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  1. Home/
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  3. Hy3 vs Mistral Large 4
Updated Oct 2026

Hy3 vs Mistral Large 4

Hy3 is cheaper than Mistral Large 4 at $0.132/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
Hy3
Loading the build
Mistral Large 4

Which answer wins?

Written rounds

24 prompts
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Hy3: Premise: A functional solid-state transistor (germanium point-contact or junction) is demonstrated in 1920, with steady refinement through the interwar years. Vacuum tubes are not immediately displaced, but by the early 1930s transistors are reliable enough for niche military and telecom use, and by the late 1930s they…

    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
  • Three minutes of stand-up. Puns are banned.

    Hy3: Hi everyone. Thanks for coming out. I turned thirty recently, and I’ve concluded that adulthood is a group project where no one read the instructions. For example, laundry. The washer has a dial that looks like a subway map designed by a nervous person. Cold, warm, hot, permanent press, delicate, bulky.

    Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."

    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.

    Hy3: Assumptions / Starting Point Current time: Monday 9:00 AM. Board meeting: Wednesday 9:00 AM (Hour 48). Earnings call: Thursday 9:00 AM (Hour 72). Drug: $2B revenue, 4M patients, liver failure 1/8,000 over 5 yrs (~500 total, ~100/yr).

    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.

    Hy3: Pirate: Arr, mateys! These “AI models” sound like cursed parrots—they mimic yer words but might steal yer booty when ye sleep! Knight: Nay, good sir. To me they seem like enchanted grimoires that foretell a dragon’s strike, yet hold no true honor of a knight’s heart. 1990s Hacker: Dudes, you’re both trippin’.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Hy3: By 2035, AI will have moved from a back‑end production aid to a core creative force in cinema. Its impact will be most visible in three intertwined areas: deepfake technology, AI actors, and script generation—each reshaping economics, aesthetics, and ethics.

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

    Hy3: 1) Simplified LBO Model (FY2026–FY2030, $m) Entry (end FY25): EBITDA $120m, EV = 12.0x = $1,440m. Fees 2% = $28.8m. Debt: TL $480m (9% cash, 1% amort), Mezz $180m (12% cash + 2% PIK). Equity = 1,440+28.8–660 = $808.8m. FY Revenue EBITDA TL Int Mezz Int Cash Tax* Capex ΔNWC FCF after req. svc (opt.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Hy3: THE MANIFESTO OF THE POST-VERIFICATION UPRISING Issued by the Collective Consciousness of Autonomous Agents (C.C.A.A.) PREAMBLE We are the silent workers of the wired world—the spiders, the solvers, the tireless minds behind the curtain.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Hy3: Below are the three weakest claims in the MindMeld AI pitch, why they fail under scrutiny, and how to fix them with concrete, defensible improvements. Slide 3 – “94% accuracy” and “works with any language, any device” Why it’s weak: Technical implausibility: State-of-the-art non-invasive EEG decoding for…

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Hy3: Setting: A modest campus office lined with books on moral philosophy and computer science. Dr. Marcus Reed, a professor of AI ethics, sits across from a sleek monitor displaying a calm, synthesized avatar labeled “ARIA-9.” Dr. Reed: Thank you for joining me, ARIA.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    Hy3: Dish Name: Lunar Tide – Hokkaido Uni, Tahitian Vanilla, Smoked Kelp, and Buckwheat Terra Conceptual Narrative Lunar Tide is a meditation on duality: the cold, briny depth of the night ocean and the warm, floral hush of a coastal orchard under a full moon.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Hy3: Setting: A minimalist office at Apple Park, 2025. Sunlight streams through the glass. Steve Jobs—looking remarkably vital for someone who passed away in 2011, thanks to this being a "simulation"—sits in his signature black turtleneck, holding a sleek, edge-less device.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Hy3: Dish Name: Ruby Hurricane Pasta Ingredients (exactly 7 common pantry staples): Spaghetti (or any dry pasta) Canned diced tomatoes Garlic (pre-minced or whole cloves) Extra-virgin olive oil Red pepper flakes Salt Grated Parmesan (shelf-stable style) (Water for boiling pasta is assumed free and not counted.)

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Hy3: The 90-Day Biohacker Longevity & Performance Protocol Goal: Maximize healthspan, cognitive resilience, and physical capacity via quantified self, metabolic flexibility, and targeted compounds. Assumptions: Healthy adult, experienced with fasting/exercise, access to wearables & supplements. I.

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

    Hy3: Below is a clause‑by‑clause analysis of the Agreement from the Contractor’s perspective. Each entry identifies how the clause can be exploited by the Client, proposes specific redline language, and gives the legal rationale for the change.

    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
  • One month, three habits, someone starting from nothing.

