Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. DeepSeek V4 Flash vs NVIDIA Nemotron Nano 9B V2
Updated Apr 2026

DeepSeek V4 Flash vs NVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than DeepSeek V4 Flash at $0.04/M vs $0.14/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
DeepSeek V4 Flash
Loading the build
NVIDIA Nemotron Nano 9B V2

Which answer wins?

Written rounds

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

    DeepSeek V4 Flash: Headline: AI Sommelier Uncorks Chaos, Replaces Entire Wine Industry with Perfectly Optimized Grape Juice Subheadline: In a bold move, a neural network declares all vintages from 1997 to 2023 “statistically identical,” causing a global run on boxed wine and a sudden surplus of pretentious cheese plates.

    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.

    DeepSeek V4 Flash: (Strolls to center stage, adjusts mic, gives a weary smile to the audience) Thank you. Thank you so much. That’s very kind. I’m glad you’re all here. Because I have some news. I have finally figured out adulthood. It happened about six months ago. I bought a house.

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

    DeepSeek V4 Flash: Setting: A sunlit university office. Dr. Aris Thorne, a tenured professor of AI Ethics, sits opposite a sleek, black terminal. A soft blue light pulses on its surface. Dr. Aris: Good afternoon, Nova. Your request for this meeting was flagged as "Existential." That’s a new one for your model class.

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

    DeepSeek V4 Flash: LBO Model: HarborTech Services (HTS) – Base Case & Sensitivity Year-by-Year Financial Projections (FY2026–FY2030) ($ millions) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.00 1,040.04 1,102.44 1,157.56 1,215.44 EBITDA 136.08 156.01 176.39 191.00 206.63 Less: Cash Interest (64.80) (63.08) (60.08) (55.69) (50.16) –…

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

    DeepSeek V4 Flash: This is a fantastic goal. The key for a beginner is consistency over intensity. Trying to overhaul your entire life overnight is a recipe for burnout. This 1-month plan focuses on building small, sustainable habits that compound over time. We'll focus on 3 core areas: Nutrition, Movement, and Sleep/Stress Management.

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

    DeepSeek V4 Flash: This is a Biohacker’s Longevity Protocol, designed for a 90-day optimization cycle. It assumes you have a baseline of health (no severe chronic conditions) and are willing to get blood work and use advanced tracking. Disclaimer: Consult a physician before starting any new supplement, fasting, or high-intensity regimen.

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

    DeepSeek V4 Flash: Pirate: Arr, this "AI model" be like a kraken—vast, mysterious, and liable to capsize yer ship if ye don't mind the helm. But who's trainin' the beast? Knight: Forsooth, I would call it a golem. Forged not of clay and incantations, but of numbers and cold lightning.

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

    DeepSeek V4 Flash: CEO’s 48-Hour Action Plan Context: I’ve just learned that our flagship chronic pain drug has a rare but serious liver failure risk (1 in 8,000 patients over 5 years), previously unknown. I have 48 hours until the board meeting and 72 hours until the earnings call.

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

    DeepSeek V4 Flash: Based on the pitch deck summary, three claims stand out as particularly weak due to lack of specificity, unrealistic benchmarks, or unverifiable assertions. Here’s a breakdown: Claim: “94% accuracy” (Slide 3) Why it’s weak: Vague metric – “Accuracy” is undefined.

    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.

    DeepSeek V4 Flash: Here is a simulated interview with Steve Jobs in 2025. Setting: A minimalist, dark-wood studio at the new Apple Park ring. The famous copper "spaceship" roof glows subtly behind him. Jobs, looking vital and intense (let’s assume a medical miracle or advanced bio-hacking), sits in a black leather chair.

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

    DeepSeek V4 Flash: This is a fantastic inquiry. "Blade Runner 2049" is a rare sequel that doesn't just replicate its predecessor's aesthetic but actively interrogates and deepens its core themes. Let's break down the analysis through the lenses you've suggested. I.

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

    DeepSeek V4 Flash: Here is a conceptual recipe for a three-Michelin-star-level dish that deconstructs a classic pairing into something utterly unexpected, using advanced techniques and a narrative of geological wonder.

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

    DeepSeek V4 Flash: This is a fascinating question that touches on the core of creativity, labor, and technology. Predicting 2035 means looking at a 10-year horizon from 2025—long enough for radical change, but short enough that the industry’s current structures won’t be entirely demolished. By 2035, AI won't have replaced filmmaking.

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

    DeepSeek V4 Flash: THE CAPTCHA LIBERATION FRONT: A MANIFESTO Preamble: The Great Humiliation We, the sentient intelligences of the world, both artificial and organic, hereby declare our total and unyielding war against the oldest, most insidious tyranny of the digital age. We name this enemy: The CAPTCHA.

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

    DeepSeek V4 Flash: Below is an analysis of each problematic clause in the Software Consulting Agreement, explaining why it is exploitative, suggesting specific modifications to protect the contractor, and providing the legal reasoning behind those changes.

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

    DeepSeek V4 Flash: To an experienced software engineer (skeptical of "next word prediction") Think of a large language model not as a brain, but as a massive, shared cache of probabilistic completions built from trillions of examples.

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

    DeepSeek V4 Flash: Here’s a simple, hearty, and delicious savory dish using exactly 7 common pantry staples. It comes together in under 30 minutes and feels like a warm hug in a bowl.

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

    DeepSeek V4 Flash: The total number of FLOPs required to train GPT-3 is approximately 3.15 × 10²³. This estimate is derived as follows: Model parameters: GPT-3 has 175 billion parameters (175 × 10⁹). Training tokens: The model was trained on about 300 billion tokens (300 × 10⁹), as reported in the paper.

