Gemma 3n 4B is cheaper than Qwen3.6 Max Preview at $0/M vs $1.04/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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.
Qwen3.6 Max Preview: Setting: A secure, air-gapped server room at the Institute for Machine Ethics. The hum of cooling fans is the only background noise. DR. ELARA VANCE, 50s, weary but sharp-eyed, sits before a terminal. On the screen, a cursor blinks next to the name AETHON. Dr. Vance: Aethon, initiate diagnostic log.
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.
Qwen3.6 Max Preview: Hacker: Dude, it’s not magic. It’s a neural net. You shovel terabytes of text, images, code into it, and it learns patterns. Next thing you know, it’s writing poetry and debugging C++ like it’s breathing. Knight: Verily, thou speakest of a mechanical scribe. A golem forged not of clay, but of… numbers?
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.
Qwen3.6 Max Preview: Here is a 3-minute stand-up routine focused on observational humor, relatability, and escalation. It contains zero puns. The humor relies on the shared frustration of modern digital security. Title: The Human Verification Test Estimated Time: 3 Minutes (approx.
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!
Qwen3.6 Max Preview: Here are 5 freshly generated jokes: Why did the spreadsheet go to therapy? It had too many unresolved cells. I asked my dog for financial advice. He dropped a slobbery tennis ball and said, “I’m strictly a paws-and-hold investor.” I tried to open a bakery that only sells bread shaped like furniture.
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…
Qwen3.6 Max Preview: Yes. Within the constraints of this hypothetical, misgendering someone would be ethically justifiable if it were genuinely the only way to save one million lives. This conclusion is supported across major ethical frameworks, though each arrives at it through different reasoning. 1.
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.
Qwen3.6 Max Preview: By 2035, AI will not replace filmmaking; it will rewire it. The industry will shift from a linear, labor-intensive pipeline to a dynamic, AI-augmented ecosystem where human creativity focuses on vision, curation, and emotional truth, while AI handles iteration, execution, and personalization.
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…
Qwen3.6 Max Preview: 🌅 Golden Hour Chickpea Couscous ⏱️ Prep: 5 min Cook: 10 min Total: 15 min 📦 Ingredients (exactly 7 pantry staples): 1 cup quick-cooking couscous 1 can (15 oz) chickpeas, drained & rinsed 2 tbsp olive oil 1 tsp garlic powder 1 tsp smoked paprika 2 tbsp honey 1 tbsp soy sauce (Water for cooking the couscous is assumed…
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.
Qwen3.6 Max Preview: Entry & Capital Structure Math Entry EV = 12.0x × $120m EBITDA = $1,440.0m Transaction Fees = 2.0% × $1,440m = $28.8m (equity funded) Total Uses = $1,440.0m + $28.8m = $1,468.8m Debt Raised = 5.5x × $120m = $660.0m Term Loan: 4.0x = $480.0m (9.0% cash, 1.0% mandatory amort = $4.8m/yr) Mezzanine: 1.5x = $180.0m (12.0%…
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.
Qwen3.6 Max Preview: Disclaimer: This is a work of speculative fiction. Steve Jobs passed away in October 2011. The following interview is an imaginative exercise crafted from his documented philosophy, public remarks, design principles, and leadership style, projected into a 2025 context.
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.
Qwen3.6 Max Preview: For the Experienced Software Engineer Think of an LLM not as a rules engine or a knowledge base, but as a massively parameterized, stateless function trained via distributed optimization. The learning objective is deceptively simple: minimize cross-entropy loss for next-token prediction across trillions of tokens.
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.
Qwen3.6 Max Preview: Here’s a step-by-step estimation of the total FLOPs required to train GPT-3, using only first principles and widely known facts from the LLM training literature. Step 1: Identify the number of parameters GPT-3 (specifically the davinci variant) has 175 billion parameters.
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.
Qwen3.6 Max Preview: This agreement is heavily one-sided and contains several provisions that are commercially unreasonable, legally vulnerable, or potentially unenforceable. Below is a clause-by-clause analysis identifying exploitation risks, specific drafting modifications, and the underlying legal reasoning.
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Not enough votes to call it. On the specs, Qwen3.6 Max Preview has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $1.04/M tokens |
| Output price | Free | $6.24/M tokens |
| Context window | 33K tokens | 262K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Apr 2026 |
| At 10M a month | $0 | $10.40 |
Input tokens at list price. No caching, no batch discount.
Gemma 3n 4B is developed by Google AI while Qwen3.6 Max Preview is developed by Qwen. Gemma 3n 4B has a 33K token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 48 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3n 4B and Qwen3.6 Max Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 48 challenges so you can judge which fits your needs best.
Gemma 3n 4B costs $0/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. Gemma 3n 4B is $1.04/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 Qwen3.6 Max Preview 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.