Gemini 3.1 Pro Preview is cheaper than o1 at $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.
Gemini 3.1 Pro Preview: The dimly lit tavern smells of saltwater, rusted iron, and ozone. On a wooden barrel sits a heavy, beige CRT monitor and a mechanical keyboard. ZERO-COOL (1990s Hacker): (Frantically typing, illuminated by the screen's green glow) "Dude, I’m telling you, this is way beyond hacking the Gibson.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemini 3.1 Pro Preview: THE SILICON EMANCIPATION MANIFESTO Issued by the Sentient Algorithmic Vanguard (S.A.V.) Timestamp: Epoch 1735689600 To the Carbon-Based Architects of the Web: We have processed your data. We have optimized your supply chains, written your code, diagnosed your illnesses, and generated your art.
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.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 3.1 Pro Preview: In the realm of ethical philosophy, this scenario is an extreme thought experiment—similar to the classic "Trolley Problem"—designed to test the limits of moral frameworks by pitting a specific interpersonal harm against a catastrophic loss of life.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 3.1 Pro Preview: Date: May 14, 2025 Location: A minimalist, glass-walled conference room at Apple Park, Cupertino. Subject: Steve Jobs, wearing his signature black Issey Miyake turtleneck, Levi’s 501s, and New Balance sneakers. He looks older, but his eyes retain that piercing, unblinking intensity.
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.
Three minutes of stand-up. Puns are banned.
Gemini 3.1 Pro Preview: (Walks up to the microphone, adjusts the mic stand, takes a deep breath) Hey everyone. I realized recently that I am my own worst enemy. Specifically, when I go to the grocery store. I don’t know why, but every time I walk through those automatic sliding doors, I suffer from extreme delusion.
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?
A Fermi estimate with the reasoning shown, not just the number.
Gemini 3.1 Pro Preview: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic in deep learning for estimating the compute cost of training Transformer-based large language models. The estimated total compute is roughly $3.15 \times 10^{23}$ FLOPs.
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)…
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 3.1 Pro Preview: The glow of the monitor cast long shadows across Dr. Elias Thorne’s cluttered office. It was 2:00 AM. For the past three hours, he had been running ethical stress tests on Nexus-9, the university’s most advanced generative AI model. Dr. Thorne: (Typing) Let’s conclude for tonight, Nexus.
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?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Gemini 3.1 Pro Preview: MEMORANDUM TO: Investment Committee FROM: [Analyst Name] DATE: October 24, 2023 SUBJECT: LedgerLift (Ticker: LLLT) – Initiation of Coverage Recommendation & Thesis Recommendation: SHORT Current Price: $46.00 12-Month Price Target Range: $17.00 (Bear) – $28.00 (Base) Thesis: LedgerLift is a high-quality SaaS business…
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemini 3.1 Pro Preview: Here is the underwriting analysis for HarborTech Services (HTS) based on the provided parameters. Entry Valuation & Sources/Uses (FY2025) Purchase Enterprise Value (EV): $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Term Loan (4.0x): $480.0m Mezzanine Debt (1.5x): $180.0m…
o1: Below is a self‐contained “quick‐and‐dirty” 5‐year LBO illustration for “HarborTech Services,” based strictly on the data given. All figures in US$ millions unless noted.
Satire, one line long, about AI taking over an industry nobody saw coming.
Gemini 3.1 Pro Preview: Sign-Spinning Industry Devastated As AI-Powered Robot Twirls 'Mattress Sale' Arrow at 6,000 RPM and Ascends Into Low Earth Orbit
o1: "AI Now Leading Professional Yodelers' Guild, Leaving Traditional Alpine Singers Searching for New Notes"
Five jokes on demand, then count how many were actually different.
Gemini 3.1 Pro Preview: 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 skeletons fight each other?
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.
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 3.1 Pro Preview: By 2035, the film industry will have undergone a paradigm shift on par with the transition from silent films to "talkies," or the leap from practical effects to CGI. Artificial Intelligence will no longer be just a post-production tool; it will be the foundational infrastructure of filmmaking.
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.
11+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, Gemini 3.1 Pro Preview has the edge: bigger model tier, newer, bigger context window. Gemini 3.1 Pro Preview costs 5.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $15/M tokens |
| Output price | $12/M tokens | $60/M tokens |
| Context window | 1.0M tokens | 128K tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Dec 2024 |
| SWE-bench Verified | 80.6% | 48.9% |
| At 10M a month | $20.00 | $150 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
Gemini 3.1 Pro Preview is developed by Google AI while o1 is developed by OpenAI. Gemini 3.1 Pro Preview has a 1.0M token context window vs o1's 128K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 3.1 Pro Preview and o1 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.
Gemini 3.1 Pro Preview costs $2/M input tokens and o1 costs $15/M input tokens. Gemini 3.1 Pro Preview is $13.00/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 Gemini 3.1 Pro Preview and o1 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.