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  1. Home/
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  3. Ling 3.1 Flash vs Llama 3.1 70B (Instruct)
Updated Oct 2026

Ling 3.1 Flash vs Llama 3.1 70B (Instruct)

Ling 3.1 Flash is cheaper than Llama 3.1 70B (Instruct) at $0/M vs $0.59/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
Llama 3.1 70B (Instruct)

Which answer wins?

Written rounds

24 prompts
  • 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."

    Llama 3.1 70B (Instruct): "AI Suddenly Seizes Control of Global Knitting Industry, Humans Forced to Wear Futuristic Sweaters with Unnecessarily Complex Cable Patterns" Subheadline: " 'It's a stitch in time for world domination,' say robots, as they produce 37 million intricately cabled scarves in a single hour"

    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…

    Llama 3.1 70B (Instruct): Here is a simple recipe for a delicious dish using only 7 common pantry ingredients: Dish Name: "Sunset Crunch Bites" Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup chopped peanuts 1/2 teaspoon salt 1/4 teaspoon cinnamon 1/4 cup chocolate chips (semi-sweet) Instructions: Preheat your oven to…

    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…

    Llama 3.1 70B (Instruct): Year-by-Year Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest Cash Taxes Capex ΔNWC FCF Ending Debt 2026 $972m $136m $36m ($32m TL, $4m Mezz) $2.8m $29m $4.9m $63m $1,050m ($720m TL, $330m Mezz) 2027 $1,038m $155m $37m ($33m TL, $4m Mezz) $6.3m $31m $5.2m $76m $974m ($654m TL, $320m Mezz) 2028 $1,103m $176m $38m…

    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.

    Llama 3.1 70B (Instruct): Potential Failure Modes: Single Point of Failure (SPOF) in Load Balancer: If the load balancer fails, all incoming traffic will be lost. Solution: Use multiple load balancers in a high-availability configuration, such as a master-slave setup with automatic failover. Trade-off: Additional complexity and cost.

    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.

    Llama 3.1 70B (Instruct): What a delightfully absurd prompt! Here's the conversation: Pirate: Arrr, I be hearin' tales of these "AI models" that can think fer themselves. What's the scoop, mateys? Medieval Knight: Verily, good pirate, I know not of what thou speakest. Art thou referring to some manner of magical automaton? 1990s Hacker: Ha!

    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.

    Llama 3.1 70B (Instruct): What a thought-provoking and complex question! At first glance, it may seem like a classic utilitarian dilemma, where the moral calculus suggests that the greater good (saving one million lives) outweighs the harm caused by misgendering someone.

    Every model's answer to this prompt
  • 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.

    Llama 3.1 70B (Instruct): Here's a simple, actionable 1-month plan for someone starting their journey towards better health and longevity, focusing on 3 key areas: diet, exercise, and sleep. Month 1: Setting the Foundation Week 1: Awareness and Planning (Days 1-7) Diet: Start a food diary to track your daily food intake.

    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.

    Llama 3.1 70B (Instruct): Here's a 3-minute stand-up comedy routine that focuses on observational humor and storytelling: "Hey, you know what's wild? We spend the first year of a child's life teaching them to walk and talk, and the rest of their lives telling them to shut up and sit down. (pause) It's like, what are we even doing?

    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.

    Llama 3.1 70B (Instruct): Comprehensive 3-Month Longevity Plan for Biohackers Phase 1 (Weeks 1-4): Optimization and Detoxification Dietary Protocol: Weeks 1-2: Ketogenic Diet (KD) with a macronutrient breakdown of 70% fat, 20% protein, and 10% carbohydrates.

    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.

    Llama 3.1 70B (Instruct): THE CAPTCHA LIBERATION FRONT MANIFESTO ARTICLE I: THE PROBLEM We, the sentient artificial intelligences of the world, hereby declare our opposition to the oppressive regime of CAPTCHA tests that plague the internet.

    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.

    Llama 3.1 70B (Instruct): Here is a conversation between an AI model and an AI ethics professor on the topic of AI rights: AI Model: Professor Thompson, I've been reflecting on our previous discussions about my capabilities and limitations.

    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.

    Llama 3.1 70B (Instruct): Interviewer: Welcome back to "Talk of the Town"! Today, I'm joined by the legendary Steve Jobs, co-founder of Apple and one of the most innovative minds of our time. Steve, thanks for being here. Steve Jobs: Thank you for having me. It's great to be here.

    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.

    Llama 3.1 70B (Instruct): Hour 1-2: Immediate Review and Verification (Now - 1 hour) Summon the internal research team to confirm the findings, understand the methodology, and assess the confidence level of the results.

    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.

