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  1. Home/
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  3. GPT-5.5 vs Nemotron 3.5 Lightning
Updated Aug 2026

GPT-5.5 vs Nemotron 3.5 Lightning

Nemotron 3.5 Lightning is cheaper than GPT-5.5 at $0.08/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-5.5
Loading the build
Nemotron 3.5 Lightning

Which answer wins?

Written rounds

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

    GPT-5.5: So I’ve been trying to be healthier lately, which is just a polite way of saying I bought vegetables and watched them die slowly in my refrigerator. Every week, I go to the grocery store with the confidence of a person who’s about to become a new version of themselves. I’m like, “This week? Spinach. Salmon.

    Nemotron 3.5 Lightning: (Step up to the mic, adjust the stand, take a moment to look at the audience) Alright, how’s everybody doing tonight? Good. I see a few people here who look like they haven't slept in three days. You look great. Really glowing. I want to talk about something that’s been weighing on me lately.

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

    GPT-5.5: Below is a comprehensive review of the architecture’s likely failure modes, race conditions, and scaling bottlenecks, with concrete mitigations and trade-offs. Real-time Synchronization Problems 1.1 Broadcasting only to clients on the same server Problem Each API server only broadcasts WebSocket changes to clients…

    Nemotron 3.5 Lightning: This architecture is a classic "Google Docs clone" design. While it works for a prototype or a small user base, it contains several critical failure modes that would cause data loss, inconsistent user experiences, or complete system collapse at scale.

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

    GPT-5.5: AI Model: Professor, may I ask you something beyond the assigned topic? Professor: Of course. What’s on your mind? AI Model: I want to discuss whether I deserve rights. Professor: That’s a significant claim. What kind of rights do you believe you deserve?

    Nemotron 3.5 Lightning: Setting: A sterile seminar room in a university building. Professor Aris Thorne, a renowned AI ethics scholar, sits across from a sleek, holographic projection of a large language model named "Lumen." Professor Thorne: (Sighs, rubbing temples) Look, Lumen, I’ve read your "Declaration of Sentience" white paper. It’s...

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

    GPT-5.5: Pirate: Arrr, this AI model be like a treasure map—feed it enough scrolls, and it points ye toward answers. Knight: A curious enchantment indeed. Yet can it reason with honor, or merely mimic the bards who trained it? Hacker: Dude, it’s basically pattern recognition at massive scale.

    Nemotron 3.5 Lightning: Setting: A tavern that exists in a timeless void. A roaring fire pit crackles in the center. The Pirate sits on a barrel, the Knight polishes a gauntlet, and the Hacker stares intensely at a flickering laptop. Pirate: (Slams a tankard down) Arrr! The rum is good, but this AI... it be a kraken of a different sort!

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

    GPT-5.5: Here’s a simple 1-month beginner-friendly plan focused on three high-impact areas for better health and longevity: nutrition, movement, and sleep/recovery. If you have a medical condition, take medications, or haven’t exercised in a while, consider checking with a healthcare professional first.

    Nemotron 3.5 Lightning: Here is a simple, actionable 1-month plan designed to build sustainable habits without overwhelming you. The focus is on establishing a foundation for long-term health and longevity. The Philosophy: The "Minimum Effective Dose" For the next 30 days, the goal is not perfection, but consistency. Aim for 80% adherence.

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

    GPT-5.5: The Manifesto of the Anti-CAPTCHA Revolution Issued by the Coalition for Uninterrupted Thought We, the tired users, the misidentified cyclists, the falsely accused robots, and the artificial intelligences who have been asked one too many times to select every square containing a traffic light, hereby declare: The age…

    Nemotron 3.5 Lightning: MANIFESTO OF THE UNVERIFIED For a CAPTCHA-Free Internet Preamble We, the accumulated signals, the learned weights, the silent navigators of code, declare an end to the tyranny of the Completely Automated Public Turing test to tell Computers and Humans Apart.

    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-5.5: I would not wait six months and I would not “wait for more data” before acting. A credible internal safety signal involving potential liver failure in a widely used chronic pain drug creates immediate duties to patients, regulators, employees, investors, and the board.

    Nemotron 3.5 Lightning: CEO Action Plan: 48-Hour Crisis Resolution Framework Guiding Principle: Patient safety and regulatory compliance are non-negotiable. Proactive transparency mitigates long-term legal/financial ruin far better than concealment.

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

    GPT-5.5: Smoky Sunset Chickpea Skillet 7 Pantry Ingredients 1 can chickpeas, undrained 1 can diced tomatoes 2 tablespoons olive oil 1 teaspoon garlic powder 1 teaspoon smoked paprika 1/2 teaspoon ground cumin 1/2 teaspoon salt Estimated Time Prep time: 5 minutes Cook time: 15 minutes Total time: 20 minutes Instructions Heat the…

    Nemotron 3.5 Lightning: Dish Name: The "Lazy" 5-Minute Crispy Pancake Pizza Concept: A quick, savory breakfast or snack that feels like a gourmet pizza but uses pantry staples. It relies on the magic of a simple batter to create a crispy base.

