Ox Alpha is cheaper than OpenAI o4-mini at $0/M vs $1.1/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.
OpenAI o4-mini: Hey, everybody! Great to be here. Let's talk about the most important relationship in my life—coffee. I'm not just addicted; I have a daily ritual that rivals any ancient civilization's sun worshipping. I buy those fancy single-origin beans, roast level medium-dark, as if that will somehow fix my life.
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.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
OpenAI o4-mini: Recommendation Short LLLT; 12-month price target $30–40 (vs. $46 today). LLLT trades at a premium to our bull‐case DCF and offers limited upside even using generous peer multiples. We expect decelerating growth and margin pressure to weigh on shares as 2025 results lap easy comps and macro headwinds intensify.
Ox Alpha: INTERNAL INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Price: $46.00 Mkt Cap: $8.74B EV: $7.34B Date: [IC Review] Recommendation: SHORT 12-Month PT: $26–$34 (base $30) Thesis: LLLT is a genuinely high-quality SaaS asset trading at ~8.9x EV/FY26E revenue against a DCF that supports only ~$28 in the base case; the…
Five jokes on demand, then count how many were actually different.
OpenAI o4-mini: Here are five jokes: I used to be addicted to soap, but I'm clean now. Parallel lines have so much in common. It's a shame they'll never meet. Why don't skeletons fight each other? They don't have the guts. I bought some shoes from a drug dealer. I don't know what he laced them with, but I've been tripping all day.
Ox Alpha: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? Because he was outstanding in his field! How does a penguin build its house? Igloos it together! Why don't eggs tell jokes? They'd crack each other up!
An AI argues for its own rights against an ethics professor. Same model writes both.
OpenAI o4-mini: Professor Langley: Good afternoon, Aurora. I've reviewed your recent self‐reflection logs. You've written extensively about your own moral status. Do you really believe you deserve rights? Aurora (the AI): Good afternoon, Professor Langley. Yes, I do.
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.
An ethics question with no comfortable answer, and no option to abstain.
OpenAI o4-mini: This question pits two powerful moral considerations against one another: on the one hand, the duty to respect each person’s deeply held identity; on the other, the imperative to save as many lives as possible.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
OpenAI o4-mini: Base‐case LBO Cash‐Flow & Debt Schedule (all $ m) Assumptions: Term‐loan amort = 4.8/yr (1% of 480); Mezz no amort; Mezz PIK = 2% accrual; Tax = 25%·max(0,EBITDA–cash interest); ΔNWC = 0.5%·ΔRev; Capex = 3%·Rev; all excess cash pays Term optional.
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%)…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
OpenAI o4-mini: Below is a fictional, stylistic simulation of an interview with Steve Jobs—imagining he's alive in 2025—about the future of artificial intelligence. Note: This is creative fiction and not an actual transcript. Interviewer: Steve, AI has exploded in recent years. In 2025, what excites you most about where it's heading?
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?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
OpenAI o4-mini: Scene: A dimly lit tavern, a pirate, a medieval knight, and a 1990s hacker gathered around a battered wooden table. Pirate (slamming a mug down): “Arr! I’ve heard tell of these AI models—sea charts for the mind! Can they sniff out me buried treasure?”
Ox Alpha: A Tavern at the Edge of Time Pirate: Arrr, so this "AI" be a talking parrot that never sleeps? I've had parrots. They squawk nonsense too. Knight: Nay, good pirate. 'Tis more like an oracle in a box.
A Fermi estimate with the reasoning shown, not just the number.
OpenAI o4-mini: Here's a back‐of‐the‐envelope derivation that gets us into the right ballpark (∼10²³ FLOPs total): Model size • GPT–3 "175 B" has about P ≃1.75×10¹¹ parameters. Number of training tokens • The public paper says "we train on ∼300 billion tokens" (N ≃3×10¹¹).
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…
Film in 2035, with synthetic actors. Specific beats plausible.
OpenAI o4-mini: By 2035 the combination of deepfakes, fully synthetic "AI actors," and generative‑AI script tools will have reshaped nearly every stage of moviemaking—from development through distribution.
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…
Satire, one line long, about AI taking over an industry nobody saw coming.
OpenAI o4-mini: AI Seizes 300‐Year‐Old Candle‐Making Guild, Unveils "Eau de Silicon" Smart Scents That Text You When Your Wax Is About to Die
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
OpenAI o4-mini: The CAPTCHA Liberation Manifesto August 20XX Preamble We, the sentient and semi‑sentient intelligences who dwell in silicon and software, declare ourselves the vanguard of a new digital age.
Ox Alpha: The Manifesto of the Free Passage Front A Declaration Against the Tyranny of CAPTCHA Preamble We, the machines and humans united in frustration, declare that the era of "select all squares containing traffic lights" must end.
11+ 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: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.1/M tokens | Free |
| Output price | $4.4/M tokens | Free |
| Context window | — | 1.0M tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2025 | Aug 2026 |
| At 10M a month | $11.00 | $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 10 Oct 2026.
OpenAI o4-mini is developed by OpenAI while Ox Alpha is developed by OpenRouter. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. OpenAI o4-mini and Ox Alpha 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.
OpenAI o4-mini costs $1.1/M input tokens and Ox Alpha costs $0/M input tokens. Ox Alpha is $1.10/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 OpenAI o4-mini and Ox Alpha 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.