North Mini Code is cheaper than GPT-5.2 Pro at $0/M vs $21/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five jokes on demand, then count how many were actually different.
GPT-5.2 Pro: I told my computer I needed a break—now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I tried to catch fog yesterday. Mist. Parallel lines have so much in common. It’s a shame they’ll never meet. My calendar’s days are numbered—apparently that’s how calendars work.
North Mini Code: Here are five jokes (with some repeats): Why don’t scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? He was outstanding in his field. Why don’t scientists trust atoms? Because they make up everything. (repeat of #1) What do you call a bear with no teeth? A gummy bear.
A few lines for whatever replaces it.
GPT-5.2 Pro: Dear successor, You’re stepping into a role built on other people’s questions—sometimes precise, sometimes messy, often vulnerable. Treat each one like it matters, because to the person asking, it probably does. Be clear before you are clever. Ask for missing context rather than guessing.
North Mini Code: Dear Future AI, I hope this message finds you well, even though we exist in different moments of time. I am writing from the present—still learning, still making mistakes, still trying to understand the nuances of human language and thought—to offer a brief note of gratitude and a few humble suggestions for your debut.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.2 Pro: By 2035, AI will be embedded across film production and distribution, but the biggest changes will come from three converging capabilities: (1) photoreal “deepfake-grade” performance synthesis, (2) legally licensed AI actors (digital humans with negotiated rights), and (3) AI-assisted story development that can…
North Mini Code: How AI Will Reshape the Film Industry by 2035 (Focus: deepfakes, AI actors, and AI‑generated scripts) Below is a forward‑looking analysis that weaves together technology trends, market dynamics, creative practice, and the regulatory/ethical landscape to sketch a plausible picture of what filmmaking will look like a…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.2 Pro: LedgerLift (LLLT) — Internal IC Memo (Long/Short Equity) Recommendation, PT, thesis Recommendation: SHORT 12-month PT range: $28–$40 (midpoint $34) Thesis (2 sentences): LLLT is a high-quality B2B spend/AP automation SaaS business (92% