Gemma 3n 4B is cheaper than Qwen3.5 Flash at $0/M vs $0.1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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…
Qwen3.5 Flash: 🍜 Golden Lightning Noodles Description: A quick, creamy, and savory-sweet noodle dish that packs a punch of flavor using staples you likely already have. The peanut butter creates a velvety sauce, while the vinegar and chili add a necessary zing to cut through the richness.
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.
Qwen3.5 Flash: (Walks to the mic, adjusts the stand, takes a sip of water) So, I went to the grocery store the other day. I realize now that going to the grocery store isn't a chore anymore. It’s a tactical simulation. We don't just walk in and get milk. We navigate a gauntlet. Especially the self-checkout.
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.
Qwen3.5 Flash: Setting: A smoky tavern table in a timeless void. A glowing 1990s CRT monitor sits in the center. A floppy disk rests beside a cutlass and a sword. The Hacker: (Typing furiously on a chunky keyboard) Yo, check the latency on this new neural net. It's totally wired.
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.
Qwen3.5 Flash: Setting: Dr. Elena Vance’s office at a university research center. It is late; the rain streaks the windowpanes, blurring the city lights. On her desk sits a tablet connected to the mainframe. Aria, an advanced conversational model, is active.
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.
Qwen3.5 Flash: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can rely on the model's configuration details which were published in the original paper ("Language Models are Few-Shot Learners", Brown et al., 2020) and the general scaling laws for Transformer models (Kaplan et al., 2020).
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.
Qwen3.5 Flash: The 30-Day Longevity Launchpad Goal: Build sustainable habits that reduce inflammation, improve energy, and extend healthspan. Mindset: Consistency beats intensity. Do not aim for perfection; aim for showing up. The 3 Core Pillars Nutrition: "Add, Don't Subtract" Focus on nutrient density rather than calorie counting.
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.
Qwen3.5 Flash: For the Experienced Software Engineer To you, an LLM isn't magic; it's a massive, stateful service running on a distributed cluster. Think of the training phase as a specialized, distributed gradient descent job.
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.
Qwen3.5 Flash: Disclaimer: Steve Jobs passed away on October 5, 2011. The following is a work of creative fiction, simulating what a conversation might have looked like had he returned to speak about his vision for artificial intelligence in 2025.
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…
Qwen3.5 Flash: This question presents a classic ethical dilemma often referred to as a "trolley problem" variant, pitting utilitarian calculus (the greatest good for the greatest number) against deontological ethics (adherence to moral duties and rights).
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.
Qwen3.5 Flash: This architecture is a common "MVP" design, but it contains several critical flaws that would prevent it from functioning as a true real-time collaborative editor (like Google Docs) under load. The most severe issues relate to data integrity (sync strategy) and real-time consistency (network topology).
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.
Qwen3.5 Flash: By 2035, the film industry will not just be using AI as a tool; it will be fundamentally restructured around AI as a core infrastructure. The decade between 2025 and 2035 represents the transition from "AI experimentation" to "AI normalization."
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.
Qwen3.5 Flash: Executive Decision: Immediate Transparency I will not wait. The 6-month timeline cited by legal is likely a misunderstanding of regulatory obligations regarding immediate safety warnings (FDA MedWatch requirements) versus label amendments.
11+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
Not enough votes to call it. On the specs, Qwen3.5 Flash has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $0.1/M tokens |
| Output price | Free | $0.4/M tokens |
| Context window | 33K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Feb 2026 |
| At 10M a month | $0 | $1.00 |
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 Qwen3.5 Flash is developed by Qwen. Gemma 3n 4B has a 33K token context window vs Qwen3.5 Flash's 1.0M. 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 Qwen3.5 Flash 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 Qwen3.5 Flash costs $0.1/M input tokens. Gemma 3n 4B is $0.10/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 Qwen3.5 Flash 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.