Gemma 3n 4B is cheaper than GPT-6.1 Sol at $0/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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…
GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.
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.
GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.
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…
GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…
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.
GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”
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.
GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.
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.
GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.
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.
GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.
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.
GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.
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!
GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.
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.
GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.
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.
GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.
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."
GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.
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Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $2/M tokens |
| Output price | Free | $10/M tokens |
| Context window | 33K tokens | 1.1M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Sep 2026 |
| At 10M a month | $0 | $20.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
Gemma 3n 4B is developed by Google AI while GPT-6.1 Sol is developed by OpenAI. Gemma 3n 4B has a 33K token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3n 4B and GPT-6.1 Sol 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.
Gemma 3n 4B costs $0/M input tokens and GPT-6.1 Sol costs $2/M input tokens. Gemma 3n 4B is $2.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Gemma 3n 4B and GPT-6.1 Sol 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.