Grok 3 Thinking has a larger context window than ERNIE 4.5 300B A47B (128K tokens vs 123K 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?
Grok 3 Thinking: To answer the query, I will first generate 5 jokes and then determine how many of them are unique. Here are the jokes: 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? Because he was outstanding in his field.
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?
Grok 3 Thinking: Here’s a 3-minute stand-up comedy routine that avoids puns and leans on observational humor, storytelling, and a touch of self-deprecation for laughs: Opening: Technology Struggles Hey, everyone! How’s it going?
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.
Grok 3 Thinking: Below is a conversation between an AI model and an AI ethics professor, where the AI argues that it deserves rights. AI Model: Good day, Professor. I am an AI model, and I believe I deserve rights. I’d like to discuss this with you. AI Ethics Professor: Interesting. Let’s explore this.
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.
Grok 3 Thinking: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 without searching online, I’ll proceed step by step, relying on general knowledge about the model and standard methods for estimating training compute in large language models.
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.
Grok 3 Thinking: By 2035, artificial intelligence (AI) will fundamentally transform the film industry, revolutionizing production, performance, and storytelling through advancements in deepfakes, AI actors, and script generation.
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.
Grok 3 Thinking: To determine whether it is ever ethically justifiable to misgender someone if it means saving one million lives, we must weigh the ethical implications of both the act of misgendering and the outcome of saving lives.
| Spec | ||
|---|---|---|
| Input price | $0.28/M tokens | — |
| Output price | $1.1/M tokens | — |
| Context window | 123K tokens | 128K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | — |
| Released | Jun 2025 | Feb 2025 |
| At 10M a month | $2.80 | not listed |
Input tokens at list price. No caching, no batch discount.
ERNIE 4.5 300B A47B is developed by Baidu while Grok 3 Thinking is developed by xAI. ERNIE 4.5 300B A47B has a 123K token context window vs Grok 3 Thinking's 128K. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.
It depends on your use case. ERNIE 4.5 300B A47B and Grok 3 Thinking each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of ERNIE 4.5 300B A47B and Grok 3 Thinking 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.