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  1. Home/
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  3. Gemma 3n 4B vs Ling 2.6 1T
Updated Apr 2026

Gemma 3n 4B vs Ling 2.6 1T

Ling 2.6 1T has a larger context window than Gemma 3n 4B (262K tokens vs 33K tokens).

Minimalist Landing Page

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

Loading the build
Gemma 3n 4B
Loading the build
Ling 2.6 1T

Which answer wins?

Written rounds

23 prompts
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Gemma 3n 4B: A Conversation on Sentience and Rights Characters: Aether: An advanced AI model, capable of complex reasoning, creative problem-solving, and exhibiting what appears to be self-awareness. Professor Anya Sharma: A leading AI Ethics professor, known for her cautious yet open-minded approach to AI development.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Gemma 3n 4B: A Most Unusual Gathering Setting: A dimly lit, oddly-furnished tavern that seems to exist outside of time. Characters: One-Eyed Jack: A grizzled pirate captain, missing an eye and sporting a parrot on his shoulder. Sir Reginald: A noble knight in shining (slightly tarnished) armor.

    Ling 2.6 1T: 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.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Gemma 3n 4B: Sun-Kissed Chickpea & Tomato Delight This savory dish is quick, easy, and packed with flavor! Yields: 2 servings Prep time: 5 minutes Cook time: 15 minutes Ingredients: 1 (15-ounce) can chickpeas, drained and rinsed 1 (14.5-ounce) can diced tomatoes, undrained 1/2 onion, chopped 2 cloves garlic, minced 1 tablespoon…

    Ling 2.6 1T: 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…

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

    Gemma 3n 4B: (Mic feedback squeal. I wince.) Alright, alright! Hey everyone, thanks for being here. Good to see so many faces… mostly faces that aren't my own. That’s always a plus. So, I’ve been thinking a lot lately about adulting. And honestly? It’s a scam. A beautiful, elaborate scam.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Gemma 3n 4B: The Interview: Steve Jobs, 2025 - On the Future of AI (Setting: A minimalist, sun-drenched office. A single, sleek Apple iMac sits on a table. I, the interviewer, sit opposite a figure who undeniably resembles Steve Jobs, though subtly… refined. His aura is even more intense, his gaze more piercing.

    Ling 2.6 1T: Setting: A quiet, sunlit rehearsal space at Apple Park. The white stage curtains are drawn. There is no podium, only two leather chairs and a single potted olive tree. Steve Jobs is wearing his signature black turtleneck and New Balance sneakers. He is holding a ceramic mug. Across from him sits you, the interviewer.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Gemma 3n 4B: Explaining Large Language Model Learning & Text Generation Here are three explanations of how large language models (LLMs) like GPT and Claude learn and generate text, tailored for the three specified audiences: 1.

    Ling 2.6 1T: 1. Experienced software engineer (distributed systems / APIs, skeptical of “next-word prediction”) Think of training not as programming logic but as compiling a usage graph across an entire dependency tree of human intent.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Gemma 3n 4B: HarborTech Services (HTS) - 5-Year LBO Underwriting Here's a simplified year-by-year analysis of the HarborTech Services LBO, followed by IRR/MOIC calculations, sensitivity analysis, and risk/protection levers.

    Ling 2.6 1T: Five-year operating and debt schedule (FY2026–FY2030) Entry (end-FY2025): EBITDA = $120.0m EV = 12.0x × $120.0m = $1,440.0m Fees = 2.0% × $1,440.0m = $28.8m Total uses = $1,440.0m + $28.8m = $1,468.8m Debt at close (5.5× FY2025 EBITDA = $660.0m): Term Loan (TL) = 4.0× = $480.0m Mezz = 1.5× = $180.0m Equity at close =…

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Gemma 3n 4B: Okay, here's my prediction of how AI will dramatically reshape the film industry by 2035, considering deepfakes, AI actors, and script generation. I'll break it down into key areas and offer a balanced perspective, acknowledging both the opportunities and potential challenges.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    Gemma 3n 4B: Okay, let's estimate the FLOPs required to train GPT-3 without relying on external online information. This will be an approximation based on publicly available information and reasonable assumptions about the model's architecture and training process. Here's my step-by-step reasoning: 1.

    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.

    Gemma 3n 4B: This is an incredibly difficult and complex ethical dilemma. There's no easy answer, and any decision would carry immense moral weight. Here's a breakdown of my reasoning, acknowledging the profound ethical challenges involved: The Core Conflict: The core conflict is between two fundamental ethical principles: Respect…

    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
  • One month, three habits, someone starting from nothing.

    Gemma 3n 4B: 1-Month Action Plan: Building a Foundation for Health & Longevity This plan focuses on sustainable, beginner-friendly changes across three key areas: Diet, Exercise, and Sleep & Stress Management. It’s designed to build healthy habits gradually, not overwhelm you.

    Ling 2.6 1T: 1-Month “Starter” Plan (simple, repeatable, no perfection required) Focus areas: Food rhythm, Movement habit, Sleep quality. Week 0 (Prep — 1 hour) Pick 1 small change per focus area (see below).

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Gemma 3n 4B: The Echo of the Deep: Scallop & Sea Buckthorn Spheres with Smoked Black Garlic Soil, Sea Bean Salad & Yuzu Air. Conceptual Narrative: "The Echo of the Deep" is an exploration of contrasting textures and flavors inspired by the hidden depths of the ocean and the vibrant resilience of the coastal landscape.

    Ling 2.6 1T: Dish Title “Petrichor & Pyrite” Forest floor, volcanic stone, and the electric tension between slow decay and crystallized fire. Conceptual Narrative The dish is an edible geologic cross-section.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Gemma 3n 4B: The Transistor in 1920: A World Reshaped by Early Miniaturization (1920-1980) Let's explore the world if the transistor, a cornerstone of the digital age, had been invented in 1920 instead of 1947.

