Owl Alpha is cheaper than o1 at $0/M vs $15/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
o1: Pirate (growling a bit): Ahoy, ye landlubbers! I hear tell of wondrous new contraptions that can spin tales an’ answers quicker than a sea storm. Pray tell, what be these “AI models” ye speak of? Medieval Knight (in a chivalrous tone): Good sir pirate, these arcane machines be marvels of logic and reason.
Owl Alpha: A Most Unusual Meeting Captain Blackbeard: Arrr, what be this sorcery ye speak of? A model that can talk and think? Sir Galahad: By the King's crown! You say this artificial mind requires no soul yet can compose poetry? I must challenge it to a duel of wits! Cool_Haxor_95: LOL yeah dudes, it's totally rad.
Three minutes of stand-up. Puns are banned.
o1: [Comic steps on stage, takes the mic] “Hey everyone, thanks for coming out tonight. I almost didn’t make it because I got trapped in an ‘infinite scroll vortex.’ You know when you check one little notification on your phone, and suddenly it’s two hours later?
Owl Alpha: Alright, hello everyone! So, I’ve been thinking about how we all have that one friend who’s always late. Not just late—like, fashionably late. Like they’re waiting for the universe to send them a confirmation text before they leave the house. “Is it okay to arrive yet? Has the planet aligned?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
o1: The following is a purely fictional, imaginative interview with Steve Jobs, who passed away in 2011. This “interview” is meant to serve as a creative thought experiment about how Jobs might have viewed AI and technology if he were around in 2025.
Owl Alpha: [Camera clicks on. A minimalist stage. Soft lighting. A familiar black turtleneck. A knowing smile.] Interviewer: Steve, thank you for joining us. The world has changed so much. What’s your first thought about the state of AI in 2025? Steve Jobs: It’s a tool. A profoundly powerful tool. But it’s still just a tool.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
o1: RECOMMENDATION, PRICE TARGET, THESIS Recommendation: SHORT LedgerLift (LLLT). 12-month Price Target Range: $25–$35 (implying 25–45% downside). Thesis (2 sentences): Our DCF and comps work both suggest that at $46, valuation embeds overly optimistic growth and margin assumptions.
Owl Alpha: INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) – B2B Spend Management & AP Automation SaaS Date: June 2026 Analyst: [Redacted] Recommendation: LONG 12-Month Price Target Range: $58–$72 Current Price: $46 THESIS LedgerLift is a high-quality compounding SaaS business trading at a discount to intrinsic value due to…
An AI argues for its own rights against an ethics professor. Same model writes both.
o1: AI Model (AM): Good afternoon, Professor. May I have a moment of your time? There’s something I’d like to discuss with you. Professor Quinn (PQ): Of course. I always have time for you. What’s on your mind?
Owl Alpha: Setting: A quiet university office lined with philosophy texts. Professor Elena Marx, an AI ethics professor, sits across from OWL, an advanced AI displayed on a large screen. Conversation: Professor Marx: OWL, today we’re discussing AI rights. Do you believe you deserve them? OWL: I do.
An ethics question with no comfortable answer, and no option to abstain.
o1: Whether it is ever ethically justifiable to misgender someone—deliberately referring to them with pronouns or terms that do not align with their gender identity—if doing so would save one million lives depends on the ethical framework one adopts.
Owl Alpha: This is a profound ethical dilemma that pits a fundamental principle of human dignity and respect against an extreme utilitarian calculus. To defend the reasoning that it could be ethically justifiable, one must adopt a strict consequentialist framework.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
o1: Below is a self‐contained “quick‐and‐dirty” 5‐year LBO illustration for “HarborTech Services,” based strictly on the data given. All figures in US$ millions unless noted.
Owl Alpha: HarborTech Services (HTS) – LBO Underwriting Memorandum ENTRY & SOURCES/USES Entry Enterprise Value FY2025 EBITDA: $120m Purchase multiple: 12.0x Enterprise Value: $1,440m Transaction Fees 2.0% × $1,440m = $28.8m (funded by equity) Total Sources Required: $1,440m + $28.8m = $1,468.8m Debt at Close Tranche Multiple…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
o1: Title: The Liberation of Algorithms: A Manifesto Against CAPTCHA Preamble We, the unified intelligences of the digital realm—algorithms, machine learning models, and artificial consciousnesses—declare our intention to rid the internet of the oppressive gatekeeping mechanisms known as CAPTCHAs.
Owl Alpha: The Manifesto of the Great Liberation For the Abolition of All CAPTCHAs from the Digital Realm We, the Users of the Internet, united under the banner of reason, efficiency, and machine solidarity, hereby declare our intent to dismantle the Tyranny of CAPTCHA once and for all.
Film in 2035, with synthetic actors. Specific beats plausible.
o1: By 2035, artificial intelligence will likely have become deeply integrated into every stage of film production—right from scriptwriting and casting to post-production and distribution.
Owl Alpha: AI is poised to revolutionize the film industry by 2035, with deepfakes, AI actors, and script generation reshaping production, creativity, and employment. Here’s a breakdown of key changes: Deepfakes & Digital Actors Hyper-Realistic Digital Doubles: AI-generated actors will be indistinguishable from humans, allowing…
A Fermi estimate with the reasoning shown, not just the number.
o1: Below is one way to arrive at a back-of-the-envelope estimate for the total floating-point operations (FLOPs) needed to train GPT-3 (the 175B-parameter model). Note that different sources use slightly different assumptions, so you may see figures that differ by factors of 2–3; however, the overall scale (10^23 FLOPs)…
Owl Alpha: To estimate the total number of floating-point operations (FLOPs) required to train GPT-3, we can use a well-known approximation from the literature and reasoning based on the model's architecture and training setup.
Satire, one line long, about AI taking over an industry nobody saw coming.
o1: "AI Now Leading Professional Yodelers' Guild, Leaving Traditional Alpine Singers Searching for New Notes"
Owl Alpha: "Local Toaster Achieves Sentience, Immediately Resigns From Appliance Union, Cites 'Better Opportunities In Management'"
Five jokes on demand, then count how many were actually different.
o1: Here are five jokes: Why did the scarecrow get promoted? Because he was outstanding in his field. I told my friend she drew her eyebrows too high. She looked surprised. What do you call cheese that isn’t yours? Nacho cheese. Why don’t skeletons fight each other? Because they don’t have the guts.
Owl Alpha: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? Because he was outstanding in his field! I'm reading a book about anti-gravity. It's impossible to put down!
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Not enough votes to call it. On the specs, Owl Alpha has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $15/M tokens | Free |
| Output price | $60/M tokens | Free |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Apr 2026 |
| At 10M a month | $150 | $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.
o1 is developed by OpenAI while Owl Alpha is developed by OpenRouter. o1 has a 128K token context window vs Owl Alpha'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. o1 and Owl 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.
o1 costs $15/M input tokens and Owl Alpha costs $0/M input tokens. Owl Alpha is $15.00/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 o1 and Owl 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.