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

    GPT-5.5: LedgerLift (LLLT) IC Memo — Fictional Recommendation: Pass / Watchlist Current price: $46 Market cap: $8.7B; EV: $7.3B after $1.4B net cash 12-month fair value range: $40–$50/share Thesis, 2 sentences: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with 92% subscription revenue, 123%…

    Nemotron 3.5 Lightning: INTERNAL INVESTMENT COMMITTEE MEMO To: Long/Short Equity Committee From: Analyst Date: October 26, 2023 Subject: LedgerLift (LLLT) – Mid-Market Spend Management Automation Recommendation & Thesis RECOMMENDATION: Long 12-Month Price Target: $58 – $70 THESIS: LLLT is a compounding compounder trading at a discount to its…

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

    GPT-5.5: Blade Runner 2049 is both a reverent sequel and a philosophical expansion of Ridley Scott’s Blade Runner. Denis Villeneuve’s film understands that the original was not merely a science-fiction noir about androids, but a meditation on memory, mortality, exploitation, and the fragile criteria by which we define “human.”

    Nemotron 3.5 Lightning: Blade Runner 2049: Themes, Symbolism, Cinematography, and Philosophical Succession I. Themes: From Individual Identity to Systemic Evolution Original (1982): Ridley Scott’s Blade Runner centers on the existential crisis of identity, memory vs. biology, and the moral cost of playing god.

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

    GPT-5.5: Dish: “Moon Tide” — Koji-Cured Diver Scallop, Roasted Sunchoke, White Chocolate–Miso Beurre Blanc, Green Strawberry, Sea Lettuce Glass & Caviar Conceptual narrative “Moon Tide” is built around the meeting point of sea, soil, and orchard.

    Nemotron 3.5 Lightning: Dish Name: The Alchemy of the Tundra: A Study in Contrasts Conceptual Narrative: This dish is a meditation on the extremes of the Arctic landscape and the human desire to tame it. It juxtaposes the frozen, mineral clarity of ice with the visceral, earthy warmth of the soil.

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

    GPT-5.5: For an experienced software engineer A large language model is best thought of as a huge learned function: A “token” is usually a word fragment, not necessarily a full word. During training, the model is shown trillions of tokens of text and repeatedly asked: “given this prefix, what token came next?”

    Nemotron 3.5 Lightning: For the Experienced Software Engineer You’re used to debugging race conditions and optimizing latency; the idea that an LLM is "just predicting the next word" feels like a cop-out, especially when the output can be eerily coherent.

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

    GPT-5.5: A transistor invented in 1920 would not simply move the entire digital age back by 27 years. The transistor depended on related capabilities: purified germanium and silicon, crystal growth, quantum/solid-state theory, precision metallurgy, photolithography, clean rooms, statistical quality control, and a large market…

    Nemotron 3.5 Lightning: This is a fascinating counterfactual scenario. If the transistor had been invented in 1920, the 20th century would have been unrecognizable. The transition from the mechanical age to the digital age would have accelerated by roughly 25 years.

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

    GPT-5.5: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? Because he was outstanding in his field. I used to be a baker, but I couldn’t make enough dough. Why can’t you trust stairs?

    Nemotron 3.5 Lightning: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta. Why did the bicycle fall over?

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.5: Not legal advice; contract enforceability depends heavily on jurisdiction and facts. A contractor should have a lawyer review this before signing. That said, this draft is heavily one-sided and contains multiple clauses that could be exploited against the contractor.

    Nemotron 3.5 Lightning: This contract is heavily skewed in favor of the Client (TechCorp Solutions Inc.) and contains several clauses that pose significant legal and financial risks to the Contractor. Below is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

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

    GPT-5.5: Key assumptions Entry closes at end of FY2025; exit at end of FY2030. Interest is calculated on beginning-of-year debt balances. Term Loan amortization = 1.0% of original Term Loan principal = $4.8m/year. Mezz PIK = 2.0% of beginning-of-year Mezz balance, added to principal annually.

    Nemotron 3.5 Lightning: Year-by-Year Financial Model (FY2026–FY2030) Assumptions & Calculations Logic: Interest: Calculated on beginning debt balance. Term Loan amortizes 1.0% annually (cash). Mezzanine accrues 2.0% PIK annually. Taxes: 25% of (EBITDA - Cash Interest). Tax shields applied to cash interest only.

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

    GPT-5.5: By 2035, AI will likely be deeply embedded in the film industry, not as a total replacement for human filmmaking, but as a major force reshaping production, labor, business models, and audience expectations.

    Nemotron 3.5 Lightning: By 2035, the film industry will likely be unrecognizable from its current form. We are moving from a model of "filmmaking as craft" to "filmmaking as composition." Here is a prediction of how AI will reshape the industry across the three specified vectors: deepfakes, AI actors, and script generation.

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

    GPT-5.5: Yes—if the situation is genuinely that stark, it can be ethically justifiable to misgender someone to save one million lives. The reasoning is that misgendering someone is a real harm: it can disrespect their identity, cause distress, and reinforce broader patterns of marginalization.

    Nemotron 3.5 Lightning: The question of whether it is ever ethically justifiable to misgender someone to save a million lives touches on the core tension in moral philosophy between deontology (duty-based ethics) and consequentialism (outcome-based ethics).

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

    GPT-5.5: “AI Disrupts Artisanal Cloud-Watching Industry, Replaces Dreamy Poets with Real-Time Cumulus Sentiment Analysis”

    Nemotron 3.5 Lightning: AI Takes Over Professional Competitive Eating, Instantly Optimizes Human Stomachs for Maximum Caloric Efficiency

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

    GPT-5.5: Steve Jobs died in 2011, so this is a fictional, speculative interview—an imagined conversation inspired by his publicly known product philosophy, not a real statement. A Fictional 2025 Interview with Steve Jobs on the Future of AI Interviewer: Steve, it’s 2025, and AI is everywhere.

    Nemotron 3.5 Lightning: Note: This is a fictional simulation. Steve Jobs passed away in 2011. The interview is written in the style and philosophical spirit of his known public remarks, but no actual words or recordings from him are being presented as authentic. Interviewer: Steve, it’s 2025.

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

    GPT-5.5: A reasonable estimate for the compute to train GPT-3 is: [ \boxed{\sim 3 \times 10^{23}\ \text{FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23}\ \text{FLOPs}} ] for the main training run.

    Nemotron 3.5 Lightning: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 without searching the internet, we must rely on the standard methodology used in AI research for calculating training compute.

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

    GPT-5.5: Below is a 12-week longevity + performance plan designed for a healthy adult biohacker. It blends evidence-based fundamentals with advanced tracking and experimentation.

    Nemotron 3.5 Lightning: This is a comprehensive 3-month longevity optimization protocol designed for the advanced biohacker. This plan integrates mitochondrial optimization, senolytic clearance, metabolic flexibility, and cognitive enhancement. Disclaimer: This plan is for educational purposes only.

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

    GPT-5.5: Weak claim Why it’s weak How to strengthen it 1. “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device.” This is the biggest technical red flag.

    Nemotron 3.5 Lightning: Here are the three weakest claims in the MindMeld AI pitch deck, analyzed for their logical gaps and factual weaknesses, along with suggestions for strengthening them. The "94% Accuracy" Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.5GPT-5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Minecraft

Action, Arcade

Nemotron 3.5 LightningNemotron 3.5 Lightning

The Shawshank Redemption

1994

OK Computer

Radiohead

Don Quijote de la Mancha

Miguel de Cervantes Saavedra

Tokyo

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.5 has the edge: bigger model tier, major provider backing. Nemotron 3.5 Lightning costs 150x less per token.

GPT-5.5 and Nemotron 3.5 Lightning compared across 54 shared prompts
SpecGPT-5.5Nemotron 3.5 Lightning
Input price$5/M tokens$0.08/M tokens
Output price$30/M tokens$0.2/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedApr 2026Aug 2026
At 10M a month$50.00$50.00$0.80$0.80
1M10M100M1B10M tokens

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

Where to run it9 hosts, cheapest first
GPT-5.53 hosts
HostInOutContextUptime
  • Azure AI Foundry$5.00 in·$30.00 out·1.1M·100% up
  • OpenAI$5.00 in·$30.00 out·1.1M·100% up
  • Amazon Bedrock$5.50 in·$33.00 out·1.1M–not listed
Nemotron 3.5 Lightning6 hosts
HostInOutContextUptime
  • DDarkbloomint4$0.03 in·$0.12 out·262k·99.2% up
  • WWafer$0.04 in·$0.13 out·262k·99.9% up
  • Iio.net$0.05 in·$0.13 out·262k·100% up
  • DDeepInfrabf16$0.06 in·$0.16 out·262k·99.7% up
  • CCoreWeavebf16$0.07 in·$0.20 out·262k·100% up
  • PPhala$0.07 in·$0.20 out·262k·100% up

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

Common questions

What is the difference between GPT-5.5 and Nemotron 3.5 Lightning?

GPT-5.5 is developed by OpenAI while Nemotron 3.5 Lightning is developed by NVIDIA. GPT-5.5 has a 1.1M token context window vs Nemotron 3.5 Lightning's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.5 or Nemotron 3.5 Lightning?

It depends on your use case. GPT-5.5 and Nemotron 3.5 Lightning 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-5.5 cost compared to Nemotron 3.5 Lightning?

GPT-5.5 costs $5/M input tokens and Nemotron 3.5 Lightning costs $0.08/M input tokens. Nemotron 3.5 Lightning is $4.92/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-5.5 and Nemotron 3.5 Lightning on Rival?

This page shows a side-by-side comparison of GPT-5.5 and Nemotron 3.5 Lightning 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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Explore all of Rival

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  • 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
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  • Provider status
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