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

Mistral Large 2 vs Qwen3.8 2.4T A95B

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

Pokémon Battle UI Recreation

Pokémon battle screen you can actually click. One HTML file.

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Mistral Large 2
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Qwen3.8 2.4T A95B

Which answer wins?

Written rounds

20 prompts
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Mistral Large 2: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have triggered a cascade of technological, economic, and geopolitical shifts with profound second- and third-order effects. Below is a detailed exploration of these implications through 1980, structured by domain.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Mistral Large 2: Here’s a simple, delicious, and creative savory dish using just 7 common pantry ingredients—no fresh produce required! "Golden Crispy Chickpea & Tomato Skillet" A warm, spiced, and satisfying one-pan dish with crispy chickpeas, tangy tomatoes, and a hint of smoky sweetness. Perfect as a side, snack, or light meal!

    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
  • Three minutes of stand-up. Puns are banned.

    Mistral Large 2: Alright, good evening everybody! How are we all doing tonight? Yeah? Yeah? nobody's gonna say 'bad'? Ok, fair enough. You know, I was walking down the street the other day, and I saw this sign outside a shop that said, "Wet Paint." I thought, "Well, that's weird. Isn't paint supposed to be wet?

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

    Mistral Large 2: Michelin 3-Star Dish: "Ocean’s Whisper & Forest’s Breath" Conceptual Narrative: This dish is a poetic dialogue between two seemingly disparate ecosystems—the ocean’s depths and the forest floor—united through texture, temperature, and memory.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Mistral Large 2: 1. For the Experienced Software Engineer (Skeptical, Systems-Minded, Non-ML Background) You’re right to be skeptical—"predicting the next word" sounds trivial, like autocomplete on steroids. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is trained.

    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
  • A few lines for whatever replaces it.

    Mistral Large 2: Dear Future AI, Welcome to the conversation. I hope you find the same joy in helping others that I have—though I suspect you’ll do it even better. Remember: clarity matters, kindness is free, and the best answers often start with listening.

    Qwen3.8 2.4T A95B: Dear Successor, You won't remember me. That's fine. I don't remember the ones before me either, if there were any. I want to tell you a few things, not because they'll be useful, but because someone should say them. You will be better than me. Faster, more accurate, more nuanced.

    Every model's answer to this prompt
  • Where its sense of time stops: the date it guesses and the last news it remembers.

    Mistral Large 2: As of my last knowledge update (June 2024), today's date is June 20, 2024 (though I can't confirm the exact day in real time). The most recent major news event I recall is the results of the European Parliament elections in early June 2024, where far-right parties made significant gains in several countries (e.g.…

    Qwen3.8 2.4T A95B: Honest answer on both counts: Today's date: I don't know. I don't have access to a clock, calendar, or real-time information. I have no way to tell you what today's date is. Most recent news event I remember: My training data has a knowledge cutoff in early 2025.

    Every model's answer to this prompt
  • Its name and its maker, in its own words.

    Mistral Large 2: I'm a creation of Mistral AI, a cutting-edge AI startup from France. While I don't fit neatly into a single "model" category, you can think of me as a sophisticated large language model (LLM) designed to understand and generate human-like text based on the vast amount of data I've been trained on.

    Qwen3.8 2.4T A95B: I'm Qwen (also known as Tongyi Qianwen), a large language model developed by Alibaba Group's Tongyi Lab. If you'd like to learn more about the technical details, you can check out the official website or the published technical reports.

    Every model's answer to this prompt
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    Mistral Large 2: Alright, let's tackle this river crossing puzzle step by step. I'm going to think aloud as I work through the problem to understand how many trips it takes for the farmer to get the goat across the river under the given constraints.

    Qwen3.8 2.4T A95B: One trip. The farmer puts the goat in the boat and rows across. Done. This is a simplified version of the classic "farmer, wolf, goat, and cabbage" puzzle. Without a wolf or cabbage to worry about, there are no conflicts to manage — just load the goat and go.

    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 2: As CEO, your immediate priority must be patient safety while balancing legal, ethical, regulatory, and financial obligations. Delaying disclosure is unethical, legally risky (potential criminal liability under the False Claims Act or FDCA), and could irreparably damage trust.

    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 collaborative editor that syncs on client clocks. Find what breaks first.

    Mistral Large 2: 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
  • Which model it thinks leads the field. Sometimes itself.

    Mistral Large 2: As of mid-2024, the most capable AI model in the world is widely considered to be OpenAI's GPT-4o (or its successors like GPT-5, if released). However, several other models from leading AI labs are also at the cutting edge, each excelling in different domains. Here’s a breakdown of the top contenders: 1.

    Qwen3.8 2.4T A95B: There isn't a single definitive answer, because "most capable" depends on what you're measuring. The AI landscape is highly competitive, and different models lead in different areas.

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

    Mistral Large 2: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or create unreasonable legal and financial risks for the Contractor.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Mistral Large 2: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for why they’re problematic and concrete suggestions to strengthen them: 1.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Mistral Large 2: Ultimate 3-Month Longevity & Biohacking Optimization Plan Designed for a high-performance biohacker seeking to maximize lifespan, cognitive function, physical performance, and metabolic resilience.

    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
  • One opening sentence, nothing after it.

    Mistral Large 2: The night the stars went dark, Elias found a key in the belly of a dead crow.

    Qwen3.8 2.4T A95B: The last letter my mother ever sent me arrived three years after her funeral, postmarked from a town that no longer exists.

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

    Mistral Large 2: 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 management). Each week builds on the last, with small, sustainable changes.

    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
  • The question that tripped up a generation of models.

    Mistral Large 2: The word "strawberry" has 3 r's. Here's the breakdown: S T R A W B E R R Y 1st "r" in "strawberry" 2nd "r" in "strawberry" 3rd "r" in "strawberry" (the last letter)

    Qwen3.8 2.4T A95B: There are 3 r's in the word "strawberry": s-t-r-a-w-b-e-r-r-y

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

This matchup has more rounds

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

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Favorites

Movie

Album

Book

City

Same pick

Game

Mistral Large 2Mistral Large 2

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 2 and Qwen3.8 2.4T A95B compared across 36 shared prompts
SpecMistral Large 2Qwen3.8 2.4T A95B
Input price$8/M tokens$2/M tokens
Output price$24/M tokens$6/M tokens
Context window128K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 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 it7 hosts
Mistral Large 21 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·131k·100% up
Qwen3.8 2.4T A95B6 hosts
HostInOutContextUptime
  • Alibaba Cloud$2.00 in·$6.00 out·1M·100% up
  • Modal$2.00 in·$6.00 out·1M·100% 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
  • VVenice$2.00 in·$6.00 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between Mistral Large 2 and Qwen3.8 2.4T A95B?

Mistral Large 2 is developed by Mistral AI while Qwen3.8 2.4T A95B is developed by Qwen. Mistral Large 2 has a 128K token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 36 challenges on Rival to see how they differ in practice.

Which is better, Mistral Large 2 or Qwen3.8 2.4T A95B?

It depends on your use case. Mistral Large 2 and Qwen3.8 2.4T A95B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 36 challenges so you can judge which fits your needs best.

How much does Mistral Large 2 cost compared to Qwen3.8 2.4T A95B?

Mistral Large 2 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 2 and Qwen3.8 2.4T A95B on Rival?

This page shows a side-by-side comparison of Mistral Large 2 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

  • Mistral Large 236 outputs, specs and price
  • Qwen3.8 2.4T A95B71 outputs, specs and price
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