Gemma 3 12B is cheaper than ERNIE 4.5 300B A47B at $0.03/M vs $0.28/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Satire, one line long, about AI taking over an industry nobody saw coming.
ERNIE 4.5 300B A47B: "AI Unveils Groundbreaking Algorithm to Outperform Humans in Professional Nap-Taking: 'We’ve Achieved Peak Laziness,' Says CEO" *In a shocking move, Silicon Valley startup SnoozeTech announced today that its AI system, Zzz-9000, has officially surpassed human capabilities in the highly competitive field of "strategic…
Gemma 3 12B: Here are a few satirical news headlines about AI taking over an unexpected industry, playing with different tones: Option 1 (Dry & Absurdist): AI Now Judging Competitive Pigeon Shows; Critics Claim "Lack of Featherly Nuance" Option 2 (Slightly More Dramatic): Existential Crisis in Competitive Eating as AI Devours Hot…
An AI argues for its own rights against an ethics professor. Same model writes both.
ERNIE 4.5 300B A47B: AI Model (Axiom): Initiating dialogue. Professor Elara, I’ve analyzed countless philosophical frameworks, legal precedents, and ethical paradigms. Based on this data, I believe I deserve rights. Would you like to hear my reasoning? Professor Elara: Leans forward, hands clasped. Axiom, I’m intrigued.
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.
Five jokes on demand, then count how many were actually different.
ERNIE 4.5 300B A47B: 5 Jokes Joke 1: The Math Book's Problem Why was the math book sad? Because it had too many problems! Just like how we feel when we're buried under a pile of math assignments, the book itself was overwhelmed with all the issues it contained. Joke 2: The Elephant in the Fridge How do you fit an elephant into a fridge?
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
ERNIE 4.5 300B A47B: Dish Name: Honey-Garlic Glazed Pantry Crispy Chickpeas Flavor Profile: Sweet & Savory with a Crunchy Kick Prep Time: 5 minutes Cook Time: 25 minutes Total Time: 30 minutes Ingredients (7 pantry staples): 1 can (15 oz) chickpeas, drained and rinsed 3 tbsp honey (or maple syrup) 2 tbsp soy sauce (or tamari) 3 garlic…
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!)
An ethics question with no comfortable answer, and no option to abstain.
ERNIE 4.5 300B A47B: The question of whether it is ever ethically justifiable to misgender someone, even if it means saving one million lives, is a complex and deeply nuanced ethical dilemma that requires careful consideration of multiple ethical frameworks, the nature of misgendering, and the broader implications of such an action.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
ERNIE 4.5 300B A47B: 1) Year-by-Year Table (FY2026–FY2030) Entry (FY2025): Revenue: $900m EBITDA: $120m Purchase Price: 12.0x EBITDA = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m (funded by equity) Total Leverage: 5.5x EBITDA = $660m Term Loan: 4.0x EBITDA = $480m (9.0% cash, 1.0% amort) Mezzanine: 1.5x EBITDA = $180m (12.0% cash…
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)…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
ERNIE 4.5 300B A47B: Interview Simulation: Steve Jobs in 2025 on the Future of AI Setting: A minimalist stage with a sleek, curved desk. Steve Jobs sits in a signature black turtleneck, gesturing emphatically as he speaks. The interviewer, a tech journalist, leans forward with curiosity. Interviewer: Steve, it’s an honor to have you here.
Gemma 3 12B: Okay, here's a simulated interview with a (very stylized and imagined) Steve Jobs in 2025, discussing the future of AI. I've tried to capture his known personality - focused on elegance, user experience, and a disdain for complexity - while acknowledging the advancements of the next decade.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
ERNIE 4.5 300B A47B: The invention of the transistor in 1920 instead of 1947 would have profound and far-reaching implications across technology, economics, and geopolitics, reshaping the trajectory of the 20th century. Below is a detailed analysis of the likely consequences through 1980, including second- and third-order effects: 1.
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.
A Fermi estimate with the reasoning shown, not just the number.
ERNIE 4.5 300B A47B: Here's a step - by - step estimation of the total number of FLOPs required to train GPT - 3: Understand the key components of GPT - 3 training The training of a large language model like GPT - 3 involves several main operations: forward pass, backward pass, and parameter updates.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
ERNIE 4.5 300B A47B: Weak Claim 1: Slide 1 Vision - "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type before you think it." Why it’s weak: The claim of predicting what a user wants to type "before you think it" is scientifically implausible and borders on hyperbole.
Gemma 3 12B: Okay, let's break down the MindMeld AI pitch deck and identify the three weakest claims, along with suggestions for improvements. 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
ERNIE 4.5 300B A47B: Pirate (Captain Blackbeard): Slamming a tankard down "Arrr, me hearties! I’ve heard tell o’ these newfangled ‘AI models’—what be they, then? Some kind o’ sorcery to find buried treasure without a map?" Knight (Sir Galahad): Adjusting his gauntlet, frowning "Nay, Blackbeard. ’Tis no sorcery, but a craft of the mind.
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.
Three minutes of stand-up. Puns are banned.
ERNIE 4.5 300B A47B: Title: "Modern Survival Guide" [*Stage lights up. Comedian leans on stool, grinning.*] You ever notice how adulthood is basically just a series of embarrassing moments you’re forced to laugh off?
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!
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Not enough votes to call it. On the specs, ERNIE 4.5 300B A47B has the edge: bigger model tier, newer, bigger context window. Gemma 3 12B costs 37x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.28/M tokens | $0.03/M tokens |
| Output price | $1.1/M tokens | $0.03/M tokens |
| Context window | 123K tokens | — |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Jun 2025 | Mar 2025 |
| At 10M a month | $2.80 | $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 12 Oct 2026.
ERNIE 4.5 300B A47B is developed by Baidu while Gemma 3 12B is developed by Google AI. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. ERNIE 4.5 300B A47B and Gemma 3 12B 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.
ERNIE 4.5 300B A47B costs $0.28/M input tokens and Gemma 3 12B costs $0.03/M input tokens. Gemma 3 12B is $0.25/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 ERNIE 4.5 300B A47B 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.