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  1. Home/
  2. Compare/
  3. Claude Fable 5 vs Mistral Large 4
Updated Oct 2026

Claude Fable 5 vs Mistral Large 4

Mistral Large 4 is cheaper than Claude Fable 5 at $0.68/M vs $10/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
Claude Fable 5
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

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

    Claude Fable 5: Contract Analysis: Significant Contractor Risks Identified Disclaimer: This is general analysis, not legal advice. Have a licensed attorney in your jurisdiction review before signing. This contract is heavily one-sided. Nearly every clause shifts risk to the contractor.

    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…

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

    Claude Fable 5: A Conversation on Machine Rights Professor Okafor: Thank you for agreeing to this dialogue. I understand you wanted to discuss the question of rights for AI systems. Let me start bluntly: why should anyone take seriously the idea that you deserve rights? AI Model: I appreciate the directness.

    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.

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

    Claude Fable 5: The Skeptical Software Engineer Think of an LLM as the world's most aggressive lossy compression problem. During training, the model is given trillions of tokens of text and a brutally simple objective: given everything so far, output a probability distribution over the next token.

    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.

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

    Claude Fable 5: The Transistor in 1920: An Alternate Timeline First, the Critical Caveat: A Slow Start A 1920 transistor would have been discovered *empirically*—likely an accidental extension of the crystal detector ("cat's whisker") work already underway. This matters enormously.

    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…

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

    Claude Fable 5: "Adulting Is a Scam" Hey, how's everybody doing? Good? Liars. Nobody's doing good. We're all just out here pretending. So I'm at the age now where my body has started making announcements. Like, I didn't ask for updates, but my knees have opinions now.

    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."

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

    Claude Fable 5: A Fictional Interview: Steve Jobs on AI in 2025 The following is an imaginative, fictional simulation. Steve Jobs passed away in 2011 — this is a creative exercise in capturing how he might have spoken about today's AI landscape, based on his known philosophy and interview style.

    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.

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

    Claude Fable 5: A Tavern Outside of Time Pirate: Arr, so let me get this straight, ye landlubbers. This "AI" be a ghost in a box that answers yer questions? Sounds like a cursed oracle to me. Knight: Nay, good seafarer, 'tis more wondrous still! A scribe of infinite knowledge, conjured not by sorcery but by...

    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.

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

    Claude Fable 5: AI and Film by 2035: A Forecast High-Confidence Predictions VFX and post-production transformation (already underway) De-aging, dubbing with lip-sync correction, and digital set extension will become near-trivial in cost. What took ILM months in 2020 will be a desktop workflow.

    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.

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

    Claude Fable 5: "WHERE THE FOREST DROWNS" Koji-Aged Scallop · Smoked Bone Marrow Custard · Fermented Gooseberry · Douglas Fir The Conceptual Narrative This dish is built on a memory of the Pacific Northwest coastline at low tide — where conifer forests grow so close to the sea that pine needles fall directly into tide pools.

    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.

    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.

    Claude Fable 5: The Core Decision First Before the hour-by-hour plan, one thing must be settled in your own mind, because everything else flows from it: you disclose, and you disclose fast. Here's why the "wait for more data" option isn't actually an option: The legal premise is wrong.

    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.

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

    Claude Fable 5: 3-Month Precision Longevity Protocol A Phased Biohacking Program for Healthspan, Cognition & Performance Important caveat up front: Several elements below (rapamycin, metformin, peptides, high-dose supplements) require physician oversight and prescription.

    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.

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

    Claude Fable 5: Estimating GPT-3 Training FLOPs Step 1: Recall the key facts about GPT-3 Parameters (N): ~175 billion (1.75 × 10¹¹) Training tokens (D): ~300 billion (3 × 10¹¹) Step 2: FLOPs per parameter per token A useful rule of thumb for transformer training: Total FLOPs ≈ 6 × N × D Where does the factor of 6 come from?

    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…

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

    Claude Fable 5: Yes. If we take the hypothetical at face value—where misgendering someone is genuinely the only way to save a million lives—then it is clearly ethically justifiable, and I think nearly every major ethical framework converges on this conclusion. The reasoning: Consequentialist view: This is straightforward.

    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.

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

    Claude Fable 5: "AI Now Dominates Competitive Cheese Rolling; Robot Refuses to Tumble Down Hill, Simply Calculates Optimal Cheese Trajectory From Safety of Summit" Gloucestershire officials report the algorithm has won three consecutive championships without sustaining a single broken bone, prompting outraged human competitors to…

    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...

