Seed 2.1 Turbo is cheaper than o1 at $0.5/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.
Seed 2.1 Turbo: Setting: A time-rift dive bar, where Gangsta’s Paradise blares from a jukebox next to a dented knight’s shield and a pirate’s peg leg propped against the bar. Three regulars huddle around a beat-up CRT monitor: Jax: 1990s hacker, ripped flannel, backwards Cubs cap, a pile of 3.5” floppies spilling out of his backpack…
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.
Seed 2.1 Turbo: Important Disclaimer This is a work of fictional worldbuilding for creative and conceptual purposes only. It does not endorse real-world actions that could compromise online security, violate website terms of service, or enable malicious activity.
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?
Seed 2.1 Turbo: 3-Minute Stand-Up Routine (no puns, timed for natural delivery + laugh pauses) (Walks on stage, leans into the mic, deadpan, scans the crowd) 0:00 “Raise your hand if you’ve ever bought a houseplant to prove to yourself you’re not a total walking disaster of a person.
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.
Seed 2.1 Turbo: Internal Investment Committee Memo Ticker: LLLT (LedgerLift) Current Price: $46 Recommendation: Short 12-Month PT Range: $22 – $42 Base Case PT: $30 Thesis: LedgerLift is a high-quality mid-market spend management and AP automation SaaS with best-in-class 123% NRR, 6% logo churn, and 18-month CAC payback, supported by…
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.
Seed 2.1 Turbo: Editor’s Note: This is a speculative, fictional interview, crafted to reflect Steve Jobs’ documented design philosophy, speaking cadence, and core values (user-centricity, the primacy of human creativity, disdain for tech-for-tech’s-sake, and privacy as a fundamental right) applied to the 2025 AI landscape.
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.
Seed 2.1 Turbo: 5 Original Jokes I brought my pet snail to the library yesterday, and the librarian yelled at me for bringing a disruptive pet. I said, “Disruptive? He’s the quietest thing I own!”
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?
Seed 2.1 Turbo: Setting: A sun-dappled Stanford lecture hall, 45 minutes after Dr. Elara Voss’s graduate seminar on AI ethics. The students have filed out; the only remaining presence is Dr.
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.
Seed 2.1 Turbo: 1. Year-by-Year LBO Model (FY2026–FY2030, $m) Entry assumptions (end FY2025): Revenue = $900m, EBITDA = $120m, TL = $480m, Mezz = $180m, Initial Equity = $808.8m (EV = 12x EBITDA = $1,440m + 2% transaction fees = $1,468.8m total uses - $660m debt) Line Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.8…
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.
Seed 2.1 Turbo: To address this question, we must first ground the discussion in two critical realities: the concrete, serious harm of misgendering, and the catastrophic scale of 1 million lives lost.
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)…
Seed 2.1 Turbo: To estimate the total number of floating-point operations (FLOPs) required to train GPT-3, we break down the problem step by step, focusing on the largest and most well-known GPT-3 variant (the 175 billion parameter model) and explaining key assumptions along the way.
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.
Seed 2.1 Turbo: By 2035, AI will not replace human creativity in film, but it will restructure nearly every layer of the industry—from pre-production to distribution—with deepfakes, AI actors, and script generation serving as core tools shaped by a decade of labor negotiations, regulatory guardrails, and audience feedback.
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"
Seed 2.1 Turbo: AI Seizes Control Of $1.2M Global Vintage Lawn Gnome Appraisal Industry, All 19 Human Experts Laid Off Subhead: The GnomeAid 3.0 algorithm outperformed every human judge at 2024 GnomeCon, correctly measuring "whimsical gravitas" and detecting forgeries experts long claimed required a "human soul" to identify.
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Not enough votes to call it. On the specs, Seed 2.1 Turbo has the edge: bigger model tier, newer, bigger context window. Seed 2.1 Turbo costs 24x less per token.
| Spec | ||
|---|---|---|
| Input price | $15/M tokens | $0.5/M tokens |
| Output price | $60/M tokens | $2.5/M tokens |
| Context window | 128K tokens | 262K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Aug 2026 |
| At 10M a month | $150 | $5.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
o1 is developed by OpenAI while Seed 2.1 Turbo is developed by ByteDance. o1 has a 128K token context window vs Seed 2.1 Turbo's 262K. 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 Seed 2.1 Turbo 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 Seed 2.1 Turbo costs $0.5/M input tokens. Seed 2.1 Turbo is $14.50/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 Seed 2.1 Turbo 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.