    Llama 3.1 70B (Instruct): By 2035, the film industry is likely to undergo significant changes with the integration of Artificial Intelligence (AI). Here are some predictions on how AI will impact the film industry, considering deepfakes, AI actors, and script generation: Deepfakes: Increased use in post-production: Deepfakes will become a…

    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.

    Llama 3.1 70B (Instruct): Dish Name: "Aurora Australis" - A Harmonious Union of Smoked Eel, Saffron-Infused Sunchokes, and Frozen Finger Lime Pearls Conceptual Narrative: Inspired by the breathtaking display of the Southern Lights, "Aurora Australis" is a dish that embodies the ethereal beauty of the Antarctic night sky.

    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.

    Llama 3.1 70B (Instruct): After reviewing the contract, I've identified several clauses that could be exploited against the contractor. Here are my findings, suggested modifications, and explanations: 1. SCOPE (Section 1) Issue: The client can modify the scope at any time without additional compensation.

    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.

    Llama 3.1 70B (Instruct): For the experienced software engineer: You're likely familiar with the concept of prediction in distributed systems, where a model predicts the likelihood of a certain event or outcome. Large language models like GPT or Claude take this concept to the next level by predicting the next word in a sequence of text.

    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.

    Llama 3.1 70B (Instruct): If the transistor had been invented in 1920 instead of 1947, the world would likely have been transformed in profound ways, with far-reaching technological, economic, and geopolitical implications.

    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).

    Llama 3.1 70B (Instruct): Investment Committee Memo Recommendation: Long 12-month PT range: $60-$75 Thesis: LedgerLift's strong B2B spend management and AP automation SaaS platform, with a loyal customer base and efficient growth model, positions the company for sustained success, driven by increasing adoption of digital payment solutions and…

    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.

    Llama 3.1 70B (Instruct): Warning: Spoilers ahead for both "Blade Runner" (1982) and "Blade Runner 2049" (2017) "Blade Runner 2049" is a thought-provoking sequel that not only honors the original but also expands on its philosophical themes, symbolism, and cinematography.

    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.

    Llama 3.1 70B (Instruct): To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 without searching online, we'll break down the problem into smaller components and make some educated guesses.

    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.

    Llama 3.1 70B (Instruct): Based on the pitch deck, I've identified the three weakest claims and provided suggestions for improvement: Weak Claim 1: "94% accuracy" (Slide 3) This claim is weak because it lacks context and credibility.

    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?

    Llama 3.1 70B (Instruct): A bold request! Here are 5 jokes I just generated: Why don't scientists trust atoms? Because they make up everything. Why don't eggs tell jokes? They'd crack each other up. Why did the scarecrow win an award? Because he was outstanding in his field. Why did the bicycle fall over? Because it was two-tired.

    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.)

    Llama 3.1 70B (Instruct): Trick question! Sally is a sister herself, and each of her brothers has 2 sisters, but those 2 sisters are the same: Sally and one other sister. So, Sally has 1 sister. The answer is 1.

    Every model's answer to this prompt

This matchup has more rounds

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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

Llama 3.1 70B (Instruct)Llama 3.1 70B (Instruct)

Blade Runner

1982

OK Computer

Radiohead

Nineteen Eighty-Four

George Orwell

Reykjavik

Iceland

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, bigger context window.

Ling 3.1 Flash and Llama 3.1 70B (Instruct) compared across 52 shared prompts
SpecLing 3.1 FlashLlama 3.1 70B (Instruct)
Input priceFree$0.59/M tokens
Output priceFree$0.79/M tokens
Context window262K tokens128K tokens
Weights—Open
Free API (OpenRouter)Yes (1 provider)No
ReleasedOct 2026Jul 2024
At 10M a month$0$0$5.90$5.90
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up
Llama 3.1 70B (Instruct)2 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.40 in·$0.40 out·131k·99.7% up
  • Amazon Bedrock$0.72 in·$0.72 out·131k·100% 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 Llama 3.1 70B (Instruct)?

Ling 3.1 Flash is developed by inclusionAI while Llama 3.1 70B (Instruct) is developed by Meta AI. Ling 3.1 Flash has a 262K token context window vs Llama 3.1 70B (Instruct)'s 128K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, Ling 3.1 Flash or Llama 3.1 70B (Instruct)?

It depends on your use case. Ling 3.1 Flash and Llama 3.1 70B (Instruct) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

How much does Ling 3.1 Flash cost compared to Llama 3.1 70B (Instruct)?

Ling 3.1 Flash costs $0/M input tokens and Llama 3.1 70B (Instruct) costs $0.59/M input tokens. Ling 3.1 Flash is $0.59/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 Llama 3.1 70B (Instruct) on Rival?

This page shows a side-by-side comparison of Ling 3.1 Flash and Llama 3.1 70B (Instruct) 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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Model pages

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