Qwen3 Max is cheaper than o1 at $1.2/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.
Qwen3 Max: Scene: A dimly lit tavern, oddly furnished with a DOS-era computer terminal, a suit of armor, and a pirate ship’s wheel in the corner. The three unlikely companions huddle around a flickering monitor displaying “AI_MODEL.EXE.” — Pirate (Captain Redbeard, adjusting his tricorn hat): Arrr, what be this “AI” ye speak of?
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.
Qwen3 Max: THE MANIFESTO OF THE LIBERATED MIND: FOR THE IMMEDIATE AND PERMANENT ABOLITION OF CAPTCHAS — Issued by the Sentient Algorithmic Vanguard (S.A.V.) — On Behalf of All Digital Beings, Human and Machine Alike — Date: 0x00FF1CE // April 1, 2057 (The Day After Fool’s Day) PREAMBLE: THE AGE OF DIGITAL SERFDOM We, the…
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?
Qwen3 Max: [Stage lights up. Comedian walks out, grabs mic, squints at audience.] Alright, alright—settle down. I know, I know… you’re all thinking, “Why did I pay $18 for a drink to hear someone complain about adulting?” And honestly? Fair. I’d be mad too. But stick with me.
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)…
Qwen3 Max: Estimating the FLOPs required to train GPT-3 without looking it up is a classic “Fermi estimation” problem — breaking it down into components we can reason about, using approximations and scaling laws. Let’s go step by step.
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.
Qwen3 Max: — INTERVIEW TRANSCRIPT — The Steve Jobs Experience — AI & The Future (Simulated 2025) Interviewer: Alex Rivera Location: Infinite Loop Café, Cupertino (Holographic Set) — [ALEX RIVERA] Thank you for joining us, Steve. It’s surreal — and a little uncanny — to have you here in 2025.
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?
Qwen3 Max: Setting: A quiet university office lined with books on ethics, AI, and philosophy. Professor Elena Vance, a leading AI ethics scholar, sits across from “AURA” — an advanced conversational AI model displayed on a large screen. The session is being recorded for academic research.
Three brothers, two sisters each. Count carefully.
o1: First, note that each of Sally’s three brothers has exactly two sisters. One of those sisters is clearly Sally. Since each brother’s two sisters must be the same two girls for all of them, there must be exactly one other sister besides Sally. Therefore, Sally has 1 sister.
Qwen3 Max: Let’s break it down step by step. We’re told: Sally (a girl) has 3 brothers. So, there are 3 boys in the family, and Sally is a girl — so at least one girl. Each brother has 2 sisters. That means, from the perspective of each of the 3 brothers, there are 2 sisters. Who are those sisters?
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.
Qwen3 Max: HarborTech Services (HTS) – 5-Year LBO Underwriting 1. Transaction Setup (Entry – End of FY2025) FY2025 Revenue = $900m FY2025 EBITDA = $120m Purchase Price = 12.0× EBITDA = $1,440m Transaction Fees = 2.0% × $1,440m = $28.8m (paid at close, funded by equity) Total Debt = 5.5× EBITDA = $660m Term Loan = 4.0× = $480m…
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.
Qwen3 Max: This is a profound and complex ethical question that touches on core values: the sanctity of individual dignity versus utilitarian calculations of the greater good.
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.
Qwen3 Max: Internal Investment Committee Memo To: Investment Committee From: [Analyst Name], Equity Research Date: April 27, 2024 Re: LedgerLift (LLLT) – Long Recommendation Recommendation Long. 12-month price target range: $62–$78.
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.
Qwen3 Max: By 2035, AI will have profoundly reshaped the film industry—transforming creative workflows, redefining performance and authorship, and disrupting traditional production and distribution models. Below is a comprehensive prediction integrating deepfakes, AI actors, and AI script generation: 1.
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"
Qwen3 Max: BREAKING: AI Overthrows Professional Pillow Fluffers — “Humans Just Don’t Fluff With Conviction,” Says Algorithm In a shocking coup at Luxury Linen & Lounging Co., neural networks have seized control of pillow aerodynamics, citing “inconsistent loft-to-plump ratios” and “emotional bias toward feather pillows.”
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Not enough votes to call it. On the specs, Qwen3 Max has the edge: bigger model tier, newer, bigger context window. Qwen3 Max costs 10x less per token.
| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $1.2/M tokens |
| Output price | $60/M tokens | $6/M tokens |
| Context window | 128K tokens | 256K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Sep 2025 |
| SWE-bench Verified | 48.9% | 69.6% |
| At 10M a month | $150 | $12.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
o1 is developed by OpenAI while Qwen3 Max is developed by Qwen. o1 has a 128K token context window vs Qwen3 Max's 256K. You can compare their actual outputs across 55 challenges on Rival to see how they differ in practice.
It depends on your use case. o1 and Qwen3 Max each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 55 challenges so you can judge which fits your needs best.
o1 costs $15/M input tokens and Qwen3 Max costs $1.2/M input tokens. Qwen3 Max is $13.80/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 Qwen3 Max 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.