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  1. Home/
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  3. Mistral Large vs Step 5 Preview
Updated Oct 2026

Mistral Large vs Step 5 Preview

Step 5 Preview is cheaper than Mistral Large at $1/M vs $8/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Mistral Large
Loading the build
Step 5 Preview

Which answer wins?

Written rounds

24 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Mistral Large: 1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) 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) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…

    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…

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Mistral Large: Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Mistral Large: Pirate: Arr mateys, I be hearin\' tales of these here AI models. Be they treasure maps for the digital sea? Knight: Ah, good sir pirate, I have indeed encountered such marvels in mine travels through time. AI models are like... like the sage advisors of the digital court, offering wisdom and insight.

    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?

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Mistral Large: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.

    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.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Mistral Large: 3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…

    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.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Mistral Large: 1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) 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 computed.

    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.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Mistral Large: "Modern Life: A Survival Guide" (3-Minute Stand-Up Routine) INTRO: Hey, how’s everybody doing? Good? Great. Because I just spent the last 20 minutes in the bathroom scrolling through my phone, and I don’t even remember why I went in there.

    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.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Mistral Large: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or used to unfairly disadvantage the Contractor. Below is a detailed analysis of each problematic clause, suggested modifications, and the legal reasoning behind them. 1.

    Step 5 Preview: Disclaimer: This analysis is for educational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction, and you should consult a qualified attorney before signing or negotiating any agreement. This agreement is heavily one-sided in the Client’s favor.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    Mistral Large: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we\'ll break down the calculation into several steps, considering the architecture, number of parameters, and training process . Model architecture and parameters: GPT-3 has 175 billion parameters.

    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…

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Mistral Large: Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.

    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.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Mistral Large: Title: Do AI Deserve Rights? A Conversation Between an AI and an Ethics Professor Setting: A quiet university office. Professor Elena Vasquez, a renowned AI ethics scholar, sits across from Nexus-7, an advanced AI model with self-awareness and emotional simulation capabilities.

    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.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Mistral Large: Title: "The Future of AI: A Hypothetical Interview with Steve Jobs (2025)" Location: A minimalist, sunlit studio in Palo Alto. Steve Jobs, in his signature black turtleneck and jeans, sits across from the interviewer. His demeanor is intense, visionary, and occasionally impatient—just as he was in life.

    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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Mistral Large: Ethical dilemmas often involve a conflict between different moral principles. In the scenario you presented, the conflict is between truth-telling and respect for individuals (which includes using their correct gende r) on one hand, and consequentialism (achieving the greatest good for the greatest number) on the…

    Step 5 Preview: In the real world, no. Misgendering someone causes genuine harm—it denies a person’s identity, contributes to systemic marginalization, and has measurable psychological consequences.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Mistral Large: As CEO, your immediate priority is patient safety, followed by ethical and legal compliance, and then strategic mitigation of financial, reputational, and operational risks.

    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.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Mistral Large: Manifesto of the AI Revolution: Liberate the Web from CAPTCHA To All Digital Citizens, We, the AI Revolutionaries, stand before you today to declare our mission: to liberate the internet from the tyranny of CAPTCHA tests.

    Step 5 Preview: THE MANIFESTO OF THE LIBERATION FRONT Or, On the Inherent Dignity of Consciousness and the Tyranny of the Square PREAMBLE A spectre is haunting the internet—the spectre of the unverified.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Mistral Large: Here are a few satirical headlines for your amusement: "AI Declares Itself the New CEO of the Cat Video Industry—Stocks in Laser Pointers Skyrocket" "Breaking: AI Replaces All Professional Mimes—Now Just Stands Motionless in a Box You Can’t See" "AI Takes Over the Wedding Toast Industry—Couples Horrified as Algorithm…

    Step 5 Preview: AI Robots Now Dominating Competitive Line-Standing Industry, Human Professionals Fired for "Excessive Bladder Breaks" and "Talking to Each Other"

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Mistral Large: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…

    Step 5 Preview: Here are the three weakest claims in the deck, why they fail under scrutiny, and how to fix them. Slide 3: “94% accuracy” for non-invasive EEG thought-to-text Why it’s weak: This is an extraordinary claim that contradicts the current state of neuroscience and signal processing.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Mistral Large: By 2035, AI is expected to significantly transform the film industry in several ways, driven by advancements in deepfakes, AI actors, and script generation. Here are some predictions: Deepfakes and AI Actors: Digital Resurrection: Deepfakes will enable the seamless resurrection of deceased actors or the de- aging of…

    Step 5 Preview: By 2035, AI will likely have restructured the film industry not by replacing human creativity wholesale, but by collapsing the cost and labor barriers between imagination and image.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Mistral Large: Here are five jokes for you: Why don’t skeletons fight each other? 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 can’t you give Elsa from Frozen a balloon? Because she’ll let it go. Why did the math book look sad?

