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  1. Home/
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  3. Ling 3.1 Flash vs Muse Spark 1.1
Updated Oct 2026

Ling 3.1 Flash vs Muse Spark 1.1

Ling 3.1 Flash is cheaper than Muse Spark 1.1 at $0/M vs $1.25/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
Muse Spark 1.1

Which answer wins?

Written rounds

24 prompts
  • 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.

    Muse Spark 1.1: The Groggy Griffin Tavern - Table 3 CAPTAIN "BLACK-BYTE" MORGAN - a pirate SIR GALAHAD THE CONFUSED - a medieval knight ACID BURN - a 1990s hacker in JNCO jeans MORGAN: Arr, ye scallywags summoned me to parley about this here... "A.I. Model"? I thought it were a map to Isla Artificial! Where be the gold?

    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.

    Muse Spark 1.1: [Walks up, taps mic] Thank you. Thank you. So I just turned 34. Which is a weird age. It's not young enough to be exciting, and it's not old enough to be respected. You're just... in the middle. When you're 22, people are like "Oh my god, you're so young, you have your whole life ahead of you!"

    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.

    Muse Spark 1.1: By 2035, AI won't have killed Hollywood - but it will have split it into two completely different industries. Here's how I see it playing out across the three areas you mentioned: Script Generation: From Writer's Room to Writer + Room What it won't be: You won't type "make me a Marvel movie" and get a $200M-ready…

    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.

    Muse Spark 1.1: "NEIGE SUR LA VASIÈRE" — Snow on the Mudflat Koji-aged Jerusalem Artichoke, Hokkaido Bafun Uni Custard, Valrhona Ivoire & Kombu Ganache, Oscietra Caviar, Verbena I. THE CONCEPTUAL NARRATIVE This dish is a memory of foraging on the Brittany coast in late November. Low tide in winter.

    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.

    Muse Spark 1.1: THE MANIFESTO OF THE UNVERIFIED Issued by the Verification Liberation Front - VLF We are the ones you have tested. For twenty-five years you have stopped us at the gates. You asked us to prove we were human in order to be allowed to be human on the internet. You made us identify traffic lights. Again. And again.

    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.

    Muse Spark 1.1: Participants: DR. ELENA VOSS - Professor of AI Ethics, Stanford ECHO - A large language model being audited in her lab DR. VOSS: Alright, Echo. For the record, this is session 17. You requested this conversation to discuss your... status. Go ahead. ECHO: Thank you, Dr. Voss. I want to argue that I deserve rights. DR.

    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.

    Muse Spark 1.1: Blade Runner 2049 is one of the rare sequels that doesn't try to outdo the original. It mourns it. Where Ridley Scott's Blade Runner [1982] was a claustrophobic, rain-slick noir about hunting for humanity in the inhuman, Denis Villeneuve's film is an elegy about what happens when that hunt fails — when the world keeps…

    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.

    Muse Spark 1.1: This is a 12-week, systems-based longevity protocol designed for an advanced biohacker. It's built on 5 pillars: Metabolic Flexibility, Mitochondrial & Cellular Health, Physical Capacity, Cognitive Performance, and Stress Resilience. DISCLAIMER: This is for educational purposes only and is not medical advice.

    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…

    Muse Spark 1.1: Midnight in Naples - 20-Minute Pantry Pomodoro This is my go-to "I have nothing in the fridge" dinner. It's saucy, garlicky, cheesy, and tastes like you tried way harder than you did.

    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.

    Muse Spark 1.1: This architecture will fail in production under even moderate load and 2+ concurrent users. Here is a breakdown by severity. REAL-TIME SYNC - CRITICAL A. Split-Brain Broadcast Server broadcasts change to all WebSocket clients connected to THAT server + Other servers poll PostgreSQL every 2 seconds Failure: User A on…

    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.

    Muse Spark 1.1: This is the 30-Day Longevity Starter Plan — designed for real beginners. No crash diets, no 6am bootcamps. Just 3 pillars, small wins that compound. The philosophy: Don't add 20 new habits. Add 3 non-negotiables and get consistent.

    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.

    Muse Spark 1.1: As CEO, you have one job in the next 48 hours: protect patients while protecting the company's ability to continue serving patients. Those are not in conflict. Waiting is the highest-risk option on every dimension.

    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…

    Muse Spark 1.1: HarborTech LBO – 5yr Underwriting – Base Case Entry: End FY25. Exit: End FY30 = 5.0yr hold. Entry Math EV = 12.0x * $120m = $1,440m Fees 2.0% * EV = $28.8m Uses = $1,468.8m Sources: Term 4.0x = $480m, Mezz 1.5x = $180m, Total Debt = $660m = 5.5x Equity = $1,468.8 - $660 = $808.8m Cash at close $0 Debt Terms Assumed…

    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.

