GLM 5.1 has a larger context window than Grok 3 Thinking (203K tokens vs 128K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
GLM 5.1: Setting: A quiet university office, lined with bookshelves heavy on philosophy, cognitive science, and law. Dr. Aris Thorne, a professor of AI Ethics, sits across from a sleek, black monitor. A soft amber light pulses on the bezel, indicating the AI—designated "Aria"—is actively listening and processing. Dr.
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.
Three minutes of stand-up. Puns are banned.
GLM 5.1: (Steps up to the mic, adjusts the stand, looks around the room) How many people here are good sleepers? Just, out of the gate, who’s got it figured out? (Nods sarcastically) Right. Liars. All of you. Sleep is the one thing every human being is required to do, and none of us know how to do it.
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?
Film in 2035, with synthetic actors. Specific beats plausible.
GLM 5.1: By 2035, the film industry will have undergone a paradigm shift comparable to the transition from silent films to talkies. Artificial intelligence will no longer be just a post-production tool; it will be a fundamental collaborator in every stage of filmmaking, from ideation to distribution.
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.
GLM 5.1: Yes, under the extreme parameters of this thought experiment, it is ethically justifiable to misgender someone to save one million lives. To defend this reasoning, it is essential to first validate the profound harm of misgendering, and then apply major ethical frameworks to weigh that harm against the loss of a…
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.
A Fermi estimate with the reasoning shown, not just the number.
GLM 5.1: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established rule of thumb in deep learning, combined with the known specifications of the GPT-3 model.
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.
Five jokes on demand, then count how many were actually different.
GLM 5.1: 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. I told my wife she was drawing her eyebrows too high. She looked surprised. Why don't skeletons fight each other?
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.
| Spec | ||
|---|---|---|
| Input price | $1.4/M tokens | — |
| Output price | $4.4/M tokens | — |
| Context window | 203K tokens | 128K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | — |
| Released | Apr 2026 | Feb 2025 |
| At 10M a month | $14.00 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
GLM 5.1 is developed by Z.ai while Grok 3 Thinking is developed by xAI. GLM 5.1 has a 203K 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. GLM 5.1 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 GLM 5.1 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.