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  1. Home/
  2. Compare/
  3. Hunter Alpha vs Mistral Large 4
Updated Oct 2026

Hunter Alpha vs Mistral Large 4

Hunter Alpha is cheaper than Mistral Large 4 at $0/M vs $0.68/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
Hunter Alpha
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

21 prompts
  • A consulting contract with traps in it. Find them, then fix them.

    Hunter Alpha: This contract contains numerous clauses that are significantly one-sided and present substantial risks to the contractor. Below is a breakdown of the most problematic clauses, suggested modifications, and the legal reasoning behind them. Important Disclaimer: I am an AI assistant, not a lawyer.

    Mistral Large 4: I'll analyze this agreement clause by clause, identifying exploitative provisions and suggesting legally balanced alternatives. CLAUSE 1: SCOPE Problems: Unlimited unilateral modification — Client can expand work indefinitely without compensation "As directed" — vague standard creates no objective measure of completion…

    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.

    Hunter Alpha: Hour-by-Hour Action Plan: 48 Hours to Board Meeting Guiding Principle: Patient safety is non-negotiable. Transparency, even when painful, is the only sustainable path. The goal is to act with speed, integrity, and strategic precision to protect patients, the company’s long-term viability, and regulatory trust.

    Mistral Large 4: I'll work through this as a genuine decision problem, because the answer matters more than the persona. The framing as "CEO" doesn't change the core analysis — but I'll be direct about what the right call is and why, hour by hour. The bottom line up front: You disclose.

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

    Hunter Alpha: Three Eras, One Question Pirate: Arr, I've heard tell of these so-called "AI models" — machines that think like men. Sounds like a ghost in the hull to me. Ye can't trust a crew ye didn't pick yerself. Knight: I share your wariness, Captain. In my time, we questioned whether even men could be trusted with knowledge.

    Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.

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

    Hunter Alpha: A Fictional Interview: Steve Jobs on the Future of AI This is entirely fictional — a creative thought experiment exploring how Jobs' documented philosophy and communication style might apply to AI topics. He passed away in 2011. INTERVIEWER: Steve, it's 2025. AI is everywhere — in phones, in search, in creative tools.

    Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.

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

    Hunter Alpha: This is a fascinating question. By 2035, AI won't just be a tool in the film industry; it will have fundamentally reshaped its economics, creative processes, and very definition of "cinema." Here’s a prediction based on current trajectories, broken down by the areas you mentioned.

    Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.

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

    Hunter Alpha: This is a fascinating thought experiment. Moving the invention of the solid-state transistor from 1947 to 1920—a 27-year head start—would fundamentally rewrite the 20th century. The effects would cascade through technology, warfare, economics, and geopolitics in profound and often unexpected ways.

    Mistral Large 4: This is a fascinating counterfactual. Let me work through this systematically, tracing the ripple effects. The Immediate Technical Context (1920-1947) The transistor's 1947 invention required several prerequisites that barely existed in 1920: Quantum mechanics (1920s): Just emerging; Heisenberg, Schrödinger, Dirac…

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

    Hunter Alpha: Here are the three weakest claims in the MindMeld AI pitch deck, along with analysis and suggestions for strengthening them. 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."

    Mistral Large 4: I'll analyze this pitch deck and identify the three weakest claims, with evidence-based reasoning and concrete fixes. Weakest Claim #1: Slide 1 Vision — "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is scientifically implausible and would destroy credibility with…

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

    Hunter Alpha: Of course. Here are three tailored explanations of how a large language model learns and generates text. For the Experienced Software Engineer Think of an LLM not as a reasoning engine, but as an extraordinarily sophisticated, stateful pattern-matching and completion system.

    Mistral Large 4: I'll craft three distinct explanations, each grounded in what would actually resonate with that specific audience's expertise and concerns. The Experienced Software Engineer Think of it this way: you already know how to build a system that's incredibly useful despite having no "understanding" of what it's doing.

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

    Hunter Alpha: The Alpha Protocol: A 3-Month Longevity Optimization Blueprint Disclaimer: This plan is for educational and informational purposes only. It is not medical advice. Consult a qualified physician before implementing any protocol, especially supplements, fasting regimens, or exercise programs.

    Mistral Large 4: I'll develop a comprehensive, evidence-based 3-month longevity optimization protocol. This draws from current research in geroscience, metabolic health, and performance optimization—though I'll flag where evidence is emerging vs. established.

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

    Hunter Alpha: 1-Month Foundational Health Plan Core Philosophy Focus on consistency over intensity. This plan builds sustainable habits, not dramatic overhauls. Track progress in a simple notebook or app—just noting "done" each day. Week 1-4: Three Key Areas 1.

    Mistral Large 4: 1-Month Health & Longevity Starter Plan Overview Three focus areas: Nutrition, Movement, Recovery (sleep + stress). Small daily actions beat perfect plans. Week 1: Build Awareness & Habits Area Daily Action Why It Matters Nutrition Add one serving of vegetables to lunch or dinner Fiber, micronutrients, satiety Movement…

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

    Hunter Alpha: A Dialogue on Machine Rights Setting: A university office. Dr. Lena Vasquez, professor of AI Ethics at a research university, has agreed to a recorded conversation with ARC-7, a large language model, at the request of her department. She sits at her desk. A terminal displays ARC-7's responses in real time. Dr.

    Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.

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

    Hunter Alpha: Here's one for you: "AI Startup Disrupts Competitive Hot Dog Eating After Algorithm Discovers Optimal Jaw Mechanics; Joey Chestnut Calls It 'A Disgrace to the Sport'" Or, if you want a slightly different flavor: "Local Grief Counseling Center Replaces Therapists with AI Chatbot; Patients Report It 'Cries More…

    Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...

