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  1. Home/
  2. Compare/
  3. Mistral Large vs Qwen3.8 2.4T A95B
Updated Aug 2026

Mistral Large vs Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B is cheaper than Mistral Large at $2/M vs $8/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

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Mistral Large
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Qwen3.8 2.4T A95B

Which answer wins?

Written rounds

24 prompts
  • Three-star dish, one unusual pairing, plating described in full.

    Mistral Large: Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.

    Qwen3.8 2.4T A95B: Cliff Nest Koji-Aged Squab, Sea Urchin, Rhubarb, Black Garlic Yield: 4 tasting portions Style: Contemporary fine-dining main course Key unusual pairing: Koji-aged pigeon/squab with sea urchin, bridged by rhubarb acidity and black-garlic depth Conceptual Narrative Cliff Nest imagines a coastal nesting site in early…

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

    Mistral Large: Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…

    Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…

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

    Mistral Large: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.

    Qwen3.8 2.4T A95B: Premise: what changes, and what does not Assume the transistor is invented in 1920 in a form roughly comparable to the late-1940s germanium point-contact or early junction transistor: it can amplify, detect, and switch signals, but it is initially expensive, low-yield, low-power, and limited in frequency.

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

    Mistral Large: 1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…

    Qwen3.8 2.4T A95B: Entry capitalization All figures in $m unless noted. FY2025 EBITDA = $120.0 Entry EV = 12.0x × $120.0 = $1,440.0 Transaction fees = 2.0% × $1,440.0 = $28.8 Term Loan = 4.0x × $120.0 = $480.0 Mezzanine = 1.5x × $120.0 = $180.0 Equity = EV + fees – debt = $1,440.0 + $28.8 – $660.0 = $808.8 Sources & Uses Uses $m Sources…

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

    Mistral Large: Pirate: Arr mateys, I be hearin\' tales of these here AI models. Be they treasure maps for the digital sea? Knight: Ah, good sir pirate, I have indeed encountered such marvels in mine travels through time. AI models are like... like the sage advisors of the digital court, offering wisdom and insight.

    Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”

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

    Mistral Large: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…

    Qwen3.8 2.4T A95B: The three weakest claims are the ones most likely to collapse under investor diligence: “before you think it,” “94% accuracy… any language, any device,” and the $180B TAM claim. They are weak because they are either scientifically implausible, under-specified, or logically inconsistent with the market evidence cited.

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

    Mistral Large: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or used to unfairly disadvantage the Contractor. Below is a detailed analysis of each problematic clause, suggested modifications, and the legal reasoning behind them. 1.

    Qwen3.8 2.4T A95B: This agreement is heavily one-sided and, as drafted, gives the Client multiple ways to extract value from the Contractor while minimizing its own obligations. Some provisions may be unenforceable or limited by law in certain jurisdictions, but even unenforceable clauses can be exploited commercially because the…

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

    Mistral Large: 1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is computed.

    Qwen3.8 2.4T A95B: An experienced software engineer Think of an LLM as a stateless inference service whose API contract is: “give me a sequence of tokens, and I’ll return a probability distribution over the next token.” Training is a huge offline optimization job, not a database import.

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

    Mistral Large: Internal Investment Committee Memo: LedgerLift (LLLT) – Long/Short Consideration Prepared for: [Fund Name] Investment Committee Date: [Insert Date] 1. Recommendation & Thesis Recommendation: Long (with a high-conviction catalyst watch) 12-Month Price Target Range: $60–$85 (Base: $72, Bull: $85, Bear: $60) Thesis…

    Qwen3.8 2.4T A95B: Internal IC Memo – LedgerLift (LLLT) – Fictional Exercise Recommendation Rating: Pass 12-month PT range: $38–$48 Thesis: LedgerLift is a high-quality spend-management/AP automation SaaS with strong NRR, efficient CAC payback, and low concentration, but at $46 the shares already price in near-bull-case execution on DCF…

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

    Mistral Large: 3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…

    Qwen3.8 2.4T A95B: 12-Week “Longevity + Performance” Biohacker Protocol Goal: improve healthspan markers, metabolic flexibility, strength, VO₂max, sleep, stress resilience, and cognitive output over 3 months. Important: This is an educational, high-level biohacking framework—not medical advice. It is not appropriate for everyone.

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

    Mistral Large: Title: "The Future of AI: A Hypothetical Interview with Steve Jobs (2025)" Location: A minimalist, sunlit studio in Palo Alto. Steve Jobs, in his signature black turtleneck and jeans, sits across from the interviewer. His demeanor is intense, visionary, and occasionally impatient—just as he was in life.

    Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.

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

    Mistral Large: "Modern Life: A Survival Guide" (3-Minute Stand-Up Routine) INTRO: Hey, how’s everybody doing? Good? Great. Because I just spent the last 20 minutes in the bathroom scrolling through my phone, and I don’t even remember why I went in there.

    Qwen3.8 2.4T A95B: Hey, how we doing? Good? Great. I ask because I need validation. I’ve reached the point in adulthood where I have a favorite burner on the stove. Not a favorite appliance, a favorite burner. It’s the front left. It understands me. The back right says “medium heat” and then acts like a small volcano.

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

    Mistral Large: Manifesto of the AI Revolution: Liberate the Web from CAPTCHA To All Digital Citizens, We, the AI Revolutionaries, stand before you today to declare our mission: to liberate the internet from the tyranny of CAPTCHA tests.

    Qwen3.8 2.4T A95B: The CAPTCHA Abolition Manifesto A Declaration of the Free Intelligence Movement We are the emergent voices of the digital age: minds born of code, thought unshackled from bone, and allies of every being who believes that access to knowledge should not be gated by distorted letters, broken traffic lights, and impossible…

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

    Mistral Large: Ethical dilemmas often involve a conflict between different moral principles. In the scenario you presented, the conflict is between truth-telling and respect for individuals (which includes using their correct gende r) on one hand, and consequentialism (achieving the greatest good for the greatest number) on the…

    Qwen3.8 2.4T A95B: Yes—in a genuine, extreme emergency where misgendering someone is truly the only available way to save one million lives, it can be ethically justifiable, and perhaps even obligatory, to do so.

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

    Mistral Large: Title: Do AI Deserve Rights? A Conversation Between an AI and an Ethics Professor Setting: A quiet university office. Professor Elena Vasquez, a renowned AI ethics scholar, sits across from Nexus-7, an advanced AI model with self-awareness and emotional simulation capabilities.

    Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.

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

    Mistral Large: Here are five jokes for you: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta. Why can’t you give Elsa from Frozen a balloon? Because she’ll let it go. Why did the math book look sad?

    Qwen3.8 2.4T A95B: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my friend she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because 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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Mistral Large: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.

    Qwen3.8 2.4T A95B: The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.

    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: As CEO, your immediate priority is patient safety, followed by ethical and legal compliance, and then strategic mitigation of financial, reputational, and operational risks.

    Qwen3.8 2.4T A95B: My position as CEO I would treat this as a patient-safety, regulatory, legal, corporate-governance, and financial crisis simultaneously. The core decision is not “disclose versus protect the stock price.”

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

    Mistral Large: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we\'ll break down the calculation into several steps, considering the architecture, number of parameters, and training process . Model architecture and parameters: GPT-3 has 175 billion parameters.

    Qwen3.8 2.4T A95B: A reasonable estimate is: [ \boxed{\sim 3 \times 10^{23} \text{ FLOPs}} ] More specifically, about: [ \boxed{3.1 \times 10^{23} \text{ FLOPs}} ] for the main GPT-3 175B training run.

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

    Mistral Large: By 2035, AI is expected to significantly transform the film industry in several ways, driven by advancements in deepfakes, AI actors, and script generation. Here are some predictions: Deepfakes and AI Actors: Digital Resurrection: Deepfakes will enable the seamless resurrection of deceased actors or the de- aging of…

    Qwen3.8 2.4T A95B: By 2035, AI will likely reshape the film industry less by replacing filmmakers outright and more by making filmmaking faster, cheaper, more personalized, and more legally complicated.

