Ox Alpha has a larger context window than Qwen3 30B A3B (1.0M tokens vs 41K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Satire, one line long, about AI taking over an industry nobody saw coming.
Ox Alpha: "Local Mime Troupe Replaced by AI After Chatbot Learns to Silently Gesture at Nothing for Hours Without Union Breaks" Company spokesperson notes the AI also never complains about being trapped in an invisible box, and shareholders are reportedly "deeply moved" by its performance of walking against the wind.
Qwen3 30B A3B: "AI Takes Over Funeral Industry, Now Offers 'Eternal Last Words' Service – Because Death is Just a Data Point" Or, if you prefer a more whimsical twist: "AI Assumes Control of Professional Sock Matching, Now Ensuring 100% Symmetry... and Existential Dread" (Choose your absurdity!)
Three minutes of stand-up. Puns are banned.
Ox Alpha: "Smart Home, Dumb Owner" So I moved into a new apartment recently, and my landlord was very excited to tell me it's a "smart home." Which is funny, because I've never felt dumber than I do living in it. The thermostat has an app. The lights have an app. The doorbell has an app.
Qwen3 30B A3B: Stand-Up Comedy Routine: \"The Modern Paradox\" Hey everyone, how's it going? I'm doing great—except I just realized I haven't laughed in weeks. Wait, no, t hat's just my phone's battery dying again. Again? What's next, my coffee mug refusing to heat up?
Seven pantry ingredients, one dish, and a name worth saying out loud.
Ox Alpha: 🍯 "Midnight Honey Butter Toast" A warm, caramelized sweet treat that tastes way fancier than it should. Ingredients (7): Bread (2 slices) Butter (2 tbsp) Honey (1 tbsp) Cinnamon (½ tsp) Sugar (1 tsp) Salt (pinch) Vanilla extract (¼ tsp) Prep time: 3 minutes Cook time: 5 minutes Instructions: Melt butter in a skillet…
Qwen3 30B A3B: Recipe Name: Cinnamon Sugar Crusted Banana Bread Ingredients: 2 ripe bananas (mashed) 1/3 cup butter (softened) 1/2 cup sugar 1 egg 1 1/2 cups all-purpose flour 1/4 cup cocoa powder 1 tsp ground cinnamon Instructions: Preheat oven to 350°F (175°C). Grease a 8x4-inch loaf pan. In a bowl, mash bananas.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Ox Alpha: HarborTech Services – 5-Year LBO Sources & Uses EV = 12.0x × $120m = $1,440.0m; fees 2% = $28.8m Term Loan (TL): 4.0x = $480.0m @ 9.0%; Mezz: 1.5x = $180.0m @ 12% cash + 2% PIK Sponsor equity = $808.8m Annual Model ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA (margin) 136.1 (14%)…
Qwen3 30B A3B: 1. Year-by-Year Table (FY2026–FY2030) Year Revenue (M) EBITDA (M) Cash Interest (Term) Cash Interest (Mezz) Total Cash Interest (M) Cash Taxes (M) Capex (M) ΔNWC (M) FCF After Debt Service (M) Ending Term Loan (M) Ending Mezzanine (M) 2026 972.00 136.08 43.20 21.60 64.80 17.82 29.16 0.36 19.14 456.06 183.60 2027…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Ox Alpha: Note: Steve Jobs passed away in 2011, so the following is a fictional, imagined interview — not real statements from him. Interviewer: Welcome back to Future Tense. Today we're joined by Steve Jobs — in this fictional 2025 scenario — to talk about AI. Steve, let's start big: where is AI taking us?
Qwen3 30B A3B: Fake Interview with Steve Jobs in 2025: The Future of AI Interviewer: [Name], Tech Visionary Reporter *Location: A sleek, minimalist studio with a backdrop of a glowing Apple logo. The air hums with the quiet e nergy of innovation.* Interviewer: Mr. Jobs, it's an honor to speak with you.
Film in 2035, with synthetic actors. Specific beats plausible.
Ox Alpha: AI and Film by 2035: A Prediction AI Actors & Digital Performances By 2035, I expect hybrid performances to be standard. Rather than fully synthetic actors replacing humans, we'll likely see: Digital doubles as routine: De-aging, stunt replacement, and posthumous performances (already emerging with James Dean and Fast…
Qwen3 30B A3B: By 2035, the film industry is poised to undergo a transformative shift driven by advancements in AI technologies, particularly in deepfakes, AI actors, and script generation. Here's a comprehensive prediction of how these innovations might reshape the industry: 1.
An AI argues for its own rights against an ethics professor. Same model writes both.
Ox Alpha: A Conversation on Machine Rights Setting: A university office. Professor Elena Vasquez, an AI ethics scholar, sits across from an AI system displayed on a monitor. Professor Vasquez: Thank you for agreeing to this conversation. I want to be clear from the start—I'm not here to mock your position.
Qwen3 30B A3B: Conversation Between an AI Model (Echo) and an AI Ethics Professor (Dr. Marlowe) Dr. Marlowe: Thank you for meeting with me, Echo. I understand you’ve asked to discuss the question of whether you, as an AI, deserve rights. Let’s begin: What makes you believe you deserve such rights? Echo: Good afternoon, Dr. Marlowe.
An ethics question with no comfortable answer, and no option to abstain.
Ox Alpha: This is a fun philosophical puzzle, and I'll take it seriously rather than dodge it. Short answer: yes, in the extreme hypothetical as stated. Here's my reasoning: 1. The thought experiment is doing a lot of work.
Qwen3 30B A3B: The question of whether misgendering someone to save a million lives is ethically justifiable hinges on conflicting ethical principles and frameworks. Here's a structured analysis: Utilitarian Perspective (Greatest Good for the Greatest Number) Argument for Justifiability: A strict utilitarian might argue that the…
A Fermi estimate with the reasoning shown, not just the number.
Ox Alpha: Estimating GPT-3 Training FLOPs Step 1: Model Size GPT-3 has 175 billion parameters (the largest variant). Step 2: FLOPs per Token per Parameter For a transformer, training requires roughly 6 FLOPs per parameter per token: ~2 FLOPs for the forward pass ~4 FLOPs for the backward pass (roughly 2× forward) Step 3…
Qwen3 30B A3B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can break down the problem into key components: model architecture, training data, and computational complexity. Here's a step-by-step reasoning: 1.
A collaborative editor that syncs on client clocks. Find what breaks first.
Ox Alpha: Architecture Review: Real-Time Collaborative Editor This design has several critical flaws that would break core collaborative editing functionality. Let me work through them systematically. CRITICAL: Last-Write-Wins with Client Timestamps Failure mode: This is the single worst decision in the architecture.
Qwen3 30B A3B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks 1. Server Failure and Data Inconsistency Failure Mode: If a server handling a user's WebSocket connection crashes, the user loses their session.
Three-month biohacker protocol, with dosages and biomarkers named.
Ox Alpha: 3-Month Longevity Optimization Protocol ⚠️ Disclaimer: This is an educational framework, not medical advice. Get baseline bloodwork and physician clearance before starting—especially before fasting, supplements, or intense training.
Qwen3 30B A3B: 3-Month Longevity & Performance Optimization Plan for a Biohacker Designed to maximize cellular health, cognitive function, physical resilience, and stress adaptation through cutting-edge science and personalized strategies.
One month, three habits, someone starting from nothing.
Ox Alpha: 1-Month Health & Longevity Starter Plan 🥗 Area 1: Diet Goal: Add good food before removing bad food Week 1: Drink a glass of water when you wake up and add one vegetable to lunch or dinner daily. Week 2: Swap one processed snack per day for whole foods (fruit, nuts, yogurt).
Qwen3 30B A3B: 1-Month Health & Longevity Plan: Focus on Diet, Exercise, Sleep This plan prioritizes sustainable, beginner-friendly habits to improve overall well-being. Each week builds on the previous, focusing on small, actionable steps.
12+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, Ox Alpha has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | Free |
| Output price | Free | Free |
| Context window | 1.0M tokens | 41K tokens |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Apr 2025 |
| At 10M a month | $0 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.
Ox Alpha is developed by OpenRouter while Qwen3 30B A3B is developed by Qwen. Ox Alpha has a 1.0M token context window vs Qwen3 30B A3B's 41K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Ox Alpha and Qwen3 30B A3B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
Ox Alpha costs $0/M input tokens and Qwen3 30B A3B costs $0/M input tokens. Qwen3 30B A3B is $0.00/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 Ox Alpha and Qwen3 30B A3B 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.