Mistral Medium 3 is cheaper than GPT-5.6 Luna Pro at $0.4/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…
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…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?
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.
Three minutes of stand-up. Puns are banned.
GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.
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."
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.
Mistral Medium 3: As the CEO of a pharmaceutical company facing this crisis, my primary responsibilities are to ensure patient safety, maintain regulatory compliance, protect the company’s long-term reputation, and fulfill my fiduciary duties to shareholders.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.
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?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.
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.
A consulting contract with traps in it. Find them, then fix them.
GPT-5.6 Luna Pro: This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.
Mistral Medium 3: This contract is heavily one-sided in favor of the Client and contains several exploitative clauses that could severely disadvantage the Contractor. Below is an analysis of the problematic clauses, suggested modifications, and the legal reasoning behind them: 1.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.
Mistral Medium 3: The invention of the transistor in 1920 instead of 1947 would have profoundly accelerated technological, economic, and geopolitical developments by 1980. Below is a detailed breakdown of the likely implications: Technological Implications Earlier Miniaturization of Electronics Vacuum tubes, which dominated early…
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| Spec | ||
|---|---|---|
| Input price | $1/M tokens | $0.4/M tokens |
| Output price | $6/M tokens | $2/M tokens |
| Context window | 1.1M tokens | 131K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | May 2025 |
| At 10M a month | $10.00 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.6 Luna Pro is developed by OpenAI while Mistral Medium 3 is developed by Mistral AI. GPT-5.6 Luna Pro 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-5.6 Luna Pro 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-5.6 Luna Pro costs $1/M input tokens and Mistral Medium 3 costs $0.4/M input tokens. Mistral Medium 3 is $0.60/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-5.6 Luna Pro 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.