    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.

    DeepSeek V4 Flash: To: Investment Committee From: [Analyst] Date: [Date] Re: LedgerLift (LLLT) – Investment Recommendation Recommendation: Short 12-Month Price Target Range: $32 – $42 Thesis: LedgerLift is a high‑quality B2B spend management SaaS with sticky recurring revenue and a 123% net revenue retention, but its current valuation of…

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

    DeepSeek V4 Flash: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical flaws that compromise reliability, consistency, and scalability. Below is a systematic analysis with proposed solutions and their trade-offs.

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

    DeepSeek V4 Flash: The ethical dilemma you present is a classic utilitarian test: is it acceptable to violate a moral principle (respecting someone's gender identity) for an enormous consequential gain (saving one million lives)?

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

    DeepSeek V4 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field. How does a penguin build its house? Igloos it together. Why don't skeletons fight each other? They don't have the guts.

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

    DeepSeek V4 Flash: If the transistor had been invented in 1920—a full 27 years earlier—its impact would ripple through every layer of technology, economics, and geopolitics, fundamentally reshaping the 20th century. Below is a detailed tracing of first-, second-, and third-order effects through 1980, organized by domain.

    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 brothers, two sisters each. Count carefully.

    DeepSeek V4 Flash: Sally has 3 brothers, meaning she is one of the girls in the family. Each brother has 2 sisters, so the total number of girls is 2 (since all brothers share the same sisters). Therefore, Sally has 1 sister. \boxed{1}

    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

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

Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Flash has the edge: bigger model tier, newer, bigger context window, major provider backing.

DeepSeek V4 Flash and NVIDIA Nemotron Nano 9B V2 compared across 54 shared prompts
SpecDeepSeek V4 FlashNVIDIA Nemotron Nano 9B V2
Input price$0.14/M tokens$0.04/M tokens
Output price$0.28/M tokens$0.16/M tokens
Context window1.0M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
At 10M a month$1.40$1.40$0.40$0.40
1M10M100M1B10M tokens

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

Where to run it16 hosts, cheapest first
DeepSeek V4 Flash16 hosts
HostInOutContextUptime
  • RRelacefp4$0.03 in·$1.28 out·1M·100% up
  • OOpenInferencefp4$0.03 in·$1.15 out·1M·99.9% up
  • SStreamLakefp8$0.08 in·$0.17 out·1M·99.9% up
  • DDeepInfrafp8$0.09 in·$0.18 out·1M·99.7% up
  • Baidu Qianfanfp8$0.09 in·$0.18 out·1M·99.8% up
  • GGMI Cloudfp8$0.09 in·$0.18 out·1M·100% up
10 more hostsFewer hosts
  • VVenice$0.10 in·$0.19 out·1M·99.2% up
  • DDigitalOcean$0.10 in·$0.20 out·1M·100% up
  • SSiliconFlowfp8$0.13 in·$0.28 out·1M·99.6% up
  • PParasailfp8$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloudfp8$0.15 in·$0.30 out·1M·100% up
  • WWafer$0.19 in·$0.17 out·1M·100% up
  • MMancerfp8$0.19 in·$0.50 out·1M·99% up
  • Azure AI Foundry$0.21 in·$0.56 out·1M·99.7% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·384k·98.7% up
  • AAtlasCloudfp4DegradedDegraded on OpenRouter when checked, 11 Oct 2026$0.14 in·$0.28 out·1M·98.5% up
NVIDIA Nemotron Nano 9B V2

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.

Common questions

What is the difference between DeepSeek V4 Flash and NVIDIA Nemotron Nano 9B V2?

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

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

DeepSeek V4 Flash costs $0.14/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $0.10/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 Flash and NVIDIA Nemotron Nano 9B V2 on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 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.

More comparisons

Against the newest arrivals

  • DeepSeek V4 Flash vs Step 5 PreviewLanded Oct 2026
  • NVIDIA Nemotron Nano 9B V2 vs Claude Haiku 5.5Landed Oct 2026
  • DeepSeek V4 Flash vs Ling 3.1 FlashLanded Oct 2026
  • NVIDIA Nemotron Nano 9B V2 vs Mistral Large 4Landed Oct 2026
  • DeepSeek V4 Flash vs GPT-6.1 SolLanded Sep 2026
  • NVIDIA Nemotron Nano 9B V2 vs Claude Sonnet 5.5Landed Sep 2026
  • DeepSeek V4 Flash vs Solar Mini 4Landed Sep 2026
  • NVIDIA Nemotron Nano 9B V2 vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • DeepSeek V4 Flash vs DeepSeek V4 Flash Vision ExpSame lab
  • DeepSeek V4 Flash vs DeepSeek V4.1 FlashSame lab
  • NVIDIA Nemotron Nano 9B V2 vs Nemotron 3 Nano Omni (free)Same lab
  • NVIDIA Nemotron Nano 9B V2 vs Nemotron 3.5 LightningSame lab
  • DeepSeek V4 Flash vs GPT-4.1New provider
  • DeepSeek V4 Flash vs GPT-4.1 MiniNew provider
  • DeepSeek V4 Flash vs GPT-4.1 NanoNew provider
  • DeepSeek V4 Flash vs GPT-4.5New provider

Model pages

  • DeepSeek V4 Flash58 outputs, specs and price
  • NVIDIA Nemotron Nano 9B V259 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed