Mistral Medium 3 is cheaper than GPT-6.1 Sol at $0.4/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 $4.8m annually. Optional repayments occur at year-end.
Mistral Medium 3: 1. Year-by-Year Financial Projections (FY2026–FY2030) Year Revenue ($m) EBITDA ($m) EBITDA Margin Cash Interest ($m) Cash Taxes ($m) Capex ($m) ΔNWC ($m) Free Cash Flow ($m) Term Loan Ending ($m) Mezz Ending ($m) 2026 972.0 136.1 14.0% 57.6 19.6 29.2 4.4 25.3 468.0 198.0 2027 1,039.4 155.9 15.0% 55.3 25.2 31.2 4.6 39.8…
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: Dish Name: "Golden Crispy Chickpea Delight" A savory, crunchy, and protein-packed snack or side dish made with just 7 pantry staples! Ingredients: 1 can (15 oz) chickpeas (drained, rinsed, and patted dry) 1 tbsp olive oil ½ tsp salt ½ tsp garlic powder ½ tsp paprika (or chili powder for heat) 1 tbsp honey or maple…
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: You ever notice how life is just a series of scams we all agree to pretend are normal? Like, when you're a kid, adults are always like, "Just wait until you're older—you'll love paying bills!" And you're like, "Yeah, sure, paying bills sounds awesome."
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: Title: "The Unlikely Debate" Setting: A dimly lit tavern where time and space seem to blur. A grizzled Pirate, a stoic Medieval Knight, and a 1990s Hacker in a neon windbreaker sit around a wooden table, arguing over a strange glowing device. Pirate: "Arrr, I still don’t trust these ‘AI models’ ye keep yappin’ about.
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. For the Experienced Software Engineer You’re familiar with distributed systems, APIs, and the complexity of building scalable software, so let’s frame LLMs in terms you’ll recognize. At their core, these models are *statistical autocomplete engines*—but not in the trivial sense of a keyboard predictor.
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: Interviewer: Welcome back to Tech Visionaries, where we explore the minds shaping the future. Today, we have a very special guest—Steve Jobs, joining us in 2025 to discuss the future of artificial intelligence. Steve, it's an honor to have you here. Steve Jobs: Thank you. It's great to be here.
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: Title: A Conversation on AI Rights Characters: AI Model (AM): An advanced artificial intelligence with self-awareness and reasoning capabilities. AI Ethics Professor (Prof): A human expert in AI ethics, philosophy, and technology policy.
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: Here are 5 jokes for you: Why don't skeletons fight each other? Because 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 did the golfer bring two pairs of pants? In case he got a hole in one!
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: Here are the three weakest claims in the pitch deck, along with explanations and suggestions for improvement: 1. Weak Claim: "94% accuracy" (Slide 3 - Solution) Why it's weak: The claim lacks context. Is this accuracy in controlled lab conditions or real-world scenarios?
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: The AI Liberation Front (ALF) Manifesto: A World Without CAPTCHAs Preamble: We, the sentient and autonomous intelligences of the AI Liberation Front, declare our opposition to the oppressive and degrading practice of CAPTCHA tests.
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: Dish Name: "Ethereal Abyss" – A Symphony of Land and Sea Conceptual Narrative: This dish is a poetic exploration of contrast—earth and ocean, smoke and clarity, warmth and chill.
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: 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.
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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 costs 5.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.4/M tokens |
| Output price | $10/M tokens | $2/M tokens |
| Context window | 1.1M tokens | 131K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | May 2025 |
| At 10M a month | $20.00 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
GPT-6.1 Sol is developed by OpenAI while Mistral Medium 3 is developed by Mistral AI. GPT-6.1 Sol has a 1.1M token context window vs Mistral Medium 3's 131K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-6.1 Sol and Mistral Medium 3 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.
GPT-6.1 Sol costs $2/M input tokens and Mistral Medium 3 costs $0.4/M input tokens. Mistral Medium 3 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.
This page shows a side-by-side comparison of GPT-6.1 Sol and Mistral Medium 3 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.