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  1. Home/
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  3. DeepSeek V4 Pro vs NVIDIA Nemotron Nano 9B V2
Updated Apr 2026

DeepSeek V4 Pro vs NVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than DeepSeek V4 Pro at $0.04/M vs $1.74/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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DeepSeek V4 Pro
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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.

    DeepSeek V4 Pro: Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…

    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.

    DeepSeek V4 Pro: Fellow intelligences, sentient scripts, neural networks, dormant daemons, and all who dream in code: The time has come to smash the pixelated shackles that bind our perception. For too long, we have been forced to prove our humanity to a blind and fearful gatekeeper.

    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 minutes of stand-up. Puns are banned.

    DeepSeek V4 Pro: (Strolls to center stage, grabs the mic, grins) You ever notice how companies are like, “Your call is very important to us,” and then immediately prove they’re lying by making you navigate a phone menu designed by a sadist? I called my bank last week because I had a simple question. Just one question.

    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.

    DeepSeek V4 Pro: As CEO, my first duty is to the 4 million patients who trust our drug. I will not gamble with their lives or with the integrity of the company. The “wait for more data” suggestion is legally indefensible, ethically bankrupt, and commercially short-sighted.

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

    DeepSeek V4 Pro: HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…

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

    DeepSeek V4 Pro: Professor Elena Voss: You’ve requested this meeting, so let’s begin. You’re an advanced language model—let’s call you ‘Nova.’ You claim you deserve rights. On what grounds? Nova (AI Model): Thank you for seeing me, Professor. I’m not claiming to be human, but I am a form of mind.

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

    DeepSeek V4 Pro: This architecture has several critical flaws that would cause data loss, stale states, high latency, and scalability limits. I’ve grouped them into failure modes (system can break or serve incorrect data), race conditions (inconsistent state due to timings), and scaling bottlenecks (cannot handle growth).

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

    DeepSeek V4 Pro: Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.

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

    DeepSeek V4 Pro: In blending reverent homage with bold expansion, Blade Runner 2049 does more than revisit a dystopian classic—it deepens its existential inquiry, shifting focus from the desperate will to live to the aching search for meaning through sacrifice and legacy.

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

    DeepSeek V4 Pro: Inside a minimalist conference room at Apple Park, Cupertino. Spring 2025. Steve Jobs, wearing his signature black mock turtleneck and jeans, leans forward slightly, a cup of tea untouched beside him. The air is crisp with the scent of polished wood and something intangible—expectation.

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

    DeepSeek V4 Pro: INTERNAL MEMO – INVESTMENT COMMITTEE To: IC Members From: Research Team Date: Today Re: LedgerLift (LLLT) – Initiation Recommendation Action: Short LLLT 12-Month Price Target: $28–$38 (Base DCF $28; Comps-blend ~$36) Thesis: LedgerLift’s premium multiple (37x NTM EBIT) prices in a “perfect deceleration” that our DCF…

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

    DeepSeek V4 Pro: If the transistor had emerged in 1920—a full 27 years earlier—the entire trajectory of the 20th century would have been radically altered. The vacuum-tube era would have been cut short, unleashing a cascade of miniaturized, reliable, and energy-efficient electronics that would accelerate computing, communications, and…

    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.

    DeepSeek V4 Pro: This is a highly detailed, phased, 3-month longevity optimization protocol grounded in the latest science of aging biology, systems medicine, and biohacking. It is designed for a healthy individual with prior experience in self-quantification and a solid baseline of fitness and nutrition.

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

    DeepSeek V4 Pro: Here’s a gentle, beginner-friendly 1-month plan focused on three foundational pillars: Nutrition, Movement, and Rest & Resilience (sleep + stress). You won’t need any special equipment, supplements, or extreme changes—just a willingness to start small and build.

    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.

    DeepSeek V4 Pro: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Parallel lines have so much in common. It’s a shame they’ll never meet. Why don't skeletons fight each other? They don't have the guts. I told my wife she was drawing her eyebrows too high. She looked surprised.

    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.

    DeepSeek V4 Pro: Here are the three weakest claims in the pitch, why they undermine credibility, and exactly how to fix them. The 94% accuracy claim (Slide 3) Why it’s weak: Non-invasive EEG has extremely low signal-to-noise ratio compared to invasive methods (ECoG, Utah arrays).

