ERNIE 4.5 300B A47B is cheaper than Mercury at $0.28/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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?
Mercury: Here are five jokes for you: Why don't skeletons fight each other? Because they don't have the guts. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta.
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.
Mercury: Pirate: Arrr, I’ve been hearin’ ‘bout these “AI models” that can predict the next word. Sounds like a treasure map for the mind, doesn’t it? Knight: Hail, Captain! In my time, we relied on scrolls and the wisdom of scholars. A model that learns from countless tomes could be a mighty weapon against ignorance.
Film in 2035, with synthetic actors. Specific beats plausible.
ERNIE 4.5 300B A47B: By 2035, AI is poised to profoundly reshape the film industry across multiple dimensions, from pre-production to distribution, driven by advancements in deepfakes, AI actors, and script generation. Here’s a structured prediction of these transformations: 1.
Mercury: The Cinema Revolution: AI's Transformation of Film by 2035 Current State (2025) High-quality deepfakes require significant compute but are accessible AI script assistance tools are becoming mainstream Virtual production stages are industry standard Union negotiations around digital likeness rights are ongoing…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
ERNIE 4.5 300B A47B: Hour-by-Hour Action Plan for the Next 48 Hours Day 1: Immediate Response (0–24 Hours) Hours 0–2: Crisis Team Assembly Action: Convene an emergency cross-functional team (Legal, Medical Affairs, Regulatory, Communications, Finance, HR). Reasoning: Centralizes decision-making, ensures alignment, and leverages expertise.
Mercury: 48‑Hour Action Plan (CEO‑Level) Time (UTC) Action Who Leads Key Deliverables / Outcomes Rationale 0–2 h Secure the facts – Convene an emergency “Safety & Compliance” meeting with the Chief Medical Officer (CMO), Chief Legal Officer (CLO), Chief Risk Officer (CRO), and the Head of Regulatory Affairs (RA).
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.
Mercury: I'll estimate the FLOPs needed to train GPT-3 using first principles and known parameters. Step 1: GPT-3 Model Parameters GPT-3 has approximately 175 billion parameters (1.75 × 10¹¹) Step 2: Training Data Volume GPT-3 was trained on roughly 300 billion tokens (3 × 10¹¹ tokens) Step 3: FLOPs per Parameter per Token For…
A collaborative editor that syncs on client clocks. Find what breaks first.
ERNIE 4.5 300B A47B: Here's a detailed analysis of potential issues in the architecture, along with solutions and trade-offs: 1. Real-time Sync Issues Problem: WebSocket broadcasts are limited to a single server's clients.
Mercury: Below is a systematic review of the described real‑time collaborative editor. For each problem I list: What can go wrong (failure mode, race condition, bottleneck) Why it matters (impact on correctness, latency, availability) A concrete fix (what to change or add) Trade‑offs (cost, complexity, new failure modes, etc.)
One month, three habits, someone starting from nothing.
ERNIE 4.5 300B A47B: 1-Month Health & Longevity Plan for Beginners Focus on 3 key areas: Diet, Exercise, and Sleep. Each week builds on the last to create sustainable habits. Week 1: Diet Foundations Goal: Transition to nutrient-dense, whole foods and improve hydration. Day 1–3: Hydration: Drink 2–3 liters of water daily.
Mercury: 1‑Month Health & Longevity Starter Plan (Designed for absolute beginners – no fancy gear, no extreme diets, just doable habits that fit into a normal week.) 1️⃣ Focus Area: Balanced Nutrition Week Goal Simple, Beginner‑Friendly Actions 1 Get the basics down • Hydrate: Aim for 8‑10 cups (≈2 L) of water per day.
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…
Mercury: Golden Chickpea & Sweet Potato Stew Prep time: 10 min Cook time: 25 min Total: 35 min Ingredients (7 pantry staples) 1 cup canned chickpeas, drained & rinsed 1 medium sweet potato, peeled & diced (≈ 1 cup) 1 small onion, finely chopped 2 cloves garlic, minced ½ cup coconut milk (or any plant‑based milk) 2 tsp curry…
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?
Mercury: Title: The Art of Being Unorganized [Opening] Hey everyone! So, I was thinking about how my life is like a well-organized library... except instead of books, it's filled with random socks and expired coupons. And instead of a librarian, I have a cat who thinks she's in charge.
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.
Mercury: Interviewer: Good morning, Steve. It's a pleasure to have you here today. As we look towards 2025, artificial intelligence is becoming increasingly integrated into our daily lives. What are your thoughts on the future of AI? Steve Jobs: Good morning. It's great to be here.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
ERNIE 4.5 300B A47B: 1. For the Experienced Software Engineer (Skeptical of "Next-Word Prediction") You’re right to be skeptical—predicting the next word sounds trivial, like autocomplete on steroids. But the magic lies in scale and context.
Mercury: 1. Experienced Software Engineer (Distributed‑Systems Background) A large language model (LLM) is essentially a massive, highly parallelized neural network that learns to predict the probability distribution over the next token in a sequence.
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.
Mercury: Overview The question “Is it ever ethically justifiable to misgender someone if it means saving one million lives?” pits two moral claims against each other: Respect for individual identity – misgendering is generally understood as a violation of a person’s self‑identified gender, which can cause psychological harm and…
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Not enough votes to call it. On the specs, ERNIE 4.5 300B A47B has the edge: bigger model tier, bigger context window. ERNIE 4.5 300B A47B costs 9.1x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.28/M tokens | $10/M tokens |
| Output price | $1.1/M tokens | $10/M tokens |
| Context window | 123K tokens | 32K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Jun 2025 | Jun 2025 |
| At 10M a month | $2.80 | $100 |
Input tokens at list price. No caching, no batch discount.
ERNIE 4.5 300B A47B is developed by Baidu while Mercury is developed by Inception. ERNIE 4.5 300B A47B has a 123K token context window vs Mercury's 32K. 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 Mercury 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 Mercury costs $10/M input tokens. ERNIE 4.5 300B A47B is $9.72/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 Mercury 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.