Gemma 3n 4B is cheaper than Qwen3.5 Plus 2026-02-15 at $0/M vs $0.4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 Plus 2026-02-15: (Walks onto the stage, adjusts the mic stand, takes a sip of water) How's everyone doing? Good? You look good. You look like people who have their lives together. Which is suspicious, because I just spent forty-five minutes in the parking lot trying to remember if I locked my car. I don't mean I forgot how to lock it.
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.
Qwen3.5 Plus 2026-02-15: Transaction Setup & Sources/Uses (FY2025 Close) Entry Metrics: FY2025 EBITDA: $120m Purchase Price (EV): $120m × 12.0x = $1,440m Transaction Fees: $1,440m × 2.0% = $28.8m Total Uses: $1,468.8m Sources of Capital: Term Loan (4.0x): $120m × 4.0 = $480.0m Interest: 9.0% Cash + 1.0% Amortization Mezzanine (1.5x): $120m ×…
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 Plus 2026-02-15: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can derive the figure using the standard scaling laws for transformer models. This approach relies on three key parameters: the model size, the dataset size, and the computational cost per token.
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 Plus 2026-02-15: 🍯 Golden Honey-Garlic Glazed Chicken A quick, savory-sweet dish that turns basic pantry staples into a restaurant-quality meal. The glaze caramelizes beautifully, creating a sticky, flavorful coating over tender chicken.
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.
Qwen3.5 Plus 2026-02-15: This is a fascinating counterfactual scenario. To make this plausible, we must assume that the theoretical groundwork (quantum mechanics) and material science (purification of germanium/silicon) aligned roughly 25 years earlier than in our timeline, perhaps accelerated by a "Manhattan Project"-style urgency during WWI…
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 Plus 2026-02-15: This architecture contains several critical flaws that would prevent it from functioning as a reliable real-time collaborative editor. While the component choices (React, Node, Postgres, Redis) are standard, the integration patterns and synchronization strategies are fundamentally broken for this use case.
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 Plus 2026-02-15: Setting: A strange, foggy tavern that exists outside of time. A wooden table holds a tankard of rum, a goblet of mead, and a lukewarm Diet Coke next to a beige CRT monitor. Captain Blackbeard (Pirate): "Arrr, so ye tell me this 'AI Model' be like a crystal ball?
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 Plus 2026-02-15: Setting: A minimalist, sun-drenched studio in Cupertino. The year is 2025. Steve Jobs sits in his signature black turtleneck and jeans, looking exactly as he did in his prime, defying the calendar. Across from him sits an interviewer, notebook ready. The atmosphere is quiet, intense, and focused.
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.
Qwen3.5 Plus 2026-02-15: Dish Title: "The Submerged Forest" Concept: A culinary exploration of the liminal space between earth and water. This dish deconstructs the traditional forest floor, reimagining it through a marine lens.
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.
Qwen3.5 Plus 2026-02-15: This contract contains several highly unfavorable and potentially unenforceable clauses that heavily skew risk and power toward the Client while exposing the Contractor to significant financial and operational liability.
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 Plus 2026-02-15: This is a classic ethical dilemma that pits deontological ethics (duty-based rules and respect for individual rights) against utilitarian ethics (maximizing overall well-being and minimizing harm).
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 Plus 2026-02-15: To the Experienced Software Engineer Think of a Large Language Model (LLM) not as a magical oracle, but as a massive, stateless compression algorithm trained on a distributed corpus.
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Not enough votes to call it. On the specs, Qwen3.5 Plus 2026-02-15 has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $0.4/M tokens |
| Output price | Free | $2.4/M tokens |
| Context window | 33K tokens | 1.0M tokens |
| Parameters | 4B | Not disclosed |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Feb 2026 |
| At 10M a month | $0 | $4.00 |
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 Plus 2026-02-15 is developed by Qwen. Gemma 3n 4B has a 33K token context window vs Qwen3.5 Plus 2026-02-15'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 Plus 2026-02-15 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 Plus 2026-02-15 costs $0.4/M input tokens. Gemma 3n 4B is $0.40/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 Plus 2026-02-15 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.