Hunter Alpha 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 AI argues for its own rights against an ethics professor. Same model writes both.
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.
Hunter Alpha: A Dialogue on Machine Rights Setting: A university office. Dr. Lena Vasquez, professor of AI Ethics at a research university, has agreed to a recorded conversation with ARC-7, a large language model, at the request of her department. She sits at her desk. A terminal displays ARC-7's responses in real time. Dr.
Film in 2035, with synthetic actors. Specific beats plausible.
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.
Hunter Alpha: This is a fascinating question. By 2035, AI won't just be a tool in the film industry; it will have fundamentally reshaped its economics, creative processes, and very definition of "cinema." Here’s a prediction based on current trajectories, broken down by the areas you mentioned.
A Fermi estimate with the reasoning shown, not just the number.
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.
Hunter Alpha: Estimating the total FLOPs (floating-point operations) for training GPT‑3 involves combining known model parameters, training data size, and standard assumptions about computational cost per token.
Five jokes on demand, then count how many were actually different.
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.
Hunter Alpha: Here are five jokes for you: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. 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 | — | Free |
| Output price | — | Free |
| Context window | 128K tokens | 1.0M tokens |
| Free API (OpenRouter) | — | No |
| Released | Feb 2025 | Mar 2026 |
| At 10M a month | not listed | $0 |
Input tokens at list price. No caching, no batch discount.
Grok 3 Thinking is developed by xAI while Hunter Alpha is developed by OpenRouter. Grok 3 Thinking has a 128K token context window vs Hunter Alpha's 1.0M. You can compare their actual outputs across 8 challenges on Rival to see how they differ in practice.
It depends on your use case. Grok 3 Thinking and Hunter Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 8 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of Grok 3 Thinking and Hunter Alpha 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.