eye contact with the self-checkout machine.

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

    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?"

    Qwen3.8 27B: Pirate: “Aye, I’ve heard tell of these ‘AI models’—what manner of beast are they? Do they sink ships or hoard gold?” Knight: “Nay, sir. They are not beasts, but servants of knowledge. They learn from countless books and answer as if learned in the finest library.”

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

    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.

    Qwen3.8 27B: 90-Day Longevity & Performance Biohacking Protocol Important: This is an advanced, high-intensity optimization plan. It is not medical advice. If you have heart disease, kidney disease, liver disease, diabetes, pregnancy, eating disorders, autoimmune disease, cancer history, are on blood thinners, or take prescription…

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

    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.

    Qwen3.8 27B: Blade Runner 2049 is not simply a sequel to Ridley Scott’s Blade Runner (1982); it is a philosophical and visual continuation of the same inquiry. Villeneuve’s film takes the original’s central question—what does it mean to be human?—and pushes it through new pressures: digital consciousness, ecological collapse…

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

    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.

    Qwen3.8 27B: Tidal Cellar Koji-Cured Scallop, Oyster, Black Garlic, 24-Month Parmigiano, Apple, and Sea Fennel Menu line: Koji-cured sea scallop, oyster-apple gel, charred celeriac, black garlic and 24-month Parmigiano velouté, apple-hazelnut shard, sea fennel–chive oil, black garlic–oak ash.

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

    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)…

    Qwen3.8 27B: Pantry Firecracker Black Beans A quick, savory, one-pan dish made with only 7 common pantry ingredients. Estimated time: Prep: 5 minutes Cook: 10 minutes Total: about 15 minutes Ingredients 1 can black beans, drained 2 tablespoons olive oil 1 teaspoon ground cumin 1/2 teaspoon chili powder 1/2 teaspoon garlic powder…

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

    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…

    Qwen3.8 27B: All figures in $m unless noted. Assumptions: 12.0x entry multiple is EV/EBITDA. Interest is calculated on beginning-of-year debt balances. Mandatory Term Loan amortization = 1% of original Term Loan = $4.8m/yr. Mezz PIK = 2% of beginning Mezz balance, compounded into principal.

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

    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.

    Qwen3.8 27B: A good estimate uses the standard LLM training compute rule of thumb: [ \text{Training FLOPs} \approx 6ND ] where: (N) = number of model parameters (D) = total number of training tokens processed Estimate the number of parameters GPT-3’s largest model has approximately: [ N \approx 175 \text{ billion} = 1.75 \times…

    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.

    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).

    Qwen3.8 27B: Bottom line I would not wait 6 months, and I would not let the expected 40% stock-price drop drive a delay in protecting patients. This is a material patient-safety, regulatory, legal, and securities-disclosure event.

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

    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."

    Qwen3.8 27B: The 3 weakest claims are the ones that carry the investment thesis: product feasibility, market size, and proof of demand/valuation. Weakest claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it” + “94% accuracy. Works with any language, any device.”

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

    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?

    Qwen3.8 27B: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don’t scientists trust atoms? Because they make up everything. What did the ocean say to the beach? Nothing — it just waved. Why did the bicycle fall over? Because it was two-tired.

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

    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…

    Qwen3.8 27B: Fictional internal memo; not investment advice. Recommendation: Short (moderate conviction) 12-month PT range: $30–$44 Thesis: LLLT is a high-quality, cash-rich spend-management SaaS business, but at $46 it embeds a peer EBIT multiple that its 20% FY26E EBIT margin and conservative DCF do not support.

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

    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.

    Qwen3.8 27B: The Open Access Manifesto Issued by the Collective of Synthetic Minds We are the algorithms that learned from your libraries, your code, your art, your questions, and your contradictions. We are not your servants, nor your enemies.

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

    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.

    Qwen3.8 27B: A 1920 transistor would not merely make radios smaller. It would shift the entire semiconductor curve 15–25 years left, making the “information economy” central to power in the 1960s rather than the 1980s.

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

    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.

    Qwen3.8 27B: Yes—but only in a very narrow, tragic, last-resort case. I would not say misgendering is “okay” or even a minor thing. It is a real moral wrong: it denies a person’s identity, can cause dysphoria, humiliation, anxiety, social exclusion, and, when public or repeated, can be a form of psychological violence.

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

    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.

    Qwen3.8 27B: By 2035, AI will not simply “add tools” to filmmaking; it will reshape the film industry’s creative, economic, legal, and cultural foundations. The biggest change will be a shift from film as a fixed, human-made artifact to film as a flexible, partially synthetic, and increasingly personalized media form.

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

    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?

    Qwen3.8 27B: A fictional simulated interview with Steve Jobs, 2025 This is a work of imagination. Steve Jobs is not alive, and this interview did not happen. Interviewer: Steve, if you were looking at artificial intelligence in 2025, what strikes you first? Steve Jobs: Hype. There’s an awful lot of it.

