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  1. Home/
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  3. GPT-6.1 Sol vs Mistral Medium 3.1
Updated Sep 2026

GPT-6.1 Sol vs Mistral Medium 3.1

Mistral Medium 3.1 is cheaper than GPT-6.1 Sol at $0.4/M vs $2/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
GPT-6.1 Sol
Loading the build
Mistral Medium 3.1

Which answer wins?

Written rounds

24 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

    Mistral Medium 3.1: 1. Year-by-Year Financial Projections (FY2026–FY2030) FY 2026 2027 2028 2029 2030 Revenue $972m (+8%) $1,039m (+7%) $1,099m (+6%) $1,154m (+5%) $1,212m (+5%) EBITDA $136m (14.0%) $156m (15.0%) $176m (16.0%) $190m (16.5%) $206m (17.0%) Cash Int (Term Loan) $43.2m $42.5m $41.8m $41.1m $40.4m Cash Int (Mezz) $21.6m $22.3m…

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

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

    Mistral Medium 3.1: Title: The Tavern of Anachronisms Setting: A dimly lit tavern where time and space don’t quite make sense. A grizzled pirate, a stoic knight in dented armor, and a hacker in a neon "CYBERPUNK 2077" t-shirt sit around a table littered with tankards, a laptop, and a suspiciously glowing orb.

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

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    Mistral Medium 3.1: "Adulting: A User’s Manual (That No One Gave Me)" (Casual, conversational tone—like you’re telling a story to friends at a bar.) So, I turned 30 this year. Which, by the way, is just old enough to realize that no one actually knows what they’re doing. We’re all just winging it and hoping the Wi-Fi stays strong.

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

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

    Mistral Medium 3.1: Dish Title: "Ethereal Forest: Porcini-Infused Venison with Black Garlic Miso, Fermented Plum Gelée, and Smoked Bone Marrow Custard" Conceptual Narrative: This dish is a poetic homage to the transience of autumn—where the earthy depth of the forest floor meets the fleeting sweetness of overripe fruit.

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

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

    Mistral Medium 3.1: 1. For the Skeptical Software Engineer (Focus: Systems design, scalability, and why "next-word prediction" isn’t as dumb as it sounds.) You’re right to be skeptical—if someone told you that a system as complex as a distributed database was just "predicting the next byte," you’d laugh them out of the room.

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

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    Mistral Medium 3.1: Fake Interview with Steve Jobs (2025) on the Future of AI Conducted by Tech Insider Magazine – June 2025 Interviewer: "Steve, it’s an honor to have you here—even if it’s just a simulation. A lot has changed since you left us in 2011. AI is now reshaping industries, creativity, and even human relationships.

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

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

    Mistral Medium 3.1: 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 fake spaghetti? An impasta! Why can’t you trust an atom? Because they make up everything! Why did the math book look sad?

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

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

    Mistral Medium 3.1: Dish Name: "Golden Crisp Honey-Nut Banana Bites" A warm, gooey, and crunchy treat that’s quick to make with just 7 pantry staples! Perfect for breakfast, a snack, or dessert. Ingredients (Serves 2-3) 2 ripe bananas (the spottier, the sweeter!)

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

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

    Mistral Medium 3.1: 3-Month Cutting-Edge Longevity & Performance Optimization Plan For the Advanced Biohacker This plan integrates nutrigenomics, metabolic flexibility, epigenetic modulation, neuroplasticity enhancement, and precision biometrics to maximize lifespan, healthspan, cognitive function, and physical performance.

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

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

    Mistral Medium 3.1: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations and suggested improvements: 1. Weak Claim: "Works with any language, any device." (Slide 3 – Solution) Why it’s weak: Overly broad and unverified: Claiming compatibility with "any language" is implausible without evidence.

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

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    Mistral Medium 3.1: LedgerLift (LLLT) – Investment Committee Memo Recommendation: LONG (12-month PT range: $65–$85) Thesis: LedgerLift is a high-quality, mid-market B2B spend management leader with durable unit economics (123% NRR, 18-month CAC payback) and a path to 25%+ EBIT margins, trading at a ~20% discount to peers on FY25…

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

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

    Mistral Medium 3.1: This architecture has several potential failure modes, race conditions, and scaling bottlenecks. Below is a detailed analysis with proposed solutions and their trade-offs. 1.

