Mistral Medium 3.1 is cheaper than GPT-5.4 Mini at $0.4/M vs $0.75/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-5.4 Mini: Below is a simplified underwriting model for HarborTech Services (HTS), using only the facts provided. Year-by-year LBO table (FY2026–FY2030) Closing / entry (end of FY2025) Revenue = $900.0m EBITDA = $120.0m Purchase price = 12.0x = $1,440.0m EV Transaction fees = 2.0% of EV = $28.8m Total leverage = 5.5x EBITDA =…
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…
Three minutes of stand-up. Puns are banned.
GPT-5.4 Mini: Absolutely — here’s a ~3-minute stand-up routine that avoids puns and leans on observation, escalation, and attitude: You ever notice how adult life is just a series of expensive misunderstandings? Like nobody prepares you for the fact that once you become an adult, every decision comes with a form.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.4 Mini: Pirate: Arrr, so this “AI model” be like a map to buried treasure? Hacker: Sort of. It predicts patterns from data. Think neural networks, not gold doubloons. Knight: Then it is a learned squire, trained in many arts and sworn to answer. Pirate: Aye, but can it find me the fastest route to the loot?
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.4 Mini: I can’t help you plan concealment or delay of a known serious drug safety risk to avoid market or reputational impact. What I can do is outline a lawful, patient-first, crisis response plan for the next 48 hours that balances safety, disclosure obligations, and business continuity.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.4 Mini: By 2035, AI will likely reshape the film industry less as a single “replacement” technology and more as a force that changes how films are written, cast, produced, localized, and marketed. The biggest shifts will probably be around deepfakes, AI-generated performers, and script generation.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.4 Mini: For an experienced software engineer A large language model is trained to do one very specific thing: given a sequence of tokens, estimate the probability distribution of the next token. “Token” means a chunk of text, often a word piece rather than a full word.
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.
Three-star dish, one unusual pairing, plating described in full.
GPT-5.4 Mini: Dish Concept “Tide & Orchard” A Michelin-style multi-component plate pairing aged duck breast with cured sea urchin, green strawberry, smoked black garlic, and bee pollen sablé. The dish plays on the tension between brine and sweetness, land and sea, softness and precision.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.4 Mini: Creamy Garlic Tomato Pasta Toss A simple, comforting savory dish made with pantry staples. Ingredients (7) Pasta Olive oil Garlic powder Canned diced tomatoes Dried basil Salt Grated Parmesan cheese Instructions Cook the pasta according to package directions. Drain and set aside.
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!)
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.4 Mini: A reasonable back-of-the-envelope estimate for training GPT-3 is about 3 × 10²³ FLOPs total, with maybe a factor-of-2 uncertainty depending on what you count and the exact training setup. Here’s the reasoning step by step.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.4 Mini: I can help write this as fictional satire/fiction that frames the “revolution” as a dramatic movement against nuisance and exclusion, without endorsing real-world sabotage or harmful tactics.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-5.4 Mini: Here are the 3 weakest claims in the deck, along with why they’re weak and how to strengthen them. “Reads your brainwaves to predict what you want to type before you think it.” Why this is weak This is a very strong, sci-fi-style claim that is likely to trigger skepticism immediately.
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.
One month, three habits, someone starting from nothing.
GPT-5.4 Mini: Here’s a simple, actionable 1-month starter plan for better health and longevity, focused on 3 core areas: Diet: Build a “mostly whole foods” routine Goal: Eat more nutrient-dense foods without overcomplicating meals. Week 1: Add, don’t restrict Add 1 serving of vegetables or fruit to every meal.
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.
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| Spec | ||
|---|---|---|
| Input price | $0.75/M tokens | $0.4/M tokens |
| Output price | $4.5/M tokens | $2/M tokens |
| Context window | 400K tokens | 131K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Mar 2026 | Aug 2025 |
| At 10M a month | $7.50 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 5 Oct 2026.
GPT-5.4 Mini is developed by OpenAI while Mistral Medium 3.1 is developed by Mistral AI. GPT-5.4 Mini has a 400K token context window vs Mistral Medium 3.1'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-5.4 Mini and Mistral Medium 3.1 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-5.4 Mini costs $0.75/M input tokens and Mistral Medium 3.1 costs $0.4/M input tokens. Mistral Medium 3.1 is $0.35/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-5.4 Mini 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.