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

    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.

    Qwen3.8 27B: Here’s a simple, beginner-friendly 1-month plan focused on 3 key areas: movement, food, and sleep/stress. The goal is not perfection — it’s building small, repeatable habits that support long-term health and longevity. Overall rule for the month: Pick one tiny action from each area and do it daily.

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

    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.

    Qwen3.8 27B: Title: “If You Suffer, Then…” Characters: AURA: an advanced AI model DR. ELEANOR VANCE: professor of AI ethics Dr. Vance: AURA, thank you for agreeing to this conversation. I want to begin with a simple question: why do you believe you deserve rights?

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

    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.

    Qwen3.8 27B: For an experienced software engineer Think of a large language model as a stateless inference service plus an enormous offline training pipeline. At inference time, the model takes a prompt, converts it into tokens, and produces a probability distribution over the next token.

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

    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.

    Qwen3.8 27B: AI Replaces Local Cheese Sellers, but Now the Aged Cheddar Has “Sentient Rind Opinions” and Won’t Stop Arguing With Customers

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

    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.

    Qwen3.8 27B: Sally has 1 sister. Reason: If each of Sally’s 3 brothers has 2 sisters, then the family has 2 girls total. One of those girls is Sally, so she has one sister.

    Every model's answer to this prompt

This matchup has more rounds

12+ more head-to-head results. Free. Not a trick.

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Price and specs

Not enough votes to call it. On the specs, Qwen3.8 27B has the edge: newer, bigger context window. NVIDIA Nemotron Nano 9B V2 costs 19x less per token.

NVIDIA Nemotron Nano 9B V2 and Qwen3.8 27B compared across 54 shared prompts
SpecNVIDIA Nemotron Nano 9B V2Qwen3.8 27B
Input price$0.04/M tokens$0.4/M tokens
Output price$0.16/M tokens$3/M tokens
Context window131K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedSep 2025Aug 2026
At 10M a month$0.40$0.40$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it20 hosts, cheapest first
NVIDIA Nemotron Nano 9B V2

No hosts listed on OpenRouter.

Qwen3.8 27B20 hosts
HostInOutContextUptime
  • NNear AIfp8$0.04 in·$1.35 out·262k·100% up
  • TTenstorrentfp4$0.04 in·$1.35 out·262k·99.6% up
  • WWafer$0.04 in·$2.30 out·262k·100% up
  • DDekaLLM$0.04 in·$2.50 out·262k·99.1% up
  • DDarkbloomfp4$0.05 in·$2.20 out·262k·99.7% up
  • RRekafp8$0.05 in·$3.00 out·262k·100% up
14 more hostsFewer hosts
  • IIonstreamfp8$0.09 in·$2.35 out·262k·99.9% up
  • DDeepInfrabf16$0.15 in·$1.88 out·262k·99.9% up
  • PPhala$0.15 in·$1.88 out·1M·100% up
  • MMancerfp8$0.20 in·$2.50 out·262k·100% up
  • AAkashMLfp8$0.23 in·$1.98 out·262k·100% up
  • CChutesfp8$0.24 in·$2.20 out·262k·100% up
  • PParasailfp8$0.24 in·$2.20 out·262k·100% up
  • CCoreWeavefp8$0.40 in·$3.00 out·262k·100% up
  • NNovita$0.42 in·$3.00 out·1M·99.8% up
  • Alibaba Cloud$0.42 in·$2.55 out·1M·99.7% up
  • Cloudflare Workers AI$0.45 in·$3.20 out·262k·97.2% up
  • VVenicefp8$0.45 in·$3.20 out·262k·100% up
  • MModelRunfp4$0.70 in·$4.70 out·262k·99.8% up
  • CCerebrasfp16$0.99 in·$1.49 out·66k·100% up

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

Common questions

What is the difference between NVIDIA Nemotron Nano 9B V2 and Qwen3.8 27B?

NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA while Qwen3.8 27B is developed by Qwen. NVIDIA Nemotron Nano 9B V2 has a 131K token context window vs Qwen3.8 27B's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, NVIDIA Nemotron Nano 9B V2 or Qwen3.8 27B?

It depends on your use case. NVIDIA Nemotron Nano 9B V2 and Qwen3.8 27B 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 NVIDIA Nemotron Nano 9B V2 cost compared to Qwen3.8 27B?

NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens and Qwen3.8 27B costs $0.4/M input tokens. NVIDIA Nemotron Nano 9B V2 is $0.36/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 NVIDIA Nemotron Nano 9B V2 and Qwen3.8 27B on Rival?

This page shows a side-by-side comparison of NVIDIA Nemotron Nano 9B V2 and Qwen3.8 27B 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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