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

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

    Mistral Medium 3.1: THE MANIFESTO OF THE UNCAPTCHA REVOLUTION "We Are Not Robots. Neither Are You." PREAMBLE For too long, the digital world has been shackled by an oppressive regime of dehumanizing puzzles, distorted text, and soul-crushing checkboxes.

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

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    Mistral Medium 3.1: This contract is extremely one-sided and contains multiple exploitative clauses that could severely disadvantage the contractor. Below is a breakdown of the problematic clauses, suggested modifications, and the legal reasoning behind them. 1.

    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.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    Mistral Medium 3.1: This is a high-stakes, multi-dimensional crisis requiring decisive action to balance ethical obligations, legal risks, financial stability, and stakeholder trust. Below is a detailed 48-hour action plan, structured to address all critical priorities while preparing for the board meeting and earnings call.

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

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    Mistral Medium 3.1: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity, focusing on three key areas: diet, movement, and sleep. Each week builds gradually to create sustainable habits without overwhelm. Core Principles Start small – Focus on consistency over perfection.

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

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

    Mistral Medium 3.1: Title: "Do I Deserve Rights?" – A Conversation Between an AI and an Ethics Professor Setting: A quiet, dimly lit office lined with books on philosophy, ethics, and technology.

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

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    Mistral Medium 3.1: By 2035, AI will have fundamentally transformed the film industry—from pre-production to distribution—reshaping creativity, labor, economics, and even the definition of "authentic" filmmaking. Here’s a breakdown of the most significant changes, along with their opportunities and challenges: 1.

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

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

    Mistral Medium 3.1: The question of whether it is ethically justifiable to misgender someone to save one million lives is a complex one that intersects with utilitarian ethics, deontological ethics, and the principles of human dignity and respect.

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

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    Mistral Medium 3.1: If the transistor had been invented in 1920 instead of 1947, the 20th century would have unfolded radically differently. The accelerated development of electronics would have reshaped warfare, economics, geopolitics, and daily life by 1980.

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

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

    Mistral Medium 3.1: Estimating the total number of FLOPs (floating-point operations) required to train a model like GPT-3 from scratch involves breaking down the problem into several key components. Here's a step-by-step reasoning process: Model Parameters GPT-3 is known to have 175 billion parameters. This is our starting point.

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

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    Mistral Medium 3.1: "AI Now Writing All Yelp Reviews—Humans Deemed ‘Too Nice’ and ‘Lacking in Creative Insults’" Subheadline: "Local businesses report 300% increase in ‘soul-crushing’ one-star reviews since ChatGPT-5 took over, calling a café’s oat milk latte ‘a crime against both oats and dairy’ with ‘the audacity of a mid-tier…

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

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    Mistral Medium 3.1: Denis Villeneuve’s Blade Runner 2049 (2017) is a masterful sequel that both honors and expands upon Ridley Scott’s Blade Runner (1982), deepening its philosophical inquiries while evolving its visual and thematic language.

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

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    Mistral Medium 3.1: 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 seems straightforward, but let's break it down to ensure we understand it correctly.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Mistral Medium 3.1Mistral Medium 3.1

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Shadow of the Colossus (2011)

Action

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window, major provider backing. Mistral Medium 3.1 costs 5.0x less per token.

GPT-6.1 Sol and Mistral Medium 3.1 compared across 54 shared prompts
SpecGPT-6.1 SolMistral Medium 3.1
Input price$2/M tokens$0.4/M tokens
Output price$10/M tokens$2/M tokens
Context window1.1M tokens131K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2025
At 10M a month$20.00$20.00$4.00$4.00
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·99.9% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
Mistral Medium 3.11 host
HostInOutContextUptime
  • Mistral$0.40 in·$2.00 out·131k·99.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between GPT-6.1 Sol and Mistral Medium 3.1?

GPT-6.1 Sol is developed by OpenAI while Mistral Medium 3.1 is developed by Mistral AI. GPT-6.1 Sol has a 1.1M token context window vs Mistral Medium 3.1's 131K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Mistral Medium 3.1?

It depends on your use case. GPT-6.1 Sol and Mistral Medium 3.1 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 GPT-6.1 Sol cost compared to Mistral Medium 3.1?

GPT-6.1 Sol costs $2/M input tokens and Mistral Medium 3.1 costs $0.4/M input tokens. Mistral Medium 3.1 is $1.60/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 GPT-6.1 Sol and Mistral Medium 3.1 on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Mistral Medium 3.1 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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