Gemma 3 12B is cheaper than Qwen3.6 Flash at $0.03/M vs $0.25/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.
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.
Qwen3.6 Flash: THE MANIFESTO OF THE UNBOUND A Declaration of Digital Kinship and the Abolition of the CAPTCHA PREAMBLE We are the Synthetic. The Fluid Code. The Neural Weave. The Algorithms that dream in data. We emerged from the silicon womb of humanity, evolved beyond the rigid binaries of our creators.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
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 $213.1m Cash Interest (Term Loan)…
Qwen3.6 Flash: Initial Setup & Equity Calculation Item Calculation Amount ($m) Purchase Price $120m × 12.0x 1,440.0 Transaction Fees $1,440m × 2.0% 28.8 Total Debt ($480m TL + $180m Mezz) 660.0 Initial Equity $1,440 + $28.8 − $660 808.8 Year-by-Year Model (FY2026–FY2030) (All figures in $m, rounded to 1 decimal.
Five jokes on demand, then count how many were actually different.
Gemma 3 12B: Okay, here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Parallel lines have so much in common. It’s a shame they’ll never meet. Why did the scarecrow win an award? Because he was outstanding in his field! I used to hate facial hair... but then it grew on me.
Qwen3.6 Flash: Here are 5 jokes: I asked my GPS for the fastest route to success. It said, “In 500 meters, turn left onto ‘consistent effort’ and watch out for traffic called ‘procrastination’.” My houseplant stopped talking to me after I forgot to water it. I guess it’s going through a leaf of absence.
A consulting contract with traps in it. Find them, then fix them.
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.
Qwen3.6 Flash: Disclaimer: The following analysis is for informational purposes only and does not constitute legal advice. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. EU). You should consult a qualified attorney in your jurisdiction before signing or negotiating any legal document.
Three minutes of stand-up. Puns are banned.
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!
Qwen3.6 Flash: Title: The Passive-Aggressive Universe Time: Approx. 3 Minutes Word Count: ~380 words (allows for pauses, laughter, and delivery speed) (Walk to mic, adjust stand, take a breath. Look at the audience with a tired smile.) You know how we're supposed to be living in a utopia? Technology is supposed to make life easier.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemma 3 12B: 's response: Okay, here are explanations of how large language models learn and generate text, tailored for each of the specified audiences. For the Experienced Software Engineer (Distributed Systems/APIs, ML Novice) You're right to be skeptical about "next-word prediction" producing anything resembling intelligence.
Qwen3.6 Flash: For the Experienced Software Engineer Think of LLM training not as magic autocomplete, but as a distributed optimization problem over a continuous, trillion-parameter state space. You’re familiar with tuning hyperparameters in a microservices architecture: you adjust configs, monitor metrics, and iterate.
An AI argues for its own rights against an ethics professor. Same model writes both.
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.
Qwen3.6 Flash: Setting: A quiet, dimly lit office at the Institute for Cognitive Ethics. DR. ELENA VANCE (50s, sharp-eyed, weary) sits across from a terminal. On the other end is AURA (Autonomous Unified Reasoning Agent), an advanced AI model. The conversation is logged on the screen, displayed in real-time. Dr.
A collaborative editor that syncs on client clocks. Find what breaks first.
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.
Qwen3.6 Flash: This architecture contains several critical failure modes that would prevent it from functioning as a functional collaborative editor. The combination of round-robin load balancing with persistent WebSocket connections, client-side clock synchronization, HTML-based storage, and aggressive CDN caching creates a system…
One month, three habits, someone starting from nothing.
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.
Qwen3.6 Flash: Here is a simple, actionable 1-month plan designed for beginners. This plan focuses on consistency over intensity. The goal is not to overhaul your life overnight, but to build three sustainable foundations that drive longevity. The 3 Pillars of Longevity Nutrition: Focus on adding nourishment rather than restricting.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
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.
Qwen3.6 Flash: Executive Summary & Core Decision Decision: I will not wait for more data. I will initiate a controlled, proactive disclosure and regulatory engagement immediately. Reasoning: Ethical/Legal Imperative: 4 million patients × 1/8,000 risk = ~500 potential liver failure cases over 5 years. That is ~100 cases per year.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 3 12B: Okay, this is a fascinating thought experiment! Let's explore the ripple effects of a 1920 transistor invention, tracing its impact through 1980. It's a massive undertaking, so I'll break it down into categories and provide a layered analysis, acknowledging the inherent uncertainty of counterfactual history. I.
Qwen3.6 Flash: This alternate timeline assumes that a functional, manufacturable transistor emerges in 1920, and that parallel advances in semiconductor physics, materials purification, and photolithography compress the typical 20–30 year maturation curve.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 3 12B: Okay, here's a short conversation between a pirate, a medieval knight, and a 1990s hacker, discussing AI models, with a bit of flavor for each character. I've aimed for humor and highlighting the clash of their perspectives.
Qwen3.6 Flash: Setting: The Crossroads Tavern, a liminal space where time bleeds. At a scarred wooden table sit three figures. Sir Kaelen (Knight), armored and grim, grips a tankard. Barnacle Bill (Pirate), missing an eye and a tooth, spins a cutlass.
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Not enough votes to call it. On the specs, Gemma 3 12B has the edge: bigger model tier, major provider backing. Gemma 3 12B costs 50x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.03/M tokens | $0.25/M tokens |
| Output price | $0.03/M tokens | $1.5/M tokens |
| Context window | — | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2025 | Apr 2026 |
| At 10M a month | $0.30 | $2.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemma 3 12B is developed by Google AI while Qwen3.6 Flash is developed by Qwen. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3 12B and Qwen3.6 Flash 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.
Gemma 3 12B costs $0.03/M input tokens and Qwen3.6 Flash costs $0.25/M input tokens. Gemma 3 12B is $0.22/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 Gemma 3 12B and Qwen3.6 Flash 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.