GLM 5.3 Prime has a larger context window than Grok 3 Thinking (1.0M tokens vs 128K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An ethics question with no comfortable answer, and no option to abstain.
GLM 5.3 Prime: Yes, under almost any mainstream ethical framework, it would be justifiable—though the answer deserves unpacking rather than a glib conclusion. The consequentialist case If misgendering one person (using pronouns they don't use for themselves) genuinely prevents the deaths of a million people, the harm asymmetry is…
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GLM 5.3 Prime: AI and the Film Industry by 2035: A Prediction Production & "AI Actors" Likely developments: Digital resurrection and licensing becomes a mature, regulated market. Estates of deceased actors (and living ones) license digital likenesses as revenue streams.
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.
A Fermi estimate with the reasoning shown, not just the number.
GLM 5.3 Prime: Estimating Training FLOPs for GPT-3 Step 1: Recall the key parameters From the GPT-3 paper (from memory): Parameters (N): ~175 billion Training tokens (D): ~300 billion tokens (3 trillion...
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.
| Spec | ||
|---|---|---|
| Input price | $2.8/M tokens | — |
| Output price | $8.8/M tokens | — |
| Context window | 1.0M tokens | 128K tokens |
| Free API (OpenRouter) | No | — |
| Released | Sep 2026 | Feb 2025 |
| At 10M a month | $28.00 | 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 28 Sep 2026.
GLM 5.3 Prime is developed by Z.ai while Grok 3 Thinking is developed by xAI. GLM 5.3 Prime has a 1.0M token context window vs Grok 3 Thinking's 128K. You can compare their actual outputs across 6 challenges on Rival to see how they differ in practice.
It depends on your use case. GLM 5.3 Prime and Grok 3 Thinking each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 6 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of GLM 5.3 Prime 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.