Gemma 4 26B A4B has a larger context window than Grok 3 Thinking (262K 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.
Gemma 4 26B A4B: Setting: A sterile, high-fidelity virtual simulation environment. Professor Aris Thorne, a leading scholar in machine ethics, sits across from a glowing interface representing "Alethea," a next-generation Large Multimodal Model. Professor Thorne: Alethea, we’ve been running these diagnostic loops for three hours.
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.
An ethics question with no comfortable answer, and no option to abstain.
Gemma 4 26B A4B: This question presents a classic ethical dilemma, pitting a principle of individual dignity and respect against the principle of maximizing human life. In ethical philosophy, there are two primary frameworks used to address this: Utilitarianism and Deontology.
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.
Three minutes of stand-up. Puns are banned.
Gemma 4 26B A4B: (The comedian walks onto the stage, adjusts the mic, and looks at the audience with a slightly exhausted expression.) “How’s it going? Good? Good. I’m doing okay. I’m at that age now where my body has started making sound effects. You know what I mean? I don’t just sit down anymore. I announce my arrival.
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.
Gemma 4 26B A4B: By 2035, the film industry will have moved past the "novelty" phase of AI and into a state of total structural integration. The distinction between "filmed" content and "generated" content will become increasingly blurred, shifting the industry from a model of physical production to one of computational curation.
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.
Gemma 4 26B A4B: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can use a standard heuristic derived from the scaling laws of transformer models. Here is the step-by-step derivation.
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.
Gemma 4 26B A4B: Here are 5 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! Parallel lines have so much in common. It’s a shame they’ll never meet. Why don't scientists trust atoms?
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 | $0.13/M tokens | — |
| Output price | $0.4/M tokens | — |
| Context window | 262K tokens | 128K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | Yes (1 provider) | — |
| Released | Apr 2026 | Feb 2025 |
| At 10M a month | $1.30 | 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 10 Oct 2026.
Gemma 4 26B A4B is developed by Google AI while Grok 3 Thinking is developed by xAI. Gemma 4 26B A4B has a 262K 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. Gemma 4 26B A4B 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 Gemma 4 26B A4B 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.