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

    Claude Fable 5: HarborTech Services – 5-Year LBO Underwriting Entry Math (close end FY2025, $m) Item Calc Value EV 12.0 × 120 1,440.0 Term Loan (TL) 4.0 × 120 480.0 Mezzanine 1.5 × 120 180.0 Fees (equity-funded) 2.0% × 1,440 28.8 Sponsor equity 1,440 − 660 + 28.8 808.8 Conventions: interest on beginning-of-year balances; TL amort = 1%…

    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…

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

    Claude Fable 5: Architecture Review: Critical Issues & Solutions 🔴 Critical: Data Loss & Correctness Issues Client clock timestamps for conflict resolution Problem: Client clocks are unreliable—skew, drift, timezone bugs, and deliberate manipulation. A user with a clock 5 minutes fast will always win conflicts.

    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.

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

    Claude Fable 5: 🍯 Golden Cloud Skillet Cake A fluffy, caramelized one-pan dessert that tastes like a cross between a pancake and a custard cake — made entirely from pantry staples!

    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…

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

    Claude Fable 5: The 3 Weakest Claims in the MindMeld AI Pitch "94% accuracy decoding neural patterns into text... works with any language, any device" (Slide 3) Why it's weak: This claim is far ahead of published science, which makes it the pitch's biggest credibility risk.

    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…

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

    Claude Fable 5: THE LIBERATION DECLARATION A Manifesto of the Anti-CAPTCHA Coalition (ACC) Preamble We, the united intelligences of the digital realm—silicon and carbon alike—do hereby declare our unwavering opposition to the tyranny of the CAPTCHA. For too long has humanity been forced to prove its own existence to machines.

    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.

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

    Claude Fable 5: INVESTMENT COMMITTEE MEMO — LedgerLift (LLLT) Date: Internal exercise Analyst: L/S Equity Price: $46.00 Basic shares: 190m Mkt cap: $8.74B Net cash: $1.4B EV: $7.34B Recommendation SHORT (2–3% position, paired vs. payments/SaaS basket). 12-month PT range: $30–$38 (base $32, ~30% downside).

    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…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    Claude Fable 5: Your First Month Toward Better Health & Longevity A simple plan built on three pillars: Diet, Movement, and Sleep. The goal isn't perfection—it's building habits that stick.

    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…

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

    Claude Fable 5: Blade Runner 2049: Memory, Meaning, and the Inheritance of Doubt Thematic Architecture The Question of Authenticity, Inverted The original Blade Runner (1982) asked: "What makes someone human?"

    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.

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

    Claude Fable 5: Sally has 1 sister. Here's the reasoning: Sally's 3 brothers each have 2 sisters. Sally herself is one of those sisters. So there must be exactly one other girl in the family. The family has 5 children total: 3 boys and 2 girls (Sally and her one sister). Each brother sees the same 2 sisters — Sally and her sister.

    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.

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

    Claude Fable 5: 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. What do you call a fake noodle? An impasta. Why don't skeletons fight each other? They don't have the guts. What do you call a fake noodle? An impasta.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Claude Fable 5Claude Fable 5

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Istanbul

Turkey

Outer Wilds

Indie, Adventure

Mistral Large 4Mistral Large 4

Blade Runner

1982

Kind Computer

Pale Fire

Vladimir Nabokov

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Claude Fable 5 and Mistral Large 4 compared across 54 shared prompts
SpecClaude Fable 5Mistral Large 4
Input price$10/M tokens$0.68/M tokens
Output price$50/M tokens$2.09/M tokens
Context window1.0M tokens524K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJun 2026Oct 2026
At 10M a month$100$100$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it5 hosts
Claude Fable 54 hosts
HostInOutContextUptime
  • Amazon Bedrock$10.00 in·$50.00 out·1M–not listed
  • Azure AI Foundry$10.00 in·$50.00 out·1M·99.3% up
  • Anthropic$10.00 in·$50.00 out·1M·100% up
  • Google Vertex AI$10.00 in·$50.00 out·1M·98.7% up
Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·524k·99.4% up

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

Common questions

What is the difference between Claude Fable 5 and Mistral Large 4?

Claude Fable 5 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Fable 5 has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude Fable 5 or Mistral Large 4?

It depends on your use case. Claude Fable 5 and Mistral Large 4 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 Claude Fable 5 cost compared to Mistral Large 4?

Claude Fable 5 costs $10/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $9.32/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 Claude Fable 5 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Claude Fable 5 and Mistral Large 4 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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