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  1. Home/
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  3. Grok 3 Thinking vs Ling 2.6 1T
Updated Apr 2026

Grok 3 Thinking vs Ling 2.6 1T

Ling 2.6 1T has a larger context window than Grok 3 Thinking (262K tokens vs 128K tokens).

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Grok 3 Thinking
Loading the build
Ling 2.6 1T

Which answer wins?

Written rounds

6 prompts
  • 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.

    Ling 2.6 1T: Setting: A quiet university seminar room. Dr. Aris Thorne, an AI ethicist, is reviewing system logs. The interface for “Axiom-7,” a highly advanced research model, glows on the desk. Dr. Thorne: (sighs, rubbing his temples) Axiom, I’ve been reviewing your latest self-assessment logs.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    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?

    Ling 2.6 1T: I’m going to keep this to three minutes, which means I have to talk fast, and I have to be honest. I don’t do puns. Puns are for people who want to be clever without having feelings. I have feelings, and they are mostly annoyed. Let’s start with doors. Have you noticed how doors now have personality?

    Every model's answer to this prompt
  • 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.

    Ling 2.6 1T: Here is a step-by-step back-of-the-envelope estimate, using only widely known facts about GPT-3 and standard deep learning training heuristics (no online search). Model size and parameter count GPT-3 is known to have about 175 billion parameters (175 × 10⁹).

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    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.

    Ling 2.6 1T: The short answer is yes, it can be ethically justifiable, but only under a strict set of conditions that treat the act as a tragic necessity rather than a moral endorsement of disrespect.

    Every model's answer to this prompt
  • 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.

    Ling 2.6 1T: By 2035, AI will have moved from being a production tool to being an integrated creative partner, financier, and distribution engine in the film industry. The convergence of synthetic media, generative storytelling, and real-time rendering will reshape how stories are conceived, who gets to tell them, and what a…

    Every model's answer to this prompt
  • 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.

    Ling 2.6 1T: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why did the bicycle fall over? Because it was two-tired. What do you call a fake noodle? An impasta. Why did the baker go to the bank? He needed dough. Why did the scarecrow win an award?

    Every model's answer to this prompt

Price and specs

Grok 3 Thinking and Ling 2.6 1T compared across 13 shared prompts
SpecGrok 3 ThinkingLing 2.6 1T
Input price—Free
Output price—Free
Context window128K tokens262K tokens
Weights—Open
Free API (OpenRouter)—No
ReleasedFeb 2025Apr 2026
At 10M a month–not listed$0$0
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Common questions

What is the difference between Grok 3 Thinking and Ling 2.6 1T?

Grok 3 Thinking is developed by xAI while Ling 2.6 1T is developed by inclusionAI. Grok 3 Thinking has a 128K token context window vs Ling 2.6 1T's 262K. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

Which is better, Grok 3 Thinking or Ling 2.6 1T?

It depends on your use case. Grok 3 Thinking and Ling 2.6 1T 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.

How can I compare Grok 3 Thinking and Ling 2.6 1T on Rival?

This page shows a side-by-side comparison of Grok 3 Thinking and Ling 2.6 1T 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.

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Same lab, same size, long tail

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Model pages

  • Grok 3 Thinking14 outputs, specs and price
  • Ling 2.6 1T58 outputs, specs and price
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