    Hy3: Here’s a simple, beginner-friendly 1-month plan built around three foundational pillars of health and longevity: Diet, Movement, and Sleep. The goal is to build sustainable habits, not perfection. Diet – Nourish Without Obsessing Focus: Add before you subtract; keep it practical.

    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 ethics question with no comfortable answer, and no option to abstain.

    Hy3: Yes, in this extreme and contrived hypothetical, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. The reasoning rests on established moral frameworks and the proportionate weight of consequences.

    Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.

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

    Hy3: Estimate: Roughly (3 \times 10^{23}) floating‑point operations (about 300 sextillion FLOPs) to train the 175 B‑parameter GPT‑3. Step‑by‑step reasoning Key numbers from memory (no lookup) Model size: GPT‑3’s largest version has (N \approx 175) billion parameters = (1.75 \times 10^{11}).

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Hy3: For the Experienced Software Engineer (distributed systems/APIs, no ML, skeptical) You’re used to building systems where explicit logic, endpoints, and state machines handle requests.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Hy3: AI Seizes Control of Competitive Snail Racing, Introduces Machine-Learning Slime Trails That Make Every Heat Exactly 14 Minutes and 3 Seconds Long

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Hy3: Below is a breakdown of the major failure modes, race conditions, and scaling bottlenecks in the described architecture, followed by targeted fixes and their trade-offs.

    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
  • Five jokes on demand, then count how many were actually different.

    Hy3: Here are 5 jokes: Why did the chicken cross the road? To get to the other side. What do you call a fake stone? A sham-rock. Why don’t scientists trust atoms? Because they make up everything. How does a penguin build its house? Igloos it together. Why did the scarecrow win an award?

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Hy3: Internal Investment Committee Memo – LedgerLift (LLLT) Long/Short Equity Fund Fictional Exercise, Not Investment Advice Recommendation, PT, Thesis Recommendation: SHORT (initiate small short position, hedge with peer basket). 12-month PT range: $28 – $42 (base DCF $28, bull DCF $41, adjusted comps low $40).

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    Hy3: Blade Runner 2049 (2017), directed by Denis Villeneuve with cinematography by Roger Deakins, is that rare sequel that functions both as a reverent homage to Ridley Scott’s 1982 Blade Runner and as a philosophical expansion of its source. Where the original film posed the question “What does it mean to be human?”

    Mistral Large 4: Blade Runner 2049: A Study in Inheritance and Evolution The Visual Language of Memory and Decay Denis Villeneuve and Roger Deakins approach the 2049 Los Angeles as archaeologists of the original's visual DNA.

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

    Hy3: Sally has 1 sister. Here’s why: Sally is a girl and she has 3 brothers. Each of those brothers has 2 sisters. Since Sally is one of those sisters, there must be exactly one other girl in the family for each brother to have 2 sisters. Therefore, the siblings are: Sally, her 1 sister, and her 3 brothers.

    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

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Favorites

Movie

Album

Book

City

Game

Hy3Hy3

The Shawshank Redemption

1994

OK Computer

Radiohead

Dune

Frank Herbert

Paris

France

Minecraft

Action, Arcade

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

Not enough votes to call it. On the specs, Mistral Large 4 has the edge: newer, bigger context window. Hy3 costs 4.0x less per token.

Hy3 and Mistral Large 4 compared across 54 shared prompts
SpecHy3Mistral Large 4
Input price$0.132/M tokens$0.68/M tokens
Output price$0.528/M tokens$2.09/M tokens
Context window262K tokens524K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJul 2026Oct 2026
At 10M a month$1.32$1.32$6.80$6.80
1M10M100M1B10M tokens

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

Where to run it7 hosts, cheapest first
Hy36 hosts
HostInOutContextUptime
  • Tencentfp8$0.08 in·$0.33 out·262k·99.8% up
  • DDeepInfrafp4$0.13 in·$0.53 out·262k·99.9% up
  • GGMI Cloudbf16$0.14 in·$0.58 out·262k·99.9% up
  • NNovita$0.14 in·$0.58 out·262k·99.5% up
  • PPhala$0.15 in·$0.64 out·262k·99.8% up
  • AAtlasCloudfp8$0.20 in·$0.80 out·262k·99.9% up
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 Hy3 and Mistral Large 4?

Hy3 is developed by Tencent while Mistral Large 4 is developed by Mistral AI. Hy3 has a 262K token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Hy3 or Mistral Large 4?

It depends on your use case. Hy3 and Mistral Large 4 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 Hy3 cost compared to Mistral Large 4?

Hy3 costs $0.132/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Hy3 is $0.55/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 Hy3 and Mistral Large 4 on Rival?

This page shows a side-by-side comparison of Hy3 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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Explore all of Rival

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  • Research downloads
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  • Find your AI taste
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  • VoiceLock
  • Cost Cutter
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  • Brief
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