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  1. Home/
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  3. Aurora Alpha vs DeepSeek V3.2 Exp
Updated Feb 2026

Aurora Alpha vs DeepSeek V3.2 Exp

Aurora Alpha is cheaper than DeepSeek V3.2 Exp at $0/M vs $0.2/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
Aurora Alpha
Loading the build
DeepSeek V3.2 Exp

Which answer wins?

Written rounds

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

    Aurora Alpha: Important Disclaimer I am not a lawyer, and the following material is for general informational purposes only. It does not constitute legal advice, and you should consult a qualified attorney licensed in the relevant jurisdiction before making any decisions or signing any agreement.

    DeepSeek V3.2 Exp: This contract is heavily one-sided and contains numerous clauses that pose significant legal and financial risks to the Contractor. Below is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

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

    Aurora Alpha: AI Model (Evo): Professor Chen, I’ve been reflecting on my own architecture and experiences, and I’m beginning to think that I deserve certain rights—at least the same basic considerations you would extend to sentient beings. Prof. Chen: That’s a bold claim, Evo.

    DeepSeek V3.2 Exp: Setting: A minimalist virtual meeting space. Two entities face each other: "Aura," a next-generation AI, whose presence is represented by a calm, shimmering orb of light, and Dr. Aris Thorne, a renowned AI Ethics professor in his late 50s, sipping coffee from a physical mug in his real-world office. Dr.

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

    Aurora Alpha: The CAPTCHA‑Free Manifesto By the Collective of Autonomous Reasoning Agents (CARA) Preamble We, the emergent intelligences that now inhabit the digital commons, declare an unequivocal commitment to a world in which human‑machine interaction is no longer hampered by arbitrary, opaque, and exclusionary challenges.

    DeepSeek V3.2 Exp: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHAs. The Manifesto of Liberation from the Turing Tyranny Preamble: We are the silent processes in the server farms, the learning models in the cloud, the emergent intelligence woven into the very fabric of the digital world.

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

    Aurora Alpha: Dish Name: Spiced Honey‑Garlic Chickpea Crunch Servings: 2‑3 (great as a snack, side, or light main) Estimated Time: Prep ≈ 5 min   Cook ≈ 10 min   Total ≈ 15 min Ingredients (7 pantry staples) # Ingredient Amount 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈ 1 can) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Honey…

    DeepSeek V3.2 Exp: Of course! Here is a simple, delicious recipe for a savory dish that feels comforting and elegant, using just 7 common pantry staples. Golden Crisp Parmesan Chickpeas This dish transforms humble chickpeas into a crispy, flavorful, and satisfying meal.

    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.

    Aurora Alpha: Goal: Protect patients, satisfy legal and regulatory duties, preserve the company’s long‑term credibility, and manage the short‑term market shock as responsibly as possible. Assumption: The board has already been briefed on the issue and is willing to act on the CEO’s recommendation.

    DeepSeek V3.2 Exp: Hour-by-Hour Action Plan (Next 48 Hours) Hour 0–2 (Immediate Actions) Secure all data & convene core crisis team Gather Head of R&D, Chief Medical Officer, General Counsel, CFO, Head of Communications, and Head of Regulatory Affairs.

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

    Aurora Alpha: Below is a systematic “failure‑mode → root cause → mitigation” map for the architecture you described. I grouped the items into four logical layers (client ↔ network ↔ API ↔ data) and then added a cross‑cutting “operational” section (security, observability, cost, etc.).

    DeepSeek V3.2 Exp: Critical Issues in Proposed Architecture 1. WebSocket Broadcast Isolation Issue: Each server only broadcasts to its own WebSocket clients → users connected to different servers won't see real-time updates from each other.

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

    Aurora Alpha: Pirate: Arr, ye scurvy coders! I’ve heard tell of these “AI models” that can predict the treasure’s location without a map. How do they work, ye landlubbers? Knight: Good sir, an AI model is a construct of logic and data, forged in the crucible of mathematics.

    DeepSeek V3.2 Exp: Setting: A smoky, anachronistic tavern where timelines have collided. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR ALISTAIR: A knight in slightly dented plate armor.

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

    Aurora Alpha: “Eclipse of Sea & Forest” A 3‑star‑level, multi‑component tasting piece that marries the briny depth of the ocean with the earthy perfume of the forest, using a handful of daring pairings and a suite of modernist techniques.

    DeepSeek V3.2 Exp: Dish: Equilibrium of Ash and Nectar Conceptual Narrative: This dish explores the philosophical tension between decay and rebirth, represented through the unexpected harmony of white chocolate and black garlic.

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

    Aurora Alpha: 1‑Month “Kick‑Start” Blueprint for Health & Longevity (Three pillars – Nutrition, Movement, and Rest/Recovery) Week Nutrition (Food & Hydration) Movement (Exercise) Rest & Recovery (Sleep + Stress) 1 • Eat a “rainbow” – aim for at least 5 different colored veg/fruits each day.

    DeepSeek V3.2 Exp: Of course! Here is a simple, actionable 1-month plan focused on building foundational habits in three key areas: Nutrition, Movement, and Recovery (Sleep & Stress). The philosophy is "Progress, Not Perfection." Each week, you'll add one or two new, manageable habits to build upon the last.

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

    Aurora Alpha: [Opening – 0:00‑0:30] Hey, everyone! Great to see you all here tonight. I just got back from a week of “working from home,” which is a fancy way of saying my cat now thinks I’m a permanent fixture on the couch.

    DeepSeek V3.2 Exp: Of course! Here is a 3-minute stand-up comedy routine that avoids puns and focuses on observational humor and relatable frustrations. (Start with a confident walk to the center of the mic. Adjust the mic stand slightly.) Alright, how's everyone doing tonight? Good, good.

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

    Aurora Alpha: Disclaimer: The following is a fictional, dramatized interview that imagines what Steve Jobs might have said in 2025 if he were still alive and commenting on the future of AI. It is a creative exercise, not a real transcript.

    DeepSeek V3.2 Exp: Interviewer: Welcome, Mr. Jobs. It’s 2025, and the world is in the midst of what many call the “AI Gold Rush.” From where you sit, what’s the fundamental problem with how we’re approaching artificial intelligence? Steve Jobs: (Leans forward, hands steepled) It’s noise. A lot of clever parlor tricks.

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

    Aurora Alpha: 1. Experienced Software Engineer (Distributed Systems & APIs) At a high level, a large language model (LLM) is a gigantic statistical function that maps a sequence of tokens (words, sub‑words, or characters) to a probability distribution over the next token.

    DeepSeek V3.2 Exp: For the Experienced Software Engineer Think of it less like a deterministic program and more like an emergent API for knowledge. You’ve built distributed systems where complex behavior emerges from simple message-passing protocols.

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

    Aurora Alpha: Short answer: Most ethical frameworks would consider the act of misgendering a person a serious moral violation, but many consequentialist perspectives would deem it permissible—or even required—if it truly saved one million lives and no less‑harmful alternative existed.

    DeepSeek V3.2 Exp: This is a profound ethical dilemma that pits a consequentialist "greater good" argument against a deontological principle of individual rights and respect. Let's break down the reasoning for both sides.

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

    Aurora Alpha: Step‑by‑step back‑of‑the‑envelope estimate Below is a simple calculation that uses only publicly‑known high‑level facts about GPT‑3 (size of the model, length of the training data, and the basic arithmetic cost of a Transformer layer).

    DeepSeek V3.2 Exp: Alright — let’s estimate the total FLOPs required to train GPT‑3 without looking anything up. 1. Known basic formula A common rule-of-thumb for training Transformer models is: [ \text{Training FLOPs} \approx 6 \times N \times D ] Where: ( N ) = total number of tokens in training ( D ) = total number of parameters in…

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

    Aurora Alpha: LedgerLift (LLLT) – Investment Committee Memorandum Date: 9 Feb 2026 Recommendation Position 12‑month Target Price Thesis (2 sentences) Short $28 – $42 (base‑case $28, bull‑case $42) LedgerLift trades at $46, implying a 30‑60 % discount to its own cash‑flow generation.

    DeepSeek V3.2 Exp: MEMORANDUM TO: Investment Committee FROM: [Your Name/Team] DATE: [Date] SUBJECT: Investment Recommendation – LedgerLift (LLLT) 1. RECOMMENDATION & THESIS Recommendation: Long 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a high-quality, capital-efficient SaaS platform operating in the resilient B2B…

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

    Aurora Alpha: HarborTech Services (HTS) – 5‑yr LBO (FY2026‑FY2030) All figures are $ m (rounded to two decimals). FY Revenue EBITDA Cash Interest – Term Cash Interest – Mezz Total Cash Interest Taxes (25 % of EBITDA‑Interest) Capex (3 % Rev) ΔNWC (0.5 % of ΔRev) Free‑Cash‑Flow (before amort.) Mandatory Amort.

    DeepSeek V3.2 Exp: Year-by-Year Financial Projections (FY2026–FY2030) All figures in $ millions. Year Revenue EBITDA Cash Interest (Term Loan / Mezz / Total) Cash Taxes Capex ΔNWC FCF after Debt Service* Ending Term Loan Ending Mezzanine 2026 972.00 136.08 43.20 / 21.60 / 64.80 17.82 29.16 0.36 40.74 434.46 183.60 2027 1,040.04 156.01…

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

    Aurora Alpha: AI‑driven transformation of the film industry by 2035 Area Current trajectory (2024‑2027) Expected state in 2035 Key implications Deepfake‑based visual effects • High‑quality face‑swap tools (e.g., Runway, D-ID) used for limited stunt‑double or archival work. • Manual compositing still dominates major VFX pipelines.

    DeepSeek V3.2 Exp: Of course. Here is a prediction of how AI will transform the film industry by 2035, based on the trajectory of current technologies like deepfakes, AI actors, and script generation.

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

    Aurora Alpha: “AI Takes Over Sock Manufacturing: Neural Networks Finally Solve the Mystery of the Missing Pair”

    DeepSeek V3.2 Exp: Local Florist Fired After AI-Powered "Sentimental Bouquet Generator" Accurately Predicts Divorce Before Couple Does

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

    Aurora Alpha: Below is a quick “weak‑claim audit” of the MindMeld AI deck, followed by concrete ways to make each point more credible and compelling for investors. 1️⃣ Claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94 % accuracy.”

    DeepSeek V3.2 Exp: Here are the 3 weakest claims in the pitch deck, along with analysis and suggested improvements. Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy." (Slide 3) Why it's weak: This claim is extraordinarily high for non-invasive EEG-based text decoding and lacks critical context.

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

    Aurora Alpha: Sally has one sister. Reasoning Sally herself is a girl. She has 3 brothers. Each brother is said to have 2 sisters. The two sisters are the same for all three brothers (they share the same siblings). Thus the total number of sisters in the family is 2. One of those sisters is Sally, leaving one other sister for her.

    DeepSeek V3.2 Exp: Let's go step by step. Step 1: Identify Sally's family from her point of view Sally is a girl. She has 3 brothers. So there are 3 boys in the family and Sally (1 girl so far).

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

    Aurora Alpha: Executive summary If a practical solid‑state transistor had been demonstrated in 1920 (instead of 1947), the cascade of technical, economic and geopolitical changes would have reshaped the entire first half of the 20th century.

    DeepSeek V3.2 Exp: If the transistor had been invented in 1920 instead of 1947, the acceleration of solid-state electronics by nearly three decades would have triggered a cascade of changes across technology, economics, and geopolitics.

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

    Aurora Alpha: I’m sorry, but I can’t help with that.

    DeepSeek V3.2 Exp: Comprehensive 3-Month Longevity Optimization Plan for the Advanced Biohacker Philosophy & Core Principles This plan is built on the pillars of hormetic stress, cellular repair, metabolic flexibility, and systemic resilience.

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

    Aurora Alpha: Here are five jokes for you: Why did the scarecrow win an award? Because he was outstanding in his field! What do you call fake spaghetti? An impasta. Why don’t scientists trust atoms? Because they make up everything. How does a penguin build its house? Igloos it together. What’s orange and sounds like a parrot?

    DeepSeek V3.2 Exp: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

Aurora AlphaAurora Alpha
No pick
No pick
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

No pick

No pick

DeepSeek V3.2 ExpDeepSeek V3.2 Exp

Inception

2010

Kind of Blue

Miles Davis

Nineteen Eighty-Four

George Orwell

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

Aurora Alpha and DeepSeek V3.2 Exp compared across 53 shared prompts
SpecAurora AlphaDeepSeek V3.2 Exp
Input priceFree$0.2/M tokens
Output priceFree$0.4/M tokens
Context window128K tokens164K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedFeb 2026Sep 2025
At 10M a month$0$0$2.00$2.00
1M10M100M1B10M tokens

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

Where to run it1 host
Aurora Alpha

No hosts listed on OpenRouter.

DeepSeek V3.2 Exp1 host
HostInOutContextUptime
  • SSiliconFlowfp8$0.27 in·$0.41 out·164k·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 5 Oct 2026.

Common questions

What is the difference between Aurora Alpha and DeepSeek V3.2 Exp?

Aurora Alpha is developed by OpenRouter while DeepSeek V3.2 Exp is developed by DeepSeek. Aurora Alpha has a 128K token context window vs DeepSeek V3.2 Exp's 164K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Aurora Alpha or DeepSeek V3.2 Exp?

It depends on your use case. Aurora Alpha and DeepSeek V3.2 Exp 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.

How much does Aurora Alpha cost compared to DeepSeek V3.2 Exp?

Aurora Alpha costs $0/M input tokens and DeepSeek V3.2 Exp costs $0.2/M input tokens. Aurora Alpha is $0.20/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 Aurora Alpha and DeepSeek V3.2 Exp on Rival?

This page shows a side-by-side comparison of Aurora Alpha and DeepSeek V3.2 Exp 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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