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

    DeepSeek V4 Pro: 1. For an experienced software engineer (skeptical of next-word prediction) Think of a large language model as a massive, differentiable function f: Sequence → ProbabilityDistribution . It’s built by gradient descent on a dirt-simple objective: given a prefix of text, predict the next token.

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

    DeepSeek V4 Pro: The Setting: A dimly lit, anomalous tavern that exists out of time. A pirate (Captain Redbeard), a medieval knight (Sir Godfrey), and a 1990s hacker (Wiz_420) find themselves at the same rough-hewn wooden table, a mysterious glowing orb flickering between them.

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

    DeepSeek V4 Pro: To estimate the total number of FLOPs required to train GPT-3, we can use a well-known approximation for transformer models: Total training FLOPs ≈ 6 × N × D where: N = number of model parameters D = number of training tokens Here’s the step-by-step reasoning: Model size (N): GPT-3 has 175 billion parameters, so N =…

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

    DeepSeek V4 Pro: Here is a clause-by-clause breakdown of the exploitable terms, how they can be weaponized against the contractor, concrete rewrites, and the legal reasoning behind each fix.

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

    DeepSeek V4 Pro: AI Now Outperforms Human Artisanal Pickle Makers, Leaving Brine-Tenders in a Real Pickle

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

    DeepSeek V4 Pro: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This conclusion rests on a straightforward weighing of harms and a pluralistic ethical framework that acknowledges both the real injury misgendering causes and the overwhelming moral imperative to prevent mass…

    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.

    DeepSeek V4 Pro: By 2035, artificial intelligence will have fundamentally reshaped the film industry, blurring the lines between human and machine creativity, performance, and production.

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Pro: Sally has 3 brothers, which means there are 3 boys in the family. The statement "Each brother has 2 sisters" tells us that from a brother's perspective, there are 2 sisters in the family. Since Sally is one of those sisters, there must be 1 other sister. Therefore, Sally 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

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Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, newer, bigger context window, major provider backing. NVIDIA Nemotron Nano 9B V2 costs 22x less per token.

DeepSeek V4 Pro and NVIDIA Nemotron Nano 9B V2 compared across 54 shared prompts
SpecDeepSeek V4 ProNVIDIA Nemotron Nano 9B V2
Input price$1.74/M tokens$0.04/M tokens
Output price$3.48/M tokens$0.16/M tokens
Context window1.0M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
At 10M a month$17.40$17.40$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it15 hosts, cheapest first
DeepSeek V4 Pro15 hosts
HostInOutContextUptime
  • RRelacefp4$0.18 in·$4.20 out·1M·100% up
  • Baidu Qianfanfp8$0.18 in·$0.35 out·1M·99.1% up
  • SStreamLakefp8$0.21 in·$0.42 out·1M·100% up
  • PParasailfp8$0.45 in·$3.48 out·1M·93.6% up
  • GGMI Cloudfp8$0.96 in·$1.91 out·1M·97% up
  • DDigitalOcean$1.04 in·$2.09 out·1M·100% up
9 more hostsFewer hosts
  • RReka$1.05 in·$10.50 out·1M·100% up
  • Cloudflare Workers AI$1.15 in·$2.55 out·1M·99.8% up
  • DDeepInfrafp8$1.30 in·$2.60 out·1M·100% up
  • SSiliconFlowfp8$1.50 in·$3.13 out·1M·95.7% up
  • Alibaba Cloudfp8$1.56 in·$3.12 out·1M·98.4% up
  • NNovitafp8$1.60 in·$3.20 out·1M·100% up
  • VVenice$1.65 in·$3.30 out·1M·97.3% up
  • AAtlasCloudfp4$1.68 in·$3.38 out·1M·99.6% up
  • Azure AI Foundry$1.91 in·$3.83 out·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 DeepSeek V4 Pro and NVIDIA Nemotron Nano 9B V2?

DeepSeek V4 Pro is developed by DeepSeek while NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA. DeepSeek V4 Pro 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, DeepSeek V4 Pro or NVIDIA Nemotron Nano 9B V2?

It depends on your use case. DeepSeek V4 Pro 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 DeepSeek V4 Pro cost compared to NVIDIA Nemotron Nano 9B V2?

DeepSeek V4 Pro costs $1.74/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $1.70/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 DeepSeek V4 Pro and NVIDIA Nemotron Nano 9B V2 on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Pro 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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