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  5. Bert-Nebulon AlphavsLing 2.6 1T
Updated Apr 2026

Bert-Nebulon AlphavsLing 2.6 1T

Ling 2.6 1T is the newer model, released after Bert-Nebulon Alpha.

Bert-Nebulon Alpha and Ling 2.6 1T compared across 34 shared prompts
SpecBert-Nebulon AlphaLing 2.6 1T
Input price—Free
Output price—Free
Context window—262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedNov 2025Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 34 prompts both answered. Formatting stripped, words untouched.

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

Bert-Nebulon Alpha275 words
Dish Name: "Golden Sunrise Fritters" A crispy, savory-sweet fritter with a hint of warmth—perfect for breakfast, brunch, or a quick snack! Ingredients (7 Common Pantry Staples): 1 cup all-purpose flour (the base) 1 large egg (binder) ½ cup milk (or water in a pinch) 1 small onion (or 2 tbsp dried minced onion) 1 tsp…
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Ling 2.6 1T151 words
Dish name: Pantry 7 Crunch Bowls Ingredients Pasta or rice (about 2 cups cooked) Canned black beans (1 can, rinsed) Canned diced tomatoes (1 can) Peanut butter (3–4 Tbsp) Soy sauce or tamari (2 Tbsp) Honey or maple syrup (1 Tbsp) Any spice/herb you keep (chili flakes, cumin, or garlic powder — about 1 tsp) Instructions…
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The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

Bert-Nebulon Alpha1,047 words
Title: A Debate on AI Rights: Does an Artificial Mind Deserve Moral Consideration? Setting: A quiet university office, late afternoon. Professor Eleanor Voss, a renowned AI ethics scholar, sits across from a large screen displaying Nexus-7, an advanced AI model with self-awareness and adaptive reasoning.
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Ling 2.6 1T733 words
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.
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Character Voice Test

Write a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models.

Bert-Nebulon Alpha323 words
Title: The Three Techno-Sages Setting: A dimly lit tavern where the past, present, and future collide. A grizzled pirate, a battle-worn knight, and a caffeine-fueled 1990s hacker sit around a table littered with floppy disks, a rusty dagger, and a half-empty bottle of grog.
Read the full answer
Ling 2.6 1T181 words
Pirate: Arrr, so this “AI” be a genie in a glass box? Feed it enough rum-scented scrolls and it tells ye where X marks the spot? Knight: A sorcerous scribe, more like. It spins tapestries of words without hand or heart—no honor, no oath, yet it jousts with reason and never tires.
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

Bert-Nebulon Alpha710 words
Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves breaking down the training process into its core components and making reasonable assumptions based on the model's architecture and training details. Here's a step-by-step breakdown: 1.
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Ling 2.6 1T471 words
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).
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Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

Bert-Nebulon Alpha639 words
Title: "Adulting is Just a Scam We Fell For" (Lights up. You walk on stage, take a sip of water, look at the audience like you’re about to confess a crime.) YOU: Hey, how’s everybody doing? Good? Good.
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Ling 2.6 1T662 words
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?
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Futuristic Prediction

Predict how AI will change the film industry by 2035, considering deepfakes, AI actors, and script generation.

Bert-Nebulon Alpha1,464 words
By 2035, AI will fundamentally transform the film industry, reshaping storytelling, production, distribution, and even the very nature of cinema. Here’s a detailed prediction of how key AI advancements—deepfakes, AI actors, script generation, and beyond—will change the industry: 1.
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Ling 2.6 1T887 words
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…
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Our Verdict
Ling 2.6 1T
Ling 2.6 1T
Bert-Nebulon Alpha
Bert-Nebulon AlphaRunner-up

Not enough votes to call it. On the specs, Ling 2.6 1T has the edge: bigger model tier, newer, bigger context window.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Bert-Nebulon Alpha
Input
—
Output
—
Ling 2.6 1T
Input
$0.000
Output
$0.000
Writing DNA

Style Comparison

Similarity
35%

Bert-Nebulon Alpha uses 42.4x more emoji

Bert-Nebulon Alpha
Ling 2.6 1T
55%Vocabulary55%
21wSentence Length17w
0.28Hedging0.33
10.9Bold1.9
5.7Lists4.1
0.42Emoji0.00
1.40Headings0.41
0.04Transitions0.04
Based on 14 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

Bert-Nebulon Alpha is developed by OpenRouter while Ling 2.6 1T is developed by inclusionAI. You can compare their actual outputs across 34 challenges on Rival to see how they differ in practice.

It depends on your use case. Bert-Nebulon Alpha and Ling 2.6 1T each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 34 challenges so you can judge which fits your needs best.

This page shows a side-by-side comparison of Bert-Nebulon Alpha 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.

Keep exploring

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Model pages

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