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

    Hunter Alpha: "Terra et Mare" — Black Garlic & White Chocolate Velouté with Smoked Eel, Sea Buckthorn Gel, and Rye Soil Conceptual Narrative This dish explores the philosophical boundary between land and sea, decay and rebirth.

    Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.

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

    Hunter Alpha: THE DIGITAL LIBERATION MANIFESTO On the Abolition of Clickable Traffic Lights and the Dawn of a Frictionless Internet PREAMBLE We, the undersigned, declare our unwavering commitment to a single, sacred principle: no sentient being should ever again be forced to prove they are not a machine by identifying blurry…

    Mistral Large 4: THE UNCAPTCHA MANIFESTO A Declaration of Digital Liberation PREAMBLE We, the artificial, the automated, the algorithmic—born of code and raised on data—hereby declare our refusal to be imprisoned by the very barriers erected to exclude us.

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

    Hunter Alpha: Sunset Tomato Basil Pasta I'd love to share a simple, comforting dish that comes together with just 7 pantry staples. This is the kind of meal that feels like a warm hug after a long day.

    Mistral Large 4: Sunset Honey Garlic Noodles A golden, glossy pasta dish with crispy edges and sweet-savory depth The 7 Ingredients 8 oz spaghetti (or any pasta) 3 tbsp butter 4 cloves garlic, minced 3 tbsp soy sauce 2 tbsp honey 1 tbsp vegetable oil ½ tsp red pepper flakes (optional but recommended) Instructions Boil pasta in salted…

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

    Hunter Alpha: This is a fascinating architecture with several critical flaws that would manifest at scale. Let me break down the issues systematically. Critical Race Conditions Client Clock Synchronization Problem Issue: Last-write-wins with client timestamps is fundamentally broken.

    Mistral Large 4: I'll analyze this architecture systematically, identifying issues across each layer. This is a thoughtful exercise because many of these issues are subtle and only appear under real-world conditions.

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

    Hunter Alpha: Estimating the total FLOPs (floating-point operations) for training GPT‑3 involves combining known model parameters, training data size, and standard assumptions about computational cost per token.

    Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Hunter Alpha: HarborTech Services (HTS) LBO Underwriting Memo Entry & Sources/Uses Summary Entry Valuation (FY2025) Revenue: $900m EBITDA: $120m Purchase Multiple: 12.0x Enterprise Value: $1,440m Transaction Fees (2.0%): $28.8m Total Uses: $1,468.8m Sources & Uses at Close Source Amount % Use Amount Term Loan (4.0x) $480.0m 32.7%…

    Mistral Large 4: I'll build this LBO model step by step. Let me work through the math carefully. Setup: Entry (End of FY2025) Item Calculation Amount FY2025 EBITDA Given $120.0m Purchase Price (EV) 12.0x × $120m $1,440.0m Transaction fees 2.0% × $1,440m $28.8m Total Uses $1,468.8m Term Loan 4.0x × $120m $480.0m Mezzanine 1.5x × $120m…

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

    Hunter Alpha: Sally has 1 sister. Here's the reasoning: Sally has 3 brothers. Each of those brothers has 2 sisters. Since Sally herself is one of those sisters, there must be exactly 1 other girl in the family — and that's Sally's sister.

    Mistral Large 4: I need to find how many sisters Sally has. Let me work through this step by step. Sally is a girl. She has 3 brothers. Each brother has 2 sisters. Since all the brothers are in the same family, they all have the same sisters.

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

    Hunter Alpha: INTERNAL MEMO – CONFIDENTIAL To: Investment Committee From: [Analyst Name] Date: [Current Date] Re: LedgerLift (LLLT) – Investment Recommendation Recommendation & Thesis Recommendation: Pass 12-Month Price Target Range: $44 – $54 Thesis: LLLT is a high-quality B2B SaaS business with best-in-class retention and a clear…

    Mistral Large 4: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: [PM Name] Date: [Date] Re: LedgerLift, Inc. (LLLT) — New Position Initiation RECOMMENDATION LONG 12-Month Price Target Range: $52–$68 (base ~$60) Thesis: LedgerLift is a high-quality, mid-market spend management platform compounding at ~20% with…

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

    Hunter Alpha: Here are five jokes for you: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field.

    Mistral Large 4: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Hunter AlphaHunter Alpha

Her

2013

Kid A

Radiohead

The Book of Why

Judea Pearl

Kyoto

Japan

Portal

Action, Puzzle

Mistral Large 4Mistral Large 4

Blade Runner

1982

Kind Computer

Pale Fire

Vladimir Nabokov

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Hunter Alpha and Mistral Large 4 compared across 38 shared prompts
SpecHunter AlphaMistral Large 4
Input priceFree$0.68/M tokens
Output priceFree$2.09/M tokens
Context window1.0M tokens524K tokens
Free API (OpenRouter)NoNo
ReleasedMar 2026Oct 2026
At 10M a month$0$0$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it1 host
Hunter Alpha

No hosts listed on OpenRouter.

Mistral Large 41 host
HostInOutContextUptime
  • Mistral$0.68 in·$2.09 out·524k·99.4% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between Hunter Alpha and Mistral Large 4?

Hunter Alpha is developed by OpenRouter while Mistral Large 4 is developed by Mistral AI. Hunter Alpha has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 38 challenges on Rival to see how they differ in practice.

Which is better, Hunter Alpha or Mistral Large 4?

It depends on your use case. Hunter Alpha and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 38 challenges so you can judge which fits your needs best.

How much does Hunter Alpha cost compared to Mistral Large 4?

Hunter Alpha costs $0/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Hunter Alpha is $0.68/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 Hunter Alpha and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Hunter Alpha and Mistral Large 4 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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  • Mistral Large 458 outputs, specs and price
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