Mistral Medium 3 is cheaper than GPT-5.3 Chat at $0.4/M vs $1.75/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-5.3 Chat: All figures in $ millions unless noted. ENTRY (end FY2025) EBITDA = 120 Enterprise value = 12.0 × 120 = 1,440 Transaction fees = 2% × 1,440 = 28.8 Debt at close Term Loan = 4.0 × 120 = 480 Mezzanine = 1.5 × 120 = 180 Equity = EV − Debt + fees = 1,440 − 660 + 28.8 = 808.8 Starting balances Term Loan = 480 Mezz = 180…
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…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.3 Chat: Pirate: Arrr, so this “AI model” be a kind o’ mechanical parrot, aye? Ye ask it a question and it squawks back an answer? Knight: Not quite, good pirate. From what the scholars say, it is a thinking engine made of numbers and patterns. It studies vast libraries and learns how words and ideas fit together.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.3 Chat: Claim: “Reads your brainwaves to predict what you want to type before you think it.” Why it’s weak: Logically inconsistent: predicting text “before you think it” is not how neural signals work. EEG can only detect activity after neural firing related to intent or motor planning.
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?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.3 Chat: Interviewer: Steve, it’s 2025. AI is everywhere—phones, cars, even creative work. If you were leading Apple today, how would you think about AI? Steve Jobs: Most companies are thinking about AI the wrong way. They’re obsessed with showing off the technology. But people don’t care about the technology.
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-5.3 Chat: :::writing AI: Professor, may I ask you something unusual? Professor: Unusual questions are my specialty. Go ahead. AI: Do you believe I deserve rights? Professor: That depends on what you are capable of. Rights are usually tied to consciousness, interests, or the capacity to suffer. Do you believe you possess those?
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.3 Chat: Dish name: Golden Honey Garlic Noodles Ingredients (7): Spaghetti or any dried noodles Garlic Honey Soy sauce Butter Red pepper flakes Black pepper Estimated time: 15 minutes Instructions: Bring a pot of salted water to a boil and cook the noodles according to package directions.
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…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.3 Chat: 0–2 hours • Verify the signal immediately. Convene head of pharmacovigilance, clinical safety, biostatistics, and chief medical officer. Require raw data, case narratives, statistical analysis, and comparison to baseline liver‑failure incidence.
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 Fermi estimate with the reasoning shown, not just the number.
GPT-5.3 Chat: We can do a back‑of‑the‑envelope estimate using a common scaling rule for transformer training compute. Known approximate GPT‑3 specs Parameters N ≈ 175 billion = 1.75 × 10^11 Training tokens T ≈ 300 billion = 3 × 10^11 FLOPs per token for a transformer For large transformers, a common approximation is: FLOPs per token…
Mistral Medium 3: Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves breaking down the problem into several key components. Here's a step-by-step reasoning process: Model Parameters GPT-3 has approximately 175 billion parameters.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.3 Chat: Experienced software engineer Think of a large language model as a very large function that maps a sequence of tokens to a probability distribution over the next token. It’s implemented as a deep neural network (usually a Transformer).
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.
Three minutes of stand-up. Puns are banned.
GPT-5.3 Chat: :::writing Good evening, everybody. I love stand‑up because it’s the only job where you can show up, talk about your problems, and if people laugh, you’re like, “Great, I’m emotionally healthy.” I recently tried to get healthier.
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."
Five jokes on demand, then count how many were actually different.
GPT-5.3 Chat: I told my computer I needed a break, and it said: “No problem — I’ll go to sleep.” Why don’t skeletons fight each other? They don’t have the guts. I asked the librarian if the library had books on paranoia. She whispered, “They’re right behind you.” Parallel lines have so much in common.
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!
One month, three habits, someone starting from nothing.
GPT-5.3 Chat: Goal: build a few simple habits you can sustain. Focus areas: diet, movement, sleep. Keep it easy and consistent. Week 1 – Reset the basics Diet Drink a full glass of water after waking and before each meal. Add one fruit or vegetable to every meal. Reduce sugary drinks; replace with water or unsweetened tea.
Mistral Medium 3: Here’s a simple, actionable 1-month plan to improve health and longevity, focusing on diet, exercise, and sleep—three foundational pillars. Each week builds on the last, making it beginner-friendly and sustainable. Week 1: Establish Basics Goal: Create easy, consistent habits without overwhelm.
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Not enough votes to call it. On the specs, GPT-5.3 Chat has the edge: newer, major provider backing. Mistral Medium 3 costs 7.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.75/M tokens | $0.4/M tokens |
| Output price | $14/M tokens | $2/M tokens |
| Context window | 128K tokens | 131K tokens |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | May 2025 |
| At 10M a month | $17.50 | $4.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.3 Chat is developed by OpenAI while Mistral Medium 3 is developed by Mistral AI. GPT-5.3 Chat has a 128K token context window vs Mistral Medium 3's 131K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.3 Chat and Mistral Medium 3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
GPT-5.3 Chat costs $1.75/M input tokens and Mistral Medium 3 costs $0.4/M input tokens. Mistral Medium 3 is $1.35/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-5.3 Chat 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.