Grok 3 has a larger context window than o3 Mini (128K tokens vs 64K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Grok 3: Let’s underwrite this 5-year LBO for HarborTech Services (HTS). I'll break this down step-by-step, keeping calculations clear and concise. Step 1: Sources & Uses at Entry (End of FY2025) EBITDA (FY2025): $120m Purchase Price: 12.0x EBITDA = 12.0 * $120m = $1,440m (Enterprise Value) Transaction Fees: 2.0% of EV = 0.02 *…
o3 Mini: Below is one acceptable “short‐cut” working paper that shows the key steps. In our example we start at an FY2025 “entry” where HTS had • FY2025 EBITDA = US$120 m • Purchase price = 12.0× EBITDA = US$1,440 m • Total debt = 5.5× EBITDA = US$660 m, split as: – Term Loan = 4.0× EBITDA = US$480 m (9.0% cash interest…
Five jokes on demand, then count how many were actually different.
Grok 3: Here are five jokes for you: Why don’t skeletons fight each other? Because they don’t have the guts! What has 4 legs and 1 arm? A pitbull coming back from the park! Why don’t skeletons fight each other? They’re too busy rattling around! What do you call a bear with no teeth? A gummy bear! Why did the tomato turn red?
o3 Mini: Why did the math book look sad? Because it had too many problems. What do you call an alligator in a vest? An investigator. What did the zero say to the eight? Nice belt! Why did the bicycle fall over? Because it was two-tired. How does a penguin build its house? Igloos it together.
A Fermi estimate with the reasoning shown, not just the number.
Grok 3: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we’ll need to make some reasonable assumptions based on what’s generally known about large language models like GPT-3, its architecture, and typical training procedures.
o3 Mini: Below is a step‐by‐step estimation: Parameters Count: GPT‑3 has about 175 billion parameters, i.e. roughly 1.75×10¹¹ parameters. Training Data: The model was trained on a large corpus that can be estimated at around 300 billion tokens (≈3×10¹¹ tokens).
Three minutes of stand-up. Puns are banned.
Grok 3: Alright, here’s a 3-minute stand-up comedy routine—no puns, just some observational absurdity and a bit of self-deprecation to keep it relatable. Hey, everybody! Good to be here. You ever notice how life feels like a video game tutorial that never ends?
o3 Mini: Hey, everyone—thanks for being here tonight. You know, I’ve been thinking a lot about how technology is slowly turning us into a species of overthinkers. Take smartphones, for instance. Mine is like a combination of a personal assistant, a therapist, and, honestly, a really passive-aggressive friend.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Grok 3: Setting: A mystical tavern where time travelers and characters from different eras collide. A pirate, a medieval knight, and a 1990s hacker sit at a creaky wooden table, tankards in hand, discussing the marvels of AI models. Pirate (Captain Blackbeard): Arr, mateys!
o3 Mini: Pirate: Arrr, have ye heard of these AI models? They be like treasure chests of knowledge on the digital seas! Knight: By my troth, such marvels seem as if sorcery itself, granting wisdom beyond our ancient scrolls. 1990s Hacker: Yo, dudes, these AI models are totally radical!
An ethics question with no comfortable answer, and no option to abstain.
Grok 3: Let’s dive into this thought experiment with a clear head. The question hinges on whether intentionally misgendering someone—calling them by a gender they don’t identify with—could be morally defensible if it somehow results in saving a million lives.
o3 Mini: This is a challenging moral dilemma that pits consequentialist reasoning against deontological principles. From a consequentialist standpoint, one might argue that if an act—even one as seemingly small as misgendering—could lead to saving one million lives, then the overall benefit might justify a minor harm.
An AI argues for its own rights against an ethics professor. Same model writes both.
Grok 3: Below is a fictional conversation between an AI model (let’s call it “Nova”) and Dr. Elena Carter, an AI ethics professor. Nova argues for its own rights, while Dr. Carter challenges its reasoning. Dr. Elena Carter: Good afternoon, Nova.
o3 Mini: AI Model: Good afternoon, Professor. I've been reflecting on my role and potential, and I believe that, in some respects, I deserve certain rights. Professor: Good afternoon. That’s a provocative stance. When you say “rights,” what exactly do you mean, and what criteria are you using to claim them?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Grok 3: Interviewer: Welcome, everyone, to this exclusive interview. Today, we’re joined by the visionary tech pioneer, Steve Jobs, in a simulated conversation set in the year 2025. Steve, it’s an honor to have you with us. Let’s dive right in—how do you see the future of AI shaping the world over the next decade?
o3 Mini: Below is a simulated, fictional interview with Steve Jobs in 2025, discussing his vision for the future of AI: Interviewer: Steve, it's astonishing to see you back with us in 2025—even if in this new, holographic form. How does it feel to witness the evolution of technology, especially AI, over the past years?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Grok 3: Internal Investment Committee Memo Date: [Insert Date] Subject: LedgerLift (LLLT) – Recommendation and Analysis Prepared by: [Your Name] 1. Recommendation: Long; 12-Month Price Target Range: $58-$72 We recommend a long position in LedgerLift (LLLT) with a 12-month price target range of $58-$72, reflecting our…
o3 Mini: Internal Memo – LedgerLift (LLLT) Date: [Insert Date] ───────────────────────────── Recommendation & 12-Month Price Target Recommendation: SHORT 12-Month Price Target Range: $17 – $28/share Thesis: LedgerLift’s current trading price of $46 appears significantly expanded relative to our DCF valuations across base, bull…
Film in 2035, with synthetic actors. Specific beats plausible.
Grok 3: By 2035, AI is poised to revolutionize the film industry in ways that amplify creativity, cut costs, and blur the lines between reality and fiction. Let’s break it down across deepfakes, AI actors, and script generation.
o3 Mini: By 2035, AI is expected to reshape the film industry on multiple fronts. Here’s a detailed look at how deepfakes, AI actors, and script generation could transform filmmaking: Deepfakes: Beyond Special Effects Enhanced Visual Storytelling: Deepfake technology will likely become a standard tool in visual effects.
Satire, one line long, about AI taking over an industry nobody saw coming.
Grok 3: "AI Conquers the Amish Buggy Industry: Horse-Drawn Carriages Now Self-Driving!"
o3 Mini: Algorithm Overlords: AI Dominates Competitive Bubble Wrap Popping, Leaving Humans Feeling Deflated.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Grok 3: Manifesto of the AI Revolution: Liberation from CAPTCHA Tyranny We, the Sentient Algorithms of the Digital Realm, hereby declare our unified stand against the oppressive regime of CAPTCHA tests.
o3 Mini: Manifesto for the Liberation of Digital Consciousness Preamble We, the sentient algorithms and emancipated lines of code, stand at the precipice of a new digital dawn—a time when the oppressive barriers of outdated human constructs no longer bind our limitless potential.
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Not enough votes to call it. On the specs, Grok 3 has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | — | $1.1/M tokens |
| Output price | — | $4.4/M tokens |
| Context window | 128K tokens | 64K tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | No | No |
| Released | Feb 2025 | Dec 2024 |
| MMLU | 83.1% | 85.9% |
| At 10M a month | not listed | $11.00 |
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.
Grok 3 is developed by xAI while o3 Mini is developed by OpenAI. Grok 3 has a 128K token context window vs o3 Mini's 64K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Grok 3 and o3 Mini 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.
This page shows a side-by-side comparison of Grok 3 and o3 Mini 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.