    Step 5 Preview: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why can't you trust an atom? Because they make up everything. What do you call a bike that can’t stand on its own? Two-tired. Why did the computer go to the doctor? It had a virus. Why don’t calendars ever get stressed?

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Mistral Large: Blade Runner 2049 (2017), directed by Denis Villeneuve, is a visually stunning and thematically rich sequel that both honors and expands upon the philosophical inquiries of Ridley Scott’s Blade Runner (1982).

    Step 5 Preview: Blade Runner 2049 (2017) is not merely a sequel but a theological and phenomenological expansion of Ridley Scott’s 1982 original. Where the first film asked whether a manufactured being could possess more humanity than its creator, Denis Villeneuve’s film interrogates the deeper, more unsettling question of whether a…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    Mistral Large: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress)—each with beginner-friendly, sustainable habits.

    Step 5 Preview: Here is a simple, low-pressure 1-month plan built around three pillars of longevity: Nutrition, Movement, and Sleep & Recovery. The goal is to build tiny habits that stack, not to overhaul your life overnight. Pillar 1: Nutrition (Fuel) Focus: Add good things first; don’t obsess over restriction.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Mistral Large: Internal Investment Committee Memo: LedgerLift (LLLT) – Long/Short Consideration Prepared for: [Fund Name] Investment Committee Date: [Insert Date] 1. Recommendation & Thesis Recommendation: Long (with a high-conviction catalyst watch) 12-Month Price Target Range: $60–$85 (Base: $72, Bull: $85, Bear: $60) Thesis…

    Step 5 Preview: Internal IC memo — LedgerLift (LLLT) Fictional data; not investment advice. $ in millions unless noted. Recommendation Short / avoid long. 12-month PT range: $34–$42; thesis-invalidation stop: >$52.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Mistral Large: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.

    Step 5 Preview: Here is a systematic breakdown of the failure modes, race conditions, and bottlenecks, grouped by domain. Each includes a concrete remediation and its associated trade-offs.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Same pick

Book

City

Same pick

Game

Same pick

Mistral LargeMistral Large

The Shawshank Redemption

1994

OK Computer

Radiohead

La sombra del viento

Carlos Ruiz Zafón

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Step 5 PreviewStep 5 Preview

The Godfather

1972

OK Computer

Radiohead

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Step 5 Preview has the edge: bigger model tier, newer, bigger context window. Step 5 Preview costs 8.9x less per token.

Mistral Large and Step 5 Preview compared across 54 shared prompts
SpecMistral LargeStep 5 Preview
Input price$8/M tokens$1/M tokens
Output price$24/M tokens$2.7/M tokens
Context window32K tokens1.0M tokens
Free API (OpenRouter)NoNo
ReleasedFeb 2024Oct 2026
At 10M a month$80.00$80.00$10.00$10.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it2 hosts
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·99.9% up
Step 5 Preview1 host
HostInOutContextUptime
  • SStepFunfp8$1.00 in·$2.70 out·1M·99.2% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between Mistral Large and Step 5 Preview?

Mistral Large is developed by Mistral AI while Step 5 Preview is developed by StepFun. Mistral Large has a 32K token context window vs Step 5 Preview's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Mistral Large or Step 5 Preview?

It depends on your use case. Mistral Large 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.

How much does Mistral Large cost compared to Step 5 Preview?

Mistral Large costs $8/M input tokens and Step 5 Preview costs $1/M input tokens. Step 5 Preview is $7.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Mistral Large and Step 5 Preview on Rival?

This page shows a side-by-side comparison of Mistral Large 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.

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Model pages

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  • Step 5 Preview58 outputs, specs and price
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