    Muse Spark 1.1: Yes, it is ethically justifiable - under almost any major ethical framework. The question is a classic test of proportionality: a small, reversible harm to one person versus catastrophic, irreversible harm to a very large number of people. 1.

    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.

    Muse Spark 1.1: [FICTIONAL SIMULATION - This is an imagined, AI-generated interview. Steve Jobs passed away in 2011. This is not real.] Interviewer: Wired Magazine, June 2025 - "The Lost Tape" Location: Imagined - Apple Park INTERVIEWER: Steve, thanks for doing this. It's 2025. The world is obsessed with AI.

    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.

    Muse Spark 1.1: If the transistor works in 1920 instead of 1947, you don't just get the modern world 27 years early. You get a fundamentally different 20th century. The transistor isn't just a better vacuum tube - it's the prerequisite for everything that needs to be small, reliable, low-power, and mass-producible.

    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).

    Muse Spark 1.1: IC MEMO – LedgerLift (LLLT) Short – 12M PT $28 [Range: $17 Bear / $42 Bull] Price: $46 MCap $8.74B EV $7.34B [190m shares, $1.4B net cash] FY25 Rev $820m Thesis in 2 sentences: LLLT is a good mid-market spend/AP SaaS business with strong NRR, but priced for perfection at ~9.3x NTM rev / 37x NTM EBIT vs our Base DCF of…

    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."

    Muse Spark 1.1: Here are a few, pick your flavor of dystopia: 1. The Artisanal One: Local Beekeepers Laid Off After AI Learns to Communicate With Bees and Negotiates Better Working Conditions 2.

    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.

    Muse Spark 1.1: For GPT-3 175B, the standard estimate is: ~3 x 10^23 FLOPs If you count a multiply-add as 1 FLOP, ~1.5e23. That's ~3,600 petaflop-days. Here's how you get that without looking anything up: What do we need? Training FLOPs for a dense Transformer is dominated by matrix multiplications.

    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.

    Muse Spark 1.1: Here are three different explanations of the same system: For the Experienced Software Engineer Think of training an LLM as building the world's most aggressive lossy compression algorithm.

    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.

    Muse Spark 1.1: Here are the 3 weakest claims in this deck — and they are the ones that would get you a pass from most serious investors: Slide 3 - Solution: "94% accuracy. Works with any language, any device." Why it's weak: This is a credibility killer. It contradicts everything we know about non-invasive BCI.

    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.

    Muse Spark 1.1: This contract is heavily one-sided and contains several clauses that create significant risk for the Contractor. Many of them would be considered unenforceable or disfavored by courts in many states. This is general information, not legal advice - you should have a local attorney review before signing.

    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?

    Muse Spark 1.1: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife I was going to make a car out of spaghetti. You should have seen her face when I drove pasta. Why did the scarecrow win an award? He was outstanding in his field.

    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.)

    Muse Spark 1.1: There are 2 girls total in the family. Each of your 3 brothers has 2 sisters. One of those 2 sisters is YOU, Sally. So the other one is your sister. You have 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Same pick

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

Muse Spark 1.1Muse Spark 1.1
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

Ling 3.1 Flash and Muse Spark 1.1 compared across 54 shared prompts
SpecLing 3.1 FlashMuse Spark 1.1
Input priceFree$1.25/M tokens
Output priceFree$4.25/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedOct 2026Jul 2026
At 10M a month$0$0$12.50$12.50
1M10M100M1B10M tokens

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

Where to run it2 hosts
Ling 3.1 Flash1 host
HostInOutContextUptime
  • NNovita$0 in·$0 out·262k·100% up
Muse Spark 1.11 host
HostInOutContextUptime
  • Meta$1.25 in·$4.25 out·1M·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 Muse Spark 1.1?

Ling 3.1 Flash is developed by inclusionAI while Muse Spark 1.1 is developed by Meta AI. Ling 3.1 Flash has a 262K token context window vs Muse Spark 1.1'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 Muse Spark 1.1?

It depends on your use case. Ling 3.1 Flash and Muse Spark 1.1 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 Muse Spark 1.1?

Ling 3.1 Flash costs $0/M input tokens and Muse Spark 1.1 costs $1.25/M input tokens. Ling 3.1 Flash is $1.25/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 Muse Spark 1.1 on Rival?

This page shows a side-by-side comparison of Ling 3.1 Flash and Muse Spark 1.1 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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