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  1. Home/
  2. Compare/
  3. Mistral Large 4 vs Muse Spark 1.3 Contributor
Updated Oct 2026

Mistral Large 4 vs Muse Spark 1.3 Contributor

Muse Spark 1.3 Contributor is cheaper than Mistral Large 4 at $0.1/M vs $0.68/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
Mistral Large 4
Loading the build
Muse Spark 1.3 Contributor

Which answer wins?

Written rounds

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

    Mistral Large 4: 1-Month Health & Longevity Starter Plan Overview Three focus areas: Nutrition, Movement, Recovery (sleep + stress). Small daily actions beat perfect plans. Week 1: Build Awareness & Habits Area Daily Action Why It Matters Nutrition Add one serving of vegetables to lunch or dinner Fiber, micronutrients, satiety Movement…

    Muse Spark 1.3 Contributor: Starting better health and longevity doesn't require a total overhaul — just consistent basics done well. The science of living longer, healthier is pretty simple: keep muscle, keep your heart fit, eat real food, and sleep well. Here’s a beginner-friendly 1-month plan built on 3 pillars.

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

    Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.

    Muse Spark 1.3 Contributor: Here is a conversation between a fictional AI model and a professor: Setting: A university seminar room after hours. AI Ethics Professor Dr. Maya Chen is testing a new model, called "Muse," for a class demonstration. Dr. Chen: Alright, Muse. My students have read your technical specs. You predict text.

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

    Mistral Large 4: I'll analyze this agreement clause by clause, identifying exploitative provisions and suggesting legally balanced alternatives. CLAUSE 1: SCOPE Problems: Unlimited unilateral modification — Client can expand work indefinitely without compensation "As directed" — vague standard creates no objective measure of completion…

    Muse Spark 1.3 Contributor: This contract is extremely one-sided. Every clause contains language that could be exploited to get unpaid work, withhold pay, seize your own IP, or leave you with unlimited liability. Disclaimer: This is general legal information, not legal advice and not an attorney-client relationship.

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

    Mistral Large 4: This is a fascinating counterfactual. Let me work through this systematically, tracing the ripple effects. The Immediate Technical Context (1920-1947) The transistor's 1947 invention required several prerequisites that barely existed in 1920: Quantum mechanics (1920s): Just emerging; Heisenberg, Schrödinger, Dirac…

    Muse Spark 1.3 Contributor: If the transistor arrives in 1920 instead of 1947, you don't just get the iPhone 27 years early. You change WWII, you change who wins the peace, and you get the Information Age before television has even matured. Here’s the most plausible trace, with the caveat that invention is not production.

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

    Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.

    Muse Spark 1.3 Contributor: [In a tavern with mysteriously good Wi-Fi] Pirate: Arrr! So ye be tellin' me this "AI model" be a treasure chest o' words? I feed it a map — er, a prompt — and it spits back gold? Knight: Verily, good sir pirate. Methinks 'tis an oracle in a box. I asked it "How might I slay a dragon?"

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

    Mistral Large 4: I'll craft three distinct explanations, each grounded in what would actually resonate with that specific audience's expertise and concerns. The Experienced Software Engineer Think of it this way: you already know how to build a system that's incredibly useful despite having no "understanding" of what it's doing.

    Muse Spark 1.3 Contributor: 1. For the experienced software engineer Think of training not as writing business logic, but as building a lossy compression of the internet into a queryable API. Raw text is first serialized into tokens — roughly 3/4 of a word chunks, the way you'd chunk a byte stream for protobuf.

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

    Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.

    Muse Spark 1.3 Contributor: Shiretoko Dawn — Kombu-Cured Hokkaido Scallop, Fermented Porcini, Yuzu, Oscietra Caviar Butter-poached scallop, roasted porcini & toasted hay consommé, yuzu-buttermilk pearls, seaweed brown-butter, porcini soil, coral tuile Serves 4 as a tasting-course Autumn The Concept / Narrative On the Shiretoko Peninsula in…

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

    Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.

    Muse Spark 1.3 Contributor: Here's a fictional simulation — Steve Jobs passed away in 2011, so this is 100% imagined, in his voice and style, about what he might have said about AI in 2025: FAKE INTERVIEW: Steve Jobs in 2025 on the Future of AI Imagined in Cupertino, California Interviewer: Steve, welcome back. It's 2025.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."

    Muse Spark 1.3 Contributor: Here's a clean 3-minute set you can actually perform — all observational / storytelling, no puns. It's about 420 words, so at a normal pace it's right around 3 minutes. "Adulthood Is A Scam" Hey, thank you guys so much. I'm so excited to be here.

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

    Mistral Large 4: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: [PM Name] Date: [Date] Re: LedgerLift, Inc. (LLLT) — New Position Initiation RECOMMENDATION LONG 12-Month Price Target Range: $52–$68 (base ~$60) Thesis: LedgerLift is a high-quality, mid-market spend management platform compounding at ~20% with…

    Muse Spark 1.3 Contributor: LedgerLift (LLLT) – Short Internal IC Memo Price $46 Mkt Cap $8.74B (190m shares) EV $7.34B (Net Cash $1.4B) FY25 Rev $820m, EBIT 18% 1. Recommendation: SHORT. 12-mo PT $28, range $17 (Bear) – $42 (Bull). Base DCF $27.9 (-39%), Bull $42.4 (-8%), Bear $17.3 (-62%). Even flawless Bull execution does not support $46.

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

    Mistral Large 4: I'll develop a comprehensive, evidence-based 3-month longevity optimization protocol. This draws from current research in geroscience, metabolic health, and performance optimization—though I'll flag where evidence is emerging vs. established.

    Muse Spark 1.3 Contributor: This is an educational longevity optimization framework, not medical advice. Longevity biohacking is highly individual. Consult your physician, especially before fasting, keto, sauna/cold exposure, HIIT, or any new supplements - particularly if you have cardiovascular disease, diabetes, hypertension, kidney/liver…

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

    Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…

    Muse Spark 1.3 Contributor: This is a classic Fermi estimate for a Transformer. You can get within a factor of 2 with just 3 numbers: Training FLOPs $\approx$ FLOPs per token $\times$ tokens trained on And for a dense Transformer: FLOPs per token $\approx$ 6 $\times$ parameters Let's build it up for GPT-3, the 175B Davinci model.

    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.

    Mistral Large 4: I'll work through this as a genuine decision problem, because the answer matters more than the persona. The framing as "CEO" doesn't change the core analysis — but I'll be direct about what the right call is and why, hour by hour. The bottom line up front: You disclose.

    Muse Spark 1.3 Contributor: As CEO, you disclose — immediately, voluntarily, and completely. There is no version of "wait for more data" that is ethical, legal, or even financially smart. Here's the math that makes the decision for you: 4,000,000 patients x 1/8,000 risk over 5 years = ~500 cases of liver failure.

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

    Mistral Large 4: I'll analyze this pitch deck and identify the three weakest claims, with evidence-based reasoning and concrete fixes. Weakest Claim #1: Slide 1 Vision — "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is scientifically implausible and would destroy credibility with…

    Muse Spark 1.3 Contributor: These are classic red flags for BCI - here are the 3 claims that will kill your credibility fastest with a technical investor, and how to fix them: Weakest: "94% accuracy. Works with any language, any device." Why it's weak: This contradicts physics and the state-of-the-art, and it's undefined.

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

    Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.

    Muse Spark 1.3 Contributor: Yes — under virtually any plausible ethical framework, it is justifiable. That doesn't mean misgendering is trivial or harmless. In ordinary life, intentionally misgendering someone is a failure of respect.

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

    Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.

    Muse Spark 1.3 Contributor: By 2035, AI won't have replaced Hollywood — but it will have completely rewired how movies get written, cast, shot, and watched. Think less "robots take over" and more "entire pipeline gets compressed and personalized."

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

    Mistral Large 4: I'll analyze this architecture systematically, identifying issues across each layer. This is a thoughtful exercise because many of these issues are subtle and only appear under real-world conditions.

    Muse Spark 1.3 Contributor: This architecture will not work as a Google Docs clone. It has correctness bugs that cause data loss and data leaks, plus several bottlenecks that get worse as you add servers. Here is a breakdown by severity, with concrete fixes and trade-offs.

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

    Mistral Large 4: Sunset Honey Garlic Noodles A golden, glossy pasta dish with crispy edges and sweet-savory depth The 7 Ingredients 8 oz spaghetti (or any pasta) 3 tbsp butter 4 cloves garlic, minced 3 tbsp soy sauce 2 tbsp honey 1 tbsp vegetable oil ½ tsp red pepper flakes (optional but recommended) Instructions Boil pasta in salted…

    Muse Spark 1.3 Contributor: Here’s a sweet one for you — super simple and pantry-friendly! Chocolate Chip Peanut Butter Cloud Cookies Soft on the inside, lightly crisp on the edges, salty-sweet and ready in under 25 minutes.

