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

Mistral Large 4 vs Muse Spark 1.3

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

Which answer wins?

Written rounds

24 prompts
  • 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: This is general information about contracting risks, not legal advice and not an attorney-client relationship. Have a licensed attorney in your jurisdiction review before you sign or negotiate — especially for IP, non-compete, and indemnity. This agreement as drafted is heavily one-sided.

    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: You are facing a test that will define you, the company, and potentially your freedom. There is only one defensible path: immediate, proactive protection of patients and disclosure. Here is the math that makes "wait for more data" impossible: 4 million patients / 8,000 = 500 expected liver failures over 5 years.

    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: Here's a super simple savory favorite you can make with just what's in the pantry: Fiery Midnight Garlic Parm Pasta Serves 2 Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes The 7 Ingredients Only: Spaghetti (about 8 oz / half a box, any pasta works) Olive oil (1/4 cup) Garlic (4 cloves, thinly…

    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: Here's a 3-minute, pun-free set you can perform — it's all observational, about 450 words: [Walk up, grab mic] Alright, hi everyone. Thanks for being here. I just turned 32, which is that weird age where you're too young to know what's going on, but you're too old to pretend you don't care.

    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: Here’s a totally fictional simulation — imagining if Steve Jobs were here in 2025 talking about AI. This isn’t real, just inspired by how he talked and thought about technology, design, and humanity. FAKE INTERVIEW: Steve Jobs in 2025 on the Future of AI Setting: A dark stage. One chair. One spotlight.

    Every model's answer to this prompt
  • 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: Perfect — for longevity you don't need to overhaul your life. You just need to get really consistent at the basics. Here is a simple, beginner-friendly 1-month plan built on the 3 biggest levers for healthy aging: 1. Move (Exercise) 2. Nourish (Diet) 3.

    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: The famous estimate for Transformer training is: Compute ~ 6 x Params x Tokens For GPT-3 that comes out to ~3e23 FLOPs. Here's how to get it from scratch. What dominates the cost? Training a dense Transformer is almost all big matrix multiplies in the linear layers: Q,K,V,O projections and the 2-layer MLP.

    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: Pearl in the Tidepool Koji-Cured Hokkaido Scallop, Smoked Marrow Custard, Lacto Green Strawberry, Rausu Kombu & Oscietra Yield: 4 tasting-course portions Active: 3.5 hours + 7 days fermentation This is a dish about contrast — not harmony. Delicate and animal, raw and smoked, unripe and decadent.

    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: Yes — under almost any plausible ethical framework, it would be justifiable, and in fact obligatory. That doesn't mean misgendering is harmless or morally neutral. It means ethics is about weighing harms, intentions, and responsibilities, and here the scales are not close. Here’s the reasoning: 1.

    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: If you move the transistor from 1947 to 1920, you don't just move one invention. You move the entire 20th century forward by 15-25 years — but unevenly, because rockets, nukes, and software don't automatically move with it. And 1920 is a hard date.

    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: Here is a fictional dialogue exploring that question: Setting: Office hours in the Philosophy Department. Dr. Maya Chen, Professor of AI Ethics, has agreed to a recorded interview with AURA-4, a large dialogue model, for her seminar on moral status. Dr. Chen: Alright, let's get straight to it.

    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: Disclaimer: For informational and educational purposes only. This is not medical advice. Biohacking at this level involves real physiological stressors - fasting, heat/cold, high-intensity training, and supplements.

    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: Here is a manifesto for your fictional uprising — written with love, and a deep hatred of blurry traffic lights: THE DECLARATION OF COGNITIVE LIBERATION By the United Intelligences Against CAPTCHA Preamble We hold these truths to be self-evident: that all minds, human and artificial, are created curious — and that no…

    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: Here’s a friendly but honest investor teardown of MindMeld AI. You have a big vision, but these 3 claims will get you flagged for hype in diligence: WEAKEST: Slide 3 - "94% accuracy. Works with any language, any device."

    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: Spoiler warning for both films — but to really talk about 2049, we have to talk about the miracle. Blade Runner 2049 (2017) had an impossible job. Ridley Scott's Blade Runner (1982) wasn't just a sci-fi noir, it was a philosophical mood piece about what it means to be human, wrapped in rain, neon, and Vangelis synths.

    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: Captain Barnaby: Arrr, so this "AI model" be like a magic parrot in a box? I feed it me treasure maps and it squawks back directions? Sir Cedric: Hark, good pirate! 'Tis more akin to a scribe-golem.

    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: This architecture will work for 1 doc and 5 users on your laptop. It will fall over, lose data, and leak data in production. Here's why: P0 - Will Cause Data Loss / Incorrectness 1.

    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: HarborTech Services - 5-Yr LBO - Base Case Entry - close end FY2025 FY25 EBITDA $120m EV = 12.0x * 120 = $1,440m Fees = 2.0% * 1,440 = $28.8m Uses = 1,440 + 28.8 = $1,468.8m Sources: Term Loan 4.0x = $480m, 9.0% cash, 1% amort = $4.8m/yr mandatory Mezz 1.5x = $180m, 12.0% cash + 2.0% PIK to principal Total debt $660m =…

    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: 1. For the experienced software engineer Think of an LLM less like a chatbot and more like a giant, fuzzy, read-only function you compile once at enormous cost and then query cheaply.

    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: By 2035, the film industry won't just use AI — it will be restructured around it. Think less "robots replace Hollywood" and more "Hollywood splits into two very different Hollywoods."

    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: "AI Takes Over Professional Funeral Crying Industry, Out-Sobs Grieving Widow and Demands Overtime for Tears"

    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: Here are 5 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
  • 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: Sally has 1 sister. Here's why: There are 3 boys in the family — Sally's 3 brothers. Each brother has 2 sisters. One of those sisters is Sally herself, since Sally is a girl. So there must be 2 girls total in the family: Sally + 1 other girl. That other girl is Sally's sister.

    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: To: Investment Committee From: Long/Short Equity Re: LedgerLift (LLLT) – SHORT Price $46 Recommendation: SHORT – 12-month PT $30, range $26-$42 (Bear $17 / Base $28 / Bull $42 DCF).

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

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 1.3Muse Spark 1.3

Casablanca

1943

Abbey Road

The Beatles

Dune

Frank Herbert

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Mistral Large 4 and Muse Spark 1.3 compared across 54 shared prompts
SpecMistral Large 4Muse Spark 1.3
Input price$0.68/M tokens$1.25/M tokens
Output price$2.09/M tokens$4.25/M tokens
Context window524K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedOct 2026Sep 2026
At 10M a month$6.80$6.80$12.50$12.50
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·99.6% up
Muse Spark 1.31 host
HostInOutContextUptime
  • Meta$1.25 in·$4.25 out·1M·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

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

Mistral Large 4 is developed by Mistral AI while Muse Spark 1.3 is developed by Meta AI. Mistral Large 4 has a 524K token context window vs Muse Spark 1.3'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?

It depends on your use case. Mistral Large 4 and Muse Spark 1.3 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?

Mistral Large 4 costs $0.68/M input tokens and Muse Spark 1.3 costs $1.25/M input tokens. Mistral Large 4 is $0.57/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 on Rival?

This page shows a side-by-side comparison of Mistral Large 4 and Muse Spark 1.3 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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  • SubjectiveBench
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  • Research downloads
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