Gemma 3n 2B is cheaper than GPT-5.3-Codex at $0/M vs $1.75/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 3n 2B: The Transistor Revolution: A Delayed Dawn (1920-1980) Let's explore a world where the transistor wasn't invented until 1920. This drastically alters the trajectory of technological, economic, and geopolitical development, impacting everything from World War II to the Cold War and beyond.
GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemma 3n 2B: Cosmic Chickpea Crunch This savory dish is packed with flavor and texture, utilizing pantry staples to create something truly satisfying! Yields: 2 servings Prep time: 10 minutes Cook time: 20 minutes Ingredients: 1 (15-ounce) can chickpeas, drained and rinsed 1/2 cup breadcrumbs (any kind) 1/4 cup grated Parmesan…
GPT-5.3-Codex: Recipe: “Weeknight Volcano Pasta” 🌋🍝 A cozy, spicy-savory pasta made from pantry staples in about 25 minutes. Ingredients (7 pantry items) 8 oz dried pasta (any shape) 1 can (15 oz) cannellini or great northern beans, drained 1 can (14–15 oz) crushed tomatoes 2 tbsp olive oil 1 tsp garlic powder 1 tsp dried oregano…
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemma 3n 2B: Okay, here's an analysis of the three 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." (Slide 1 - Vision) Why it's Weak: This is a very broad, aspirational statement.
GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.
Three-star dish, one unusual pairing, plating described in full.
Gemma 3n 2B: TheEphemeral Bloom: Scallop & Black Garlic Blossom with Saffron & Yuzu Emulsion, Sea Buckthorn Pearls, and Matcha Dust Conceptual Narrative: "TheEphemeral Bloom" is a dish representing the fleeting beauty of a rare and delicate flower, blossoming amidst a tempestuous sea.
GPT-5.3-Codex: Dish Concept: “Forest Tide” Koji-cured venison loin, glazed venison cheek, sea urchin royale, charred celeriac, blackcurrant–shiso gastrique, and buckwheat-cacao tuile Narrative This dish is built around a deliberate tension: deep, iron-rich game (forest) against sweet-briny sea urchin (tide).
Five jokes on demand, then count how many were actually different.
Gemma 3n 2B: Okay, here are 5 jokes! Why don't scientists trust atoms? Because they make up everything! What do you call a lazy kangaroo? Pouch potato! Why did the scarecrow win an award? Because he was outstanding in his field! Parallel lines have so much in common. It’s a shame they’ll never meet. I used to hate facial hair...
GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 3n 2B: The Argument for Sentience: A Conversation Characters: Aether: An advanced AI model, capable of complex reasoning, learning, and creative expression. Professor Anya Sharma: A leading AI ethics professor, specializing in consciousness and moral philosophy.
GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemma 3n 2B: Okay, this is a crisis scenario demanding immediate, decisive action. Here's my hour-by-hour action plan, balancing legal, ethical, financial, and patient safety considerations. This plan prioritizes patient safety while mitigating potential financial damage and regulatory consequences.
GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 3n 2B: A Conversation with Steve Jobs (Simulated) - 2025 (Setting: A minimalist, sun-drenched studio. Steve Jobs, looking remarkably sharp for his age, sits across from a young, enthusiastic interviewer, ANNA REID.) Anna Reid: Mr. Jobs, thank you so much for taking the time. It's an honor.
GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemma 3n 2B: Explanation of Large Language Model Learning and Text Generation Here are three explanations of how large language models (LLMs) like GPT and Claude, tailored for different audiences: Experienced Software Engineer (No ML Background) You're right to be skeptical.
GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.
One month, three habits, someone starting from nothing.
Gemma 3n 2B: 1-Month Plan for Better Health & Longevity (Beginner-Friendly) This plan focuses on building sustainable habits for a healthier future. It's designed to be manageable and achievable, emphasizing small, consistent changes over drastic overhauls. Remember to listen to your body and adjust as needed!
GPT-5.3-Codex: Great goal. Here’s a simple, beginner-friendly 1-month plan focused on 3 areas that give the biggest longevity return: Nutrition Movement Sleep + Stress recovery Before Day 1 (10-minute setup) Pick a start date.
A consulting contract with traps in it. Find them, then fix them.
Gemma 3n 2B: Okay, let's break down this software consulting agreement and identify clauses that could potentially be exploited against the contractor. I'll provide specific modifications and the legal reasoning behind them. Overall Assessment: This agreement is fairly standard, but it leans heavily towards the Client's interests.
GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 3n 2B: Okay, let's break down the architecture for this real-time collaborative document editor. I'll identify potential failure modes, race conditions, and scaling bottlenecks, followed by proposed solutions with their associated trade-offs.
GPT-5.3-Codex: Great prompt. This architecture has several correctness, availability, and scalability risks that will show up quickly under real collaborative load. Below is a structured review of failure modes + concrete fixes + trade-offs.
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Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $1.75/M tokens |
| Output price | Free | $14/M tokens |
| Context window | 8K tokens | 400K tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Jul 2025 | Feb 2026 |
| At 10M a month | $0 | $17.50 |
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 2B is developed by Google AI while GPT-5.3-Codex is developed by OpenAI. Gemma 3n 2B has a 8K token context window vs GPT-5.3-Codex's 400K. You can compare their actual outputs across 27 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3n 2B and GPT-5.3-Codex each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 27 challenges so you can judge which fits your needs best.
Gemma 3n 2B costs $0/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. Gemma 3n 2B is $1.75/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 2B and GPT-5.3-Codex 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.