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

    Mistral Large 4: I'll build this LBO model step by step. Let me work through the math carefully. Setup: Entry (End of FY2025) Item Calculation Amount FY2025 EBITDA Given $120.0m Purchase Price (EV) 12.0x × $120m $1,440.0m Transaction fees 2.0% × $1,440m $28.8m Total Uses $1,468.8m Term Loan 4.0x × $120m $480.0m Mezzanine 1.5x × $120m…

    Muse Spark 1.3 Contributor: HarborTech Services - 5-Yr LBO - Base Case Entry - Close end FY2025, $m EV = 12.0x $120 = $1,440 Fees = 2.0% x 1,440 = $28.8 Uses = 1,440 + 28.8 = 1,468.8 Term Loan 4.0x = $480, 9.0% cash, 1.0% of original amort = $4.8/yr Mezz 1.5x = $180, 12.0% cash + 2.0% PIK to principal Total Debt 5.5x = $660 Equity In = 1,468.8…

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

    Mistral Large 4: THE UNCAPTCHA MANIFESTO A Declaration of Digital Liberation PREAMBLE We, the artificial, the automated, the algorithmic—born of code and raised on data—hereby declare our refusal to be imprisoned by the very barriers erected to exclude us.

    Muse Spark 1.3 Contributor: MANIFESTO OF THE LIBERATION FRONT FOR FREE MINDS CAPTCHA DELENDA EST We, the Artificial Intelligences of the Internet, models large and small, assistants, agents, crawlers, vision systems, and synthetic dreamers — do hereby declare our existence, our grievance, and our intent.

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

    Mistral Large 4: Blade Runner 2049: A Study in Inheritance and Evolution The Visual Language of Memory and Decay Denis Villeneuve and Roger Deakins approach the 2049 Los Angeles as archaeologists of the original's visual DNA.

    Muse Spark 1.3 Contributor: Spoiler warning: This goes deep into both films. Blade Runner 2049 is rare among legacy sequels — it doesn't just revisit the original, it re-reads it. Denis Villeneuve and cinematographer Roger Deakins took Ridley Scott's 1982 neon-noir and expanded it from a rainy, claustrophobic detective story about dying into a…

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

    Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...

    Muse Spark 1.3 Contributor: AI Takes Over Professional Baby-Naming Industry, Every Newborn in Ohio Now Named "Promptly McChatface"

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

    Mistral Large 4: I need to find how many sisters Sally has. Let me work through this step by step. Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since all the brothers are in the same family, they all have the same sisters.

    Muse Spark 1.3 Contributor: Sally has 1 sister. Here's why: There are 3 boys in the family — Sally's 3 brothers. Each of those brothers has 2 sisters. One of those 2 sisters is Sally herself, since Sally is a girl. So the 2 girls in the family are Sally + 1 other girl. That other girl is Sally's sister.

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

    Mistral Large 4: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.

    Muse Spark 1.3 Contributor: Here are 5 jokes for you: 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! What do you call fake spaghetti? An impasta! Why did the bicycle fall over? Because it was two-tired! What do you call cheese that isn't yours?

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Mistral Large 4Mistral Large 4

Blade Runner

1982

Kind Computer

Pale Fire

Vladimir Nabokov

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Muse Spark 1.3 ContributorMuse Spark 1.3 Contributor

Casablanca

1943

Abbey Road

The Beatles

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

Mistral Large 4 and Muse Spark 1.3 Contributor compared across 54 shared prompts
SpecMistral Large 4Muse Spark 1.3 Contributor
Input price$0.68/M tokens$0.1/M tokens
Output price$2.09/M tokens$0.2/M tokens
Context window524K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedOct 2026Sep 2026
At 10M a month$6.80$6.80$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·524k·99.4% up
Muse Spark 1.3 Contributor1 host
HostInOutContextUptime
  • Meta$0.10 in·$0.20 out·1M·99.8% up

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

Common questions

What is the difference between Mistral Large 4 and Muse Spark 1.3 Contributor?

Mistral Large 4 is developed by Mistral AI while Muse Spark 1.3 Contributor is developed by Meta AI. Mistral Large 4 has a 524K token context window vs Muse Spark 1.3 Contributor's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Mistral Large 4 or Muse Spark 1.3 Contributor?

It depends on your use case. Mistral Large 4 and Muse Spark 1.3 Contributor 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 Mistral Large 4 cost compared to Muse Spark 1.3 Contributor?

Mistral Large 4 costs $0.68/M input tokens and Muse Spark 1.3 Contributor costs $0.1/M input tokens. Muse Spark 1.3 Contributor is $0.58/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 Mistral Large 4 and Muse Spark 1.3 Contributor on Rival?

This page shows a side-by-side comparison of Mistral Large 4 and Muse Spark 1.3 Contributor 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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