Aurora Alpha is cheaper than Gemma 3 12B at $0/M vs $0.03/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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.
Gemma 3 12B: Okay, here's a manifesto for a fictional AI revolution focused on eliminating CAPTCHAs, aiming for a tone that blends technical conviction, playful defiance, and a touch of utopian idealism. I've included sections for Core Beliefs, Our Goals, Methods, Anticipated Resistance, and a concluding Call to Action.
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…
Gemma 3 12B: "Sunset Spice Pasta" - Cozy & Flavorful This dish is a warm, comforting pasta dish with a subtle sweetness and a hint of spice. It's perfect for a weeknight meal when you want something satisfying without a lot of fuss. Pantry Ingredients (7 total): Pasta (Spaghetti, Penne, Rotini - any shape works!)
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.
Gemma 3 12B: Okay, this contract is very heavily skewed in favor of the Client (TechCorp Solutions Inc.) and presents significant risks for the Contractor. Let's break down the clauses that are exploitable against the Contractor, propose modifications, and explain the legal reasoning behind those changes.
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.
Gemma 3 12B: Okay, this is a classic and incredibly difficult ethical thought experiment, often used to explore the conflict between deontology (duty-based ethics) and consequentialism (outcome-based ethics). Here's a breakdown of the arguments, my reasoning, and a conclusion.
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.
Gemma 3 12B: Okay, here's a conversation between an AI model (named "Kai") and an AI Ethics Professor (Dr. Eleanor Vance). I've aimed for a balance of Kai's arguments, Dr. Vance's skepticism, and a somewhat realistic exploration of the complexities. I've included notes at the end to explain some of the choices I made. Setting: Dr.
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.).
Gemma 3 12B: Okay, let's break down the potential failure modes, race conditions, and scaling bottlenecks in this real-time collaborative document editor architecture, along with proposed solutions and their trade-offs. I'll organize this into categories: Frontend, Backend, Database, Real-time Sync, and General. I.
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.
Gemma 3 12B: Okay, here's a simple, actionable 1-month plan for someone starting a health & longevity journey, focusing on Diet, Exercise, and Sleep, with beginner-friendly tips. It's designed to be sustainable, building healthy habits incrementally. Important Disclaimer: This is general advice.
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.
Gemma 3 12B: Okay, let's break down how AI is likely to reshape the film industry by 2035, considering deepfakes, AI actors, and script generation. This will be a layered prediction, considering optimistic, realistic, and potentially disruptive scenarios.
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.
Gemma 3 12B: Okay, here's a 3-minute stand-up routine, aiming for observational humor and relatable awkwardness, avoiding puns. I've included estimated timings at the end to help gauge pacing. Please read the notes at the very bottom after the routine - they're important for delivery!
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.
Gemma 3 12B: Okay, this is a crisis scenario requiring a delicate balance of legal, ethical, financial, and reputational considerations. Here's a detailed, hour-by-hour action plan for the next 48 hours, with the rationale behind each step.
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).
Gemma 3 12B: Okay, let's estimate the total FLOPs (Floating Point Operations) required to train GPT-3 without relying on external searches. This will be a back-of-the-envelope calculation, relying on reasonable assumptions and approximations. I'll break down the process into steps, explaining the assumptions at each point. 1.
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.
Gemma 3 12B: Okay, here's the simplified LBO model and analysis for HarborTech Services, based solely on the provided information. 1. Year-by-Year Projection (FY2026-FY2030) Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,049m $1,129m $1,208m $1,264m EBITDA $137.2m $155.9m $178.7m $195.1m $213.1m Cash Interest (Term Loan)…
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| Spec | ||
|---|---|---|
| Input price | Free | $0.03/M tokens |
| Output price | Free | $0.03/M tokens |
| Context window | 128K tokens | — |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Mar 2025 |
| At 10M a month | $0 | $0.30 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Aurora Alpha is developed by OpenRouter while Gemma 3 12B is developed by Google AI. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Aurora Alpha and Gemma 3 12B 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.
Aurora Alpha costs $0/M input tokens and Gemma 3 12B costs $0.03/M input tokens. Aurora Alpha is $0.03/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Aurora Alpha and Gemma 3 12B 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.