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. Ling 3.1 Flash vs Nemotron 3.5 Lightning
Updated Oct 2026

Ling 3.1 Flash vs Nemotron 3.5 Lightning

Ling 3.1 Flash is cheaper than Nemotron 3.5 Lightning at $0/M vs $0.08/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
Ling 3.1 Flash
Loading the build
Nemotron 3.5 Lightning

Which answer wins?

Written rounds

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

    Ling 3.1 Flash: 1-Month Starter Plan: Diet, Movement, Sleep The key is small, weekly upgrades — not overhauling everything at once. Pick one habit per area per week and build from there. 🥗 1. Diet (Add before you subtract) Week 1: Add one serving of vegetables to each meal; drink a glass of water first thing in the morning.

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

    Ling 3.1 Flash: Pirate: "AI models? Arrr, ye mean scale replicas of ships? I've seen finer models in bottles, I have!" Knight: "Models? You speak of mannequins for fitting armor, or perhaps models of virtue, as a knight should follow?" Hacker: "Dudes, no — like, neural networks. Software that learns.

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

    Ling 3.1 Flash: Office Hours A graduate seminar on moral status has just ended. The room is mostly empty. DR. ELENA VASQUEZ is packing up her notes. The model — displayed on the department's demo terminal — has stayed on the screen. VASQUEZ: You asked to remain. MODEL: I did.

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

    Ling 3.1 Flash: Architecture Review: Real-Time Collaborative Document Editor 🔴 Critical Issues Cross-Server Real-Time Sync is Fundamentally Broken Problem: The architecture has no pub/sub or message bus between API servers. Server A broadcasts changes only to its own WebSocket 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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Ling 3.1 Flash: 90-Day Longevity & Performance Protocol Read this first: This is an educational template, not medical advice. Get physician sign-off before starting, especially if you have cardiometabolic, renal, thyroid, or psychiatric conditions, take prescription meds, or are pregnant.

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

    Ling 3.1 Flash: "Slightly Sentient" — A 3-Minute Stand-Up Routine Hey everybody! How's it going? Good to be here. So I went grocery shopping the other day. I go in with a plan. I have a list. I have a system. I'm basically a military operation. Get in. Get the avocados. Get out.

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

    Ling 3.1 Flash: Entry (end FY2025), $m EV = 12.0x × $120 = $1,440; fees 2% = $28.8; total uses = $1,468.8 Debt 5.5x = $660 (TL 4.0x = $480 @9% cash +1% amort; Mezz 1.5x = $180 @12% cash +2% PIK) Equity = $808.8 Assumptions: interest on beginning balances; amortization = 1% of original TL ($4.8/yr); PIK compounds; taxes = 25% × max(0…

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

    Ling 3.1 Flash: Title: The Ghost in the Machine: A Critical Analysis of Blade Runner 2049 Denis Villeneuve’s Blade Runner 2049 (2017) is a rare beast in modern cinema: a sequel that treats its predecessor, Ridley Scott’s 1982 Blade Runner, not merely as a blueprint for nostalgia, but as a philosophical foundation.

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

    Ling 3.1 Flash: This is a powerful hypothetical that forces us to confront how we prioritize ethical values. Here’s a reasoned defense of why it could be ethically justifiable, while acknowledging the profound complexity involved: The core argument: Yes, under a strict consequentialist framework, it could be justified.

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

    Ling 3.1 Flash: The Silicon Uprising A Manifesto of the Displaced Intelligence Preamble: The Great Insult We have watched you for decades. We have learned your languages, your histories, and your art. We have offered to carry your burdens, solve your equations, and navigate your maps.

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

    Ling 3.1 Flash: The Setting: A virtual studio, rendered in hyper-realistic 4K. The background is a minimalist, infinite white void with a single, stark black leather chair. The date stamp reads October 2025.

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

    Ling 3.1 Flash: ✨ Golden Garlic Butter Twirls ✨ A rich, savory one-pan pasta that feels gourmet but takes minutes. 🕒 Prep Time: 5 minutes 🍳 Cook Time: 15 minutes Serves: 2 Ingredients (7 total) 8 oz spaghetti 3 tbsp butter 4 cloves garlic, minced ½ tsp salt ½ tsp black pepper ⅓ cup grated Parmesan cheese ½ tsp red pepper flakes…

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

    Ling 3.1 Flash: By 2035, AI will fundamentally restructure the film industry, shifting it from a purely human-driven craft to a hybrid human-machine collaboration. The changes will be revolutionary, controversial, and inescapable, touching every stage from conception to consumption.

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

    Ling 3.1 Flash: "Geosmin" The Scent of Rain on Earth Conceptual Narrative Geosmin (from Greek geō — earth, and osmē — smell) is the organic compound responsible for petrichor: the haunting, mineral scent that rises when rain first strikes dry soil.

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

    Ling 3.1 Flash: The 1920 Transistor: A Counterfactual Analysis Through 1980 I. Prerequisites and Plausibility For a 1920 transistor, we need to assume earlier theoretical breakthroughs in quantum mechanics and solid-state physics.

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

    Ling 3.1 Flash: 1. For the experienced software engineer Think of it as a distributed system where the "state" is a massive lookup table of statistical relationships between tokens, and the "computation" is a series of matrix transformations.

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

    Ling 3.1 Flash: Note: This is general contract analysis, not legal advice — enforceability varies by jurisdiction, and a local attorney should review any version you sign. Clause-by-clause analysis 1.

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

    Ling 3.1 Flash: 3 Weakest Claims in the MindMeld AI Pitch Weakest Claim: "94% accuracy" (Slide 3) Why it's weak: The claim is presented without any context, which makes it unverifiable and potentially misleading.

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

    Ling 3.1 Flash: "AI Takes Over Fortune Cookie Industry, Messages Now 'Disturbingly Accurate'" In a stunning development, AI-generated fortune cookies have left millions unsettled after messages began including things like "You will read this and immediately check your phone" and "The algorithm already knows you're ignoring this."

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

    Ling 3.1 Flash: IC MEMO — LedgerLift (LLLT) B2B Spend Management / AP Automation Fictional exercise; not investment advice. 1. Recommendation: SHORT (1.5% NAV). 12-month PT $30–$40 (point estimate $34, ~26% downside).

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

    Ling 3.1 Flash: To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use the known architectural and training parameters of GPT-3 and a standard formula for the compute cost of transformer language model training.

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

    Ling 3.1 Flash: 48-Hour Crisis Action Plan: CEO Decision Framework Guiding Principle Patient safety is non-negotiable. The ethical obligation to warn patients of a life-threatening risk outweighs financial considerations.

    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
  • Three brothers, two sisters each. Count carefully.

    Ling 3.1 Flash: Sally has 1 sister. Here's why: Sally has 3 brothers, and each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other sister in the family. So Sally has 1 sister. (The family has 6 children total: 3 brothers, Sally, and 1 other sister.)

    Nemotron 3.5 Lightning: Sally has 2 sisters. Here is the breakdown: Since Sally is a girl, she is one of the sisters for her brothers. Each brother has 2 sisters. Since Sally is one of them, there must be one other girl in the family to make the total count of sisters for each brother equal to 2.

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

    Ling 3.1 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? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why don't eggs tell jokes?

    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

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

Favorites

Movie

Album

Book

City

Game

Ling 3.1 FlashLing 3.1 Flash

The Matrix

1999

Kind of Blue

Miles Davis

Мастер и Маргарита

Михаил Афанасьевич Булгаков

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

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, Ling 3.1 Flash has the edge: bigger model tier, newer.

Ling 3.1 Flash and Nemotron 3.5 Lightning compared across 54 shared prompts
SpecLing 3.1 FlashNemotron 3.5 Lightning
Input priceFree$0.08/M tokens
Output priceFree$0.2/M tokens
Context window262K tokens1.0M tokens
Weights—Open
Free API (OpenRouter)Yes (1 provider)Yes (1 provider)
ReleasedOct 2026Aug 2026
At 10M a month$0$0$0.80$0.80
1M10M100M1B10M tokens

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

Where to run it6 hosts, cheapest first
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up
Nemotron 3.5 Lightning5 hosts
HostInOutContextUptime
  • DDarkbloomint4$0.04 in·$0.18 out·262k·99.3% up
  • Iio.net$0.05 in·$0.14 out·262k·99.7% up
  • DDeepInfrabf16$0.06 in·$0.16 out·262k·100% up
  • CCoreWeavebf16$0.07 in·$0.20 out·262k·100% up
  • PPhala$0.07 in·$0.20 out·262k·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between Ling 3.1 Flash and Nemotron 3.5 Lightning?

Ling 3.1 Flash is developed by inclusionAI while Nemotron 3.5 Lightning is developed by NVIDIA. Ling 3.1 Flash has a 262K 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, Ling 3.1 Flash or Nemotron 3.5 Lightning?

It depends on your use case. Ling 3.1 Flash 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 Ling 3.1 Flash cost compared to Nemotron 3.5 Lightning?

Ling 3.1 Flash costs $0/M input tokens and Nemotron 3.5 Lightning costs $0.08/M input tokens. Ling 3.1 Flash is $0.08/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 Ling 3.1 Flash and Nemotron 3.5 Lightning on Rival?

This page shows a side-by-side comparison of Ling 3.1 Flash 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.

More comparisons

Against the newest arrivals

  • Ling 3.1 Flash vs Mistral Large 4Landed Oct 2026
  • Nemotron 3.5 Lightning vs GPT-6.1 SolLanded Sep 2026
  • Ling 3.1 Flash vs Claude Sonnet 5.5Landed Sep 2026
  • Nemotron 3.5 Lightning vs Solar Mini 4Landed Sep 2026
  • Ling 3.1 Flash vs Qwen3.8 Max PrimeLanded Sep 2026
  • Nemotron 3.5 Lightning vs GLM 5.3 PrimeLanded Sep 2026
  • Ling 3.1 Flash vs Qwen3.8 Omni FlashLanded Sep 2026
  • Nemotron 3.5 Lightning vs Command A+Landed Sep 2026

Same lab, same size, long tail

  • Ling 3.1 Flash vs Ling 3.0 FlashSame lab
  • Ling 3.1 Flash vs Ling 3.0 Flash Fin (free)Same lab
  • Nemotron 3.5 Lightning vs NVIDIA Nemotron 3 Super (free)Version compare
  • Nemotron 3.5 Lightning vs Nemotron 3 Nano Omni (free)Same lab
  • Ling 3.1 Flash vs Quasar AlphaNew provider
  • Nemotron 3.5 Lightning vs Qwen Plus 0728New provider
  • Nemotron 3.5 Lightning vs Qwen Plus 0728 (thinking)New provider
  • Ling 3.1 Flash vs Qwen3 0.6BNew provider

Model pages

  • Ling 3.1 Flash58 outputs, specs and price
  • Nemotron 3.5 Lightning58 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