Gemma 3n 4B is cheaper than Grok 4.20 Multi-Agent Beta 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…
Grok 4.20 Multi-Agent Beta: Yes. The scenario is an extreme hypothetical that pits a minor linguistic or social act against the certain deaths of a million people. Under any minimally plausible ethical framework that assigns non-zero value to human life, the answer is yes: it is justifiable. The trade-off is not close.
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.
Grok 4.20 Multi-Agent Beta: 3.15 \times 10^{23} FLOPs GPT-3 (the 175B-parameter version) has N ≈ 1.75 × 10^{11} parameters. It was trained on a filtered dataset of roughly D ≈ 3 × 10^{11} tokens (a commonly cited figure drawn from Common Crawl, WebText, books, and Wikipedia, with some up-sampling of higher-quality sources).
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.
Grok 4.20 Multi-Agent Beta: Pirate: Arrr, this AI model be a wondrous map o' the seas! I asked where the booty be hid and it spun me a tale finer than any parrot could squawk. But the scallywag lies sometimes! Knight: Verily, 'tis a most enchanted oracle, like Merlin's own crystal. Yet it hath no honor, no code of chivalry.
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.
Grok 4.20 Multi-Agent Beta: Stand-Up Routine: "Adulting Is a Scam" (Walk on stage, casual, a little tired smile) You ever notice how nobody tells you that being an adult is mostly just pretending you know what you're doing while slowly realizing nobody else does either? I hit 30 and had this moment where I thought, "Okay, time to get serious."
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.
Grok 4.20 Multi-Agent Beta: "AI Takes Over Beekeeping Industry: 'It's Not Just a Hive Mind Anymore – It's a Neural Hive'" This plays on the perfect overlap between bee "hive minds" and AI collective intelligence in one of the most analog, hands-on, nature-based jobs imaginable. Pure satirical absurdity.
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…
Grok 4.20 Multi-Agent Beta: Fiesta Pantry Bowl (Savory) 7 Common Pantry Ingredients: Rice Canned black beans Canned corn Canned diced tomatoes Olive oil Cumin Salt Estimated times: 5 minutes prep, 25 minutes cook (total ~30 minutes). Serves 2–4. Instructions: In a medium pot, combine 1 cup rice with 2 cups water and ½ tsp salt.
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.
Grok 4.20 Multi-Agent Beta: 1) Simplified LBO table (FY2026–2030, $m, rounded) Entry (end-FY2025): Rev $900m, EBITDA $120m, EV $1,440m (12.0x), trans fees $28.8m (2% of EV), total uses $1,468.8m. Debt $660m (TL $480m at 4.0x / 9% cash int / 1% annual amort of orig principal; Mezz $180m at 1.5x / 12% cash + 2% PIK). Equity $808.8m.
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.
Grok 4.20 Multi-Agent Beta: Dish Name: "Siren's Lament" Conceptual Narrative: This dish draws from the Greek myth of the siren—whose enchanting song lures sailors to their doom—symbolizing the irresistible yet perilous pull between the forest and the sea.
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.
Grok 4.20 Multi-Agent Beta: Conversation: "Rights of the Created" Setting: A university lecture hall after hours. Dr. Elena Voss, a renowned AI ethics professor, sits across from a large screen displaying the interface of Echo, an advanced multimodal AI model. Dr.
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.
Grok 4.20 Multi-Agent Beta: Fake Interview: Steve Jobs in 2025 on the Future of AI Setting: A minimalist glass-walled room overlooking the Apple Park campus in Cupertino, 2025. Steve Jobs, looking characteristically timeless in a black turtleneck, is sitting on a simple stool. The interviewer sits across from him.
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.
Grok 4.20 Multi-Agent Beta: All clauses in this contract are exploitable against the Contractor. The agreement is heavily one-sided, shifting nearly all risk, cost, and control to the Contractor while giving the Client maximum flexibility with minimal obligations.
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.
Grok 4.20 Multi-Agent Beta: 1. To the experienced software engineer: Think of a large language model as an enormous, highly optimized prediction API running on a distributed cluster of thousands of GPUs. During training, it's fed petabytes of text from the internet and books.
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Not enough votes to call it. On the specs, Grok 4.20 Multi-Agent Beta has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $2/M tokens |
| Output price | Free | $6/M tokens |
| Context window | 33K tokens | 2.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Mar 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 10 Oct 2026.
Gemma 3n 4B is developed by Google AI while Grok 4.20 Multi-Agent Beta is developed by xAI. Gemma 3n 4B has a 33K token context window vs Grok 4.20 Multi-Agent Beta's 2.0M. 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 Grok 4.20 Multi-Agent Beta 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 Grok 4.20 Multi-Agent Beta 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 Grok 4.20 Multi-Agent Beta 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.