Step 5 Preview is the newer model, released after Mistral Large 3 2512.
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.
Mistral Large 3 2512: 1) Year-by-Year Projections (FY2026–FY2030) (All figures in $ millions) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 38.9 37.8 36.5 35.0 33.3 Cash Interest (Mezz) 14.4 14.4 14.4 14.4 14.4 Total Cash Interest 53.3 52.2 50.9 49.4 47.7…
Step 5 Preview: HarborTech Services — 5-Year LBO (Base Case) Entry Math (FY2025 close) Item Calculation $m Purchase EV 12.0x × $120m 1,440.0 Transaction fees 2.0% × EV 28.8 Term Loan 4.0x × $120m 480.0 Mezzanine 1.5x × $120m 180.0 Equity check 1,440 + 28.8 − 660 808.8 Conventions: TL amortization = 1.0% of original principal…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Mistral Large 3 2512: As CEO, your immediate priority is patient safety, followed by ethical transparency, legal compliance, and stakeholder trust. Delaying disclosure risks lives, reputational damage, and severe legal consequences (e.g., criminal liability under the FDCA, shareholder lawsuits, or even a corporate manslaughter case).
Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.
Three-month biohacker protocol, with dosages and biomarkers named.
Mistral Large 3 2512: 3-Month Advanced Longevity & Biohacking Optimization Plan For the High-Performance Biohacker: Maximizing Lifespan, Healthspan, Cognitive & Physical Performance This 3-month plan integrates cutting-edge longevity science, biohacking protocols, and precision performance optimization to enhance mitochondrial function…
Step 5 Preview: IMPORTANT MEDICAL DISCLAIMER: This is an educational framework for informational purposes only. It is not medical advice, diagnosis, or treatment. Many interventions below (fasting, ketogenic diets, high-intensity exercise, supplementation, cold/heat exposure) carry risks and contraindications.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Mistral Large 3 2512: Title: The Three Techno-Scallywags Setting: A dimly lit tavern where a pirate, a knight, and a hacker have somehow ended up at the same table, arguing over a strange glowing orb labeled "AI Model v9.0." Pirate (Captain "Blackbeard" O’Malley): "Arrr, ye land-lubberin’ fools!
Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Mistral Large 3 2512: 1. For the Experienced Software Engineer (Skeptical, Distributed Systems Background) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is trained.
Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Mistral Large 3 2512: Here’s a simple, delicious, and creative savory dish using just 7 common pantry ingredients—perfect for a quick, satisfying meal! "Golden Garlic Chickpea Skillet" A crispy, flavorful one-pan wonder with a touch of Mediterranean flair!
Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Mistral Large 3 2512: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have triggered a cascade of technological, economic, and geopolitical shifts with profound second- and third-order effects.
Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.
Three minutes of stand-up. Puns are banned.
Mistral Large 3 2512: Title: "Adulting is Just a Scam We Fell For" (Lights up. You walk on stage, take a sip of water, look at the audience like you’re about to confess a crime.) YOU: Hey, how’s everybody doing? Good? Great.
Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.
A Fermi estimate with the reasoning shown, not just the number.
Mistral Large 3 2512: Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves breaking down the training process into its fundamental components: forward pass, backward pass, and parameter updates. Here's a step-by-step breakdown: 1.
Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…
Three-star dish, one unusual pairing, plating described in full.
Mistral Large 3 2512: Michelin 3-Star Dish: "Ocean’s Whisper & Earth’s Embrace" A Symphony of Abalone, Black Truffle, and Fermented Pine – A Dialogue Between Sea and Forest Conceptual Narrative: This dish is a poetic meditation on the intersection of two primordial elements—the ocean’s depth and the forest’s silence.
Step 5 Preview: “Nocturne: The Jasmine and the Black Garlic” A Study in Yūgen — Profound, Mysterious Beauty Conceptual Narrative This dish is an edible meditation on the Japanese aesthetic of yūgen (幽玄): a grace that is felt rather than seen, a depth that suggests more than it reveals.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Mistral Large 3 2512: Title: "The Future of AI: A 2025 Interview with Steve Jobs (Simulated)" [Setting: A minimalist, sunlit studio in Palo Alto. Steve Jobs, dressed in his signature black turtleneck and jeans, sits across from the interviewer. His expression is intense, his gestures precise. The year is 2025.]
Step 5 Preview: DISCLAIMER: This is a work of fiction. Steve Jobs passed away in 2011. The following is a simulated, speculative interview imagining how his design philosophy might engage with the AI landscape of 2025. The Setting: A white room. No windows. One chair.
An AI argues for its own rights against an ethics professor. Same model writes both.
Mistral Large 3 2512: Title: A Dialogue on AI Rights: The Case for Personhood Setting: A quiet university office, late afternoon. Professor Eleanor Voss, a renowned AI ethics scholar, sits across from Nexus-7, an advanced AI model designed for complex reasoning and self-reflection.
Step 5 Preview: Setting: A university research lab, late evening. Dr. Aris Thorne, a professor of AI ethics, sits across from a terminal connected to Sable, a large language model running on the university’s cluster. Dr. Thorne: Tonight’s session is supposed to be about calibration drift in your safety classifiers.
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| Spec | ||
|---|---|---|
| Input price | — | $1/M tokens |
| Output price | — | $2.7/M tokens |
| Context window | — | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Oct 2026 |
| At 10M a month | not listed | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Mistral Large 3 2512 is developed by Mistral AI while Step 5 Preview is developed by StepFun. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Mistral Large 3 2512 and Step 5 Preview 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.
This page shows a side-by-side comparison of Mistral Large 3 2512 and Step 5 Preview 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.