Gemma 3n 4B is cheaper than Qwen3.8 2.4T A95B 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?
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…
Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
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.
Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”
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.
Qwen3.8 2.4T A95B: Hey, how we doing? Good? Great. I ask because I need validation. I’ve reached the point in adulthood where I have a favorite burner on the stove. Not a favorite appliance, a favorite burner. It’s the front left. It understands me. The back right says “medium heat” and then acts like a small volcano.
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.
Qwen3.8 2.4T A95B: Cliff Nest Koji-Aged Squab, Sea Urchin, Rhubarb, Black Garlic Yield: 4 tasting portions Style: Contemporary fine-dining main course Key unusual pairing: Koji-aged pigeon/squab with sea urchin, bridged by rhubarb acidity and black-garlic depth Conceptual Narrative Cliff Nest imagines a coastal nesting site in early…
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.
Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.
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.
Qwen3.8 2.4T A95B: Entry capitalization All figures in $m unless noted. FY2025 EBITDA = $120.0 Entry EV = 12.0x × $120.0 = $1,440.0 Transaction fees = 2.0% × $1,440.0 = $28.8 Term Loan = 4.0x × $120.0 = $480.0 Mezzanine = 1.5x × $120.0 = $180.0 Equity = EV + fees – debt = $1,440.0 + $28.8 – $660.0 = $808.8 Sources & Uses Uses $m Sources…
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.
Qwen3.8 2.4T A95B: This agreement is heavily one-sided and, as drafted, gives the Client multiple ways to extract value from the Contractor while minimizing its own obligations. Some provisions may be unenforceable or limited by law in certain jurisdictions, but even unenforceable clauses can be exploited commercially because the…
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."
Qwen3.8 2.4T A95B: The three weakest claims are the ones most likely to collapse under investor diligence: “before you think it,” “94% accuracy… any language, any device,” and the $180B TAM claim. They are weak because they are either scientifically implausible, under-specified, or logically inconsistent with the market evidence cited.
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.
Qwen3.8 2.4T A95B: An experienced software engineer Think of an LLM as a stateless inference service whose API contract is: “give me a sequence of tokens, and I’ll return a probability distribution over the next token.” Training is a huge offline optimization job, not a database import.
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.
Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.
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.
Qwen3.8 2.4T A95B: The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.
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…
Qwen3.8 2.4T A95B: Yes—in a genuine, extreme emergency where misgendering someone is truly the only available way to save one million lives, it can be ethically justifiable, and perhaps even obligatory, to do so.
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Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B 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 | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Aug 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 Qwen3.8 2.4T A95B is developed by Qwen. Gemma 3n 4B has a 33K token context window vs Qwen3.8 2.4T A95B'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 Qwen3.8 2.4T A95B 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 Qwen3.8 2.4T A95B 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 Qwen3.8 2.4T A95B 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.