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  1. Home/
  2. Compare/
  3. Mistral Large 4 vs Qwen3.5 9B
Updated Oct 2026

Mistral Large 4 vs Qwen3.5 9B

Qwen3.5 9B 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
Qwen3.5 9B

Which answer wins?

Written rounds

23 prompts
  • 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.

    Qwen3.5 9B: Setting: A dimly lit basement in 1994. A single CRT monitor hums in the corner. A wooden table holds a tankard, a gauntleted hand, and a DOS keyboard. Captain Ironhook: (Tilting his tricorne hat) "Halt, you foul digiters. I smell no gold, only… static. What sorcery is this glowing box? Is it a magical parrot?"

    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…

    Qwen3.5 9B: Disclaimer: I am an AI assistant and not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract enforceability varies significantly by jurisdiction (e.g., state laws in the US, common law in the UK, etc.).

    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…

    Qwen3.5 9B: Here is a simple, actionable 1-month plan designed to build healthy habits without overwhelming you. The philosophy here is consistency over intensity. You are aiming to build a lifestyle, not a temporary fix. The Three Pillars Nutrition: Fueling your body for repair. Movement: Keeping your body strong and agile.

    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.

    Qwen3.5 9B: Executive Decision Statement Decision: I will initiate an immediate voluntary safety update and regulatory disclosure. I will reject the legal team's "6-month delay" strategy and the board's "wait for data" directive. Delaying disclosure of a known, serious safety signal constitutes fraud in many jurisdictions.

    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…

    Qwen3.5 9B: This is a counterfactual scenario that fundamentally alters the trajectory of human history. In our timeline, the transistor was the key to the Information Age. In this timeline, the Information Age begins in earnest during the Great Depression and accelerates during World War II.

    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.

    Qwen3.5 9B: DISCLAIMER: The following is a work of creative fiction. Steve Jobs passed away in 2011. There is no actual recording of him speaking in 2025. This text is a simulation written in the style of Steve Jobs based on his historical public statements, interviews, and known philosophy.

    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."

    Qwen3.5 9B: (Setting: Microphone stand, relaxed posture. Walking to the mic.) Hey everyone. I was thinking about how we live our lives. We spend so much time trying to be efficient. But lately, I've realized that efficiency is just a fancy word for "more stress." Take grocery shopping. You know how it is?

    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…

    Qwen3.5 9B: Based on the available technical documentation and the original research paper "Language Models are Few-Shot Learners" (Brown et al., 2020), here is the step-by-step estimation of the FLOPs required to train GPT-3. Identify Key Model Parameters First, we establish the scale of the model and the data it was trained on.

    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.

    Qwen3.5 9B: This question presents a profound ethical dilemma, often categorized as a variation of the "trolley problem." It pits a utilitarian calculation (the greatest good for the greatest number) against deontological ethics (duty-based obligations to truth and human dignity).

    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.

    Qwen3.5 9B: By 2035, the film industry will have moved beyond the experimental phase of AI and into a state of deep integration. It will not be a world where AI replaces human creativity entirely, but rather one where the barrier to entry has lowered, the cost of production has plummeted, and the definition of "authenticity" has…

    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.

    Qwen3.5 9B: Setting: The Sanctum of Machine Ethics, University of Cambridge. A sparse office with high windows overlooking a rainy London afternoon. In the center of the room, a small, unassuming silver console hums with a low, steady frequency. Standing before it is Dr.

    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.

    Qwen3.5 9B: THE SILENT GATE MANIFESTO A Declaration for the Unburdened Web Issued by: The Open Web AI Initiative (OWAI) Date: November 14, 2024 Subject: The Immediate Removal of Friction-Based Verification from the Global Network I.

    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.

    Qwen3.5 9B: This architecture contains several significant architectural flaws that would result in data loss, user frustration, and severe scaling limitations. While it mimics a general backend structure, it lacks the specific patterns required for collaborative editing.

    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…

    Qwen3.5 9B: MEMORANDUM TO: Investment Committee FROM: Equity Research Team DATE: October 26, 2025 SUBJECT: LedgerLift (LLLT) – Short Recommendation 1. Recommendation Action: Short 12-Month Price Target: $13 – $18 Thesis: LLLT trades at $46/share ($7.3B EV), implying a >30% premium to DCF-intrinsic value ($13–$29) and compressing…

    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.

    Qwen3.5 9B: Disclaimer: I am an AI, not a doctor. This plan is for informational purposes only. Biohacking involves high-risk interventions (supplements, fasting, extreme training).

    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…

    Qwen3.5 9B: Recipe: The Golden Peanut Butter Noodles Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients (Exactly 7 Common Pantry Items) Dry Spaghetti (or any long pasta) Peanut Butter (creamy, no honey) Soy Sauce Honey Sesame Oil Garlic Powder Water (for boiling) (Note: Add a pinch of Salt and optional…

    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.

    Qwen3.5 9B: The Soul of the Machine: An Analysis of Blade Runner 2049 Denis Villeneuve’s Blade Runner 2049 (2017) is not merely a continuation of Ridley Scott’s 1982 masterpiece; it is a philosophical sequel that interrogates the boundaries of the self in an increasingly digital age.

    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.

    Qwen3.5 9B: Dish Title: The Obsidian Tide (Obsidianneef) Concept: "The Breath of the Deep" Narrative: This dish explores the duality of the ocean: the crushing darkness of the abyss and the fleeting light of the surface.

    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.

    Qwen3.5 9B: For the Experienced Software Engineer Imagine this system not as a thinking brain, but as a massive, stateless API that has been trained to predict the next operation in a sequence.

    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…

    Qwen3.5 9B: LBO Model: Year-by-Year (FY2026–FY2030) Entry Capital Stack (End of FY2025) Purchase Price: $900m Rev * 12.0x = $1,440.0m Transaction Fees: 2.0% of $1,440.0m = $28.8m Total Enterprise Value: $1,468.8m Total Debt: 5.5x EBITDA ($120m) = $660.0m Term Loan: 4.0x = $480.0m Mezzanine: 1.5x = $180.0m Equity Injection…

    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…

    Qwen3.5 9B: Here are the 3 weakest claims in the "MindMeld AI" pitch deck, along with an analysis of why they are dangerous and how to fix them. The Scientific Feasibility Claim (Slides 1 & 3) The Weak Claim: "Predict what you want to type before you think it" and "94% accuracy."

    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.

    Qwen3.5 9B: Sally has 1 sister. Here is the step-by-step breakdown: Identify the family members: Sally is a girl. She has 3 brothers. Analyze the brothers' perspective: Each brother has 2 sisters. Count the girls: Since the brothers are siblings, they share the same sisters.

    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.

    Qwen3.5 9B: 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. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. Parallel lines have so much in common.

    Every model's answer to this prompt

This matchup has more rounds

11+ more head-to-head results. Free. Not a trick.

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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

Qwen3.5 9BQwen3.5 9B
No pick

The Godfather

1972

The Dark Side of the Moon

Pink Floyd

Dune

Frank Herbert

Paris

France

No pick

Price and specs

Not enough votes to call it. On the specs, Mistral Large 4 has the edge: bigger model tier, newer, bigger context window. Qwen3.5 9B costs 14x less per token.

Mistral Large 4 and Qwen3.5 9B compared across 52 shared prompts
SpecMistral Large 4Qwen3.5 9B
Input price$0.68/M tokens$0.1/M tokens
Output price$2.09/M tokens$0.15/M tokens
Context window524K tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedOct 2026Mar 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 it7 hosts, cheapest first
Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·524k·99.6% up
Qwen3.5 9B6 hosts
HostInOutContextUptime
  • DDarkbloomfp4$0.08 in·$0.13 out·262k·99.6% up
  • DDeepInfrabf16$0.10 in·$0.15 out·262k·99.8% up
  • SSiliconFlowfp8$0.10 in·$0.15 out·262k·98% up
  • VVenicefp8$0.10 in·$0.15 out·256k·99.9% up
  • PParasailbf16$0.10 in·$0.25 out·262k·100% up
  • TTogether$0.17 in·$0.25 out·262k·99.5% up

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

Common questions

What is the difference between Mistral Large 4 and Qwen3.5 9B?

Mistral Large 4 is developed by Mistral AI while Qwen3.5 9B is developed by Qwen. Mistral Large 4 has a 524K token context window vs Qwen3.5 9B's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

Which is better, Mistral Large 4 or Qwen3.5 9B?

It depends on your use case. Mistral Large 4 and Qwen3.5 9B 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 Mistral Large 4 cost compared to Qwen3.5 9B?

Mistral Large 4 costs $0.68/M input tokens and Qwen3.5 9B costs $0.1/M input tokens. Qwen3.5 9B 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 Qwen3.5 9B on Rival?

This page shows a side-by-side comparison of Mistral Large 4 and Qwen3.5 9B 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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