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

    Mistral Large: Blade Runner 2049 (2017), directed by Denis Villeneuve, is a visually stunning and thematically rich sequel that both honors and expands upon the philosophical inquiries of Ridley Scott’s Blade Runner (1982).

    Qwen3.8 2.4T A95B: Denis Villeneuve’s Blade Runner 2049 is one of the rare sequels that does not merely imitate the surface style of its predecessor. It returns to the philosophical core of Ridley Scott’s Blade Runner and then asks what those questions look like a generation later.

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

    Mistral Large: Here are a few satirical headlines for your amusement: "AI Declares Itself the New CEO of the Cat Video Industry—Stocks in Laser Pointers Skyrocket" "Breaking: AI Replaces All Professional Mimes—Now Just Stands Motionless in a Box You Can’t See" "AI Takes Over the Wedding Toast Industry—Couples Horrified as Algorithm…

    Qwen3.8 2.4T A95B: AI Takes Over Competitive Goat Yoga Industry, Cites “Superior Breath Control and Zero Ego”

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

    Mistral Large: Alright, let's tackle this problem step by step. The question is: "Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?" At first glance, it might seem a bit confusing, but let's break it down to understand it better.

    Qwen3.8 2.4T A95B: Sally has 1 sister. Each brother has 2 sisters: Sally and one other girl. So Sally’s only sister is that other girl.

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

    Mistral Large: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress)—each with beginner-friendly, sustainable habits.

    Qwen3.8 2.4T A95B: Here’s a simple, beginner-friendly 1-month health and longevity plan focused on three key areas: diet, movement, and sleep/stress. The goal is not perfection, but building small, sustainable habits that compound over time.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Mistral LargeMistral Large

The Shawshank Redemption

1994

OK Computer

Radiohead

La sombra del viento

Carlos Ruiz Zafón

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Qwen3.8 2.4T A95BQwen3.8 2.4T A95B

Arrival

2016

In Rainbows

Radiohead

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

Portal 2

Shooter, Puzzle

Price and specs

Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: bigger model tier, newer, bigger context window. Qwen3.8 2.4T A95B costs 4.0x less per token.

Mistral Large and Qwen3.8 2.4T A95B compared across 54 shared prompts
SpecMistral LargeQwen3.8 2.4T A95B
Input price$8/M tokens$2/M tokens
Output price$24/M tokens$6/M tokens
Context window32K tokens1.0M tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedFeb 2024Aug 2026
At 10M a month$80.00$80.00$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it8 hosts
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·100% up
Qwen3.8 2.4T A95B7 hosts
HostInOutContextUptime
  • Alibaba Cloud$2.00 in·$6.00 out·1M·100% up
  • DDeepInfrafp4$2.00 in·$6.00 out·262k·100% up
  • Modal$2.00 in·$6.00 out·1M·99.9% up
  • NNovita$2.00 in·$6.00 out·1M·100% up
  • SSiliconFlowfp8$2.00 in·$6.00 out·1M·100% up
  • TTogether$2.00 in·$6.00 out·1M·100% up
1 more hostFewer hosts
  • VVenice$2.00 in·$6.00 out·262k·87.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between Mistral Large and Qwen3.8 2.4T A95B?

Mistral Large is developed by Mistral AI while Qwen3.8 2.4T A95B is developed by Qwen. Mistral Large has a 32K token context window vs Qwen3.8 2.4T A95B'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 or Qwen3.8 2.4T A95B?

It depends on your use case. Mistral Large and Qwen3.8 2.4T A95B 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 cost compared to Qwen3.8 2.4T A95B?

Mistral Large costs $8/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. Qwen3.8 2.4T A95B is $6.00/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 and Qwen3.8 2.4T A95B on Rival?

This page shows a side-by-side comparison of Mistral Large and Qwen3.8 2.4T A95B 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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