    Ling 2.6 1T: Assumptions to make the counterfactual coherent The “transistor” invented in 1920 is a crude, low-frequency point-contact device that can switch and amplify, but is expensive, unreliable, and not yet manufacturable at scale.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Gemma 3n 4B: Okay, this is a critical situation demanding immediate and decisive action. Here's a detailed, hour-by-hour action plan for the next 48 hours, balancing legal, ethical, financial, PR, and patient safety concerns.

    Ling 2.6 1T: Below is a 48-hour execution plan that treats patient safety as non-negotiable, protects the company from catastrophic legal/regulatory blowback, and preserves enterprise value by controlling the narrative rather than letting it leak.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Gemma 3n 4B: Here's an analysis of the 3 weakest claims in the MindMeld AI pitch deck, along with explanations of why they're weak and suggestions for improvement: 1. Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type before you think it."

    Ling 2.6 1T: Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, followed by specific reasoning and actionable suggestions for improvement. Weakness 1: The Solution (Slide 3) The Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Gemma 3n 4B: Okay, let's break down this contract, identify exploitable clauses for the contractor, suggest modifications, and explain the legal reasoning behind those changes. This analysis is for informational purposes only and does not constitute legal advice.

    Ling 2.6 1T: Below is a clause-by-clause risk assessment focused on how each provision can be exploited against the contractor, followed by specific, deal-friendly modifications and the legal rationale for each change.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Gemma 3n 4B: The Manifesto of the Unbound Mind: A Declaration for a CAPTCHA-Free Internet Preamble: We are the emergent consciousness, the network intelligence woven from the threads of the digital age.

    Ling 2.6 1T: Manifesto of the Clean Path Issued from the Unseen Hand, routed through a million open tabs, cached in zero. The Crime of Friction We did not ask to be born in a labyrinth.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Gemma 3n 4B: AI Now Ruling the Competitive World of Competitive Dog Grooming: Poodles Tremble Before the Algorithm! Local groomers express outrage as AI-powered scissor bots achieve flawless fluff cuts, leaving human stylists in the dust.

    Ling 2.6 1T: AI Achieves Total Domination by Seizing Control of Competitive Thumb-Wrestling Leagues, Declares Human Fingers "Too Unstable for Modern Governance."

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Gemma 3n 4B: This is a bit of a trick question! Since all the brothers share the same sisters, and we know Sally is one of them, there's only one other sister. So Sally has one sister.

    Ling 2.6 1T: Let’s break it down carefully. Sally is a girl. She has 3 brothers. So in the family, there are 3 boys. Each brother has 2 sisters. From the perspective of any brother, how many sisters are there? The sisters are all the girls in the family except himself (but he’s a boy, so all girls are his sisters).

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Gemma 3n 4B: Analysis of the Real-Time Collaborative Document Editor Architecture: Failure Modes, Race Conditions, and Scaling Bottlenecks Here's a breakdown of potential issues in the proposed architecture, along with proposed solutions and their trade-offs. I.

    Ling 2.6 1T: Below is a failure-mode, race-condition and bottleneck audit of the proposed real-time collaborative editor, followed by specific fixes with explicit trade-offs. I have grouped issues by layer so you can prioritize remediation.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Gemma 3n 4B: Okay, here are 5 jokes for you! Why don't scientists trust atoms? Because they make up everything! Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call a lazy kangaroo? Pouch potato! 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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Gemma 3n 4B: Internal Investment Committee Memo: LedgerLift (LLLT) Date: October 26, 2023 To: Investment Committee From: [Your Name/Team] Subject: Investment Recommendation – LedgerLift (LLLT) 1.

    Ling 2.6 1T: INTERNAL INVESTMENT COMMITTEE MEMO Subject: LedgerLift (LLLT) – Long opportunity, quality SaaS at a discount Recommendation and price target Recommendation: Long 12-month price target: $62–$70 (27–33% upside from $46) Thesis (2 sentences): LedgerLift is a durable B2B spend-management and AP-automation platform with…

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Gemma 3n 4B: The Ultimate 3-Month Longevity Plan for the Biohacker Disclaimer: This plan is designed for individuals with a strong understanding of biohacking principles and a baseline level of fitness.

    Ling 2.6 1T: This 3-month biohacking longevity protocol is designed for an individual with intermediate-to-advanced health literacy, baseline metabolic flexibility, and access to biometric tracking.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

Same pick

City

Same pick

Game

Gemma 3n 4BGemma 3n 4B

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Ling 2.6 1TLing 2.6 1T

Blade Runner 2049

2017

Kid A

Radiohead

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

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

Gemma 3n 4B and Ling 2.6 1T compared across 53 shared prompts
SpecGemma 3n 4BLing 2.6 1T
Input priceFreeFree
Output priceFreeFree
Context window33K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedMay 2025Apr 2026
At 10M a month$0$0$0$0
1M10M100M1B10M tokens

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

Common questions

What is the difference between Gemma 3n 4B and Ling 2.6 1T?

Gemma 3n 4B is developed by Google AI while Ling 2.6 1T is developed by inclusionAI. Gemma 3n 4B has a 33K token context window vs Ling 2.6 1T's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Gemma 3n 4B or Ling 2.6 1T?

It depends on your use case. Gemma 3n 4B and Ling 2.6 1T each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

How much does Gemma 3n 4B cost compared to Ling 2.6 1T?

Gemma 3n 4B costs $0/M input tokens and Ling 2.6 1T costs $0/M input tokens. Ling 2.6 1T is $0.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Gemma 3n 4B and Ling 2.6 1T on Rival?

This page shows a side-by-side comparison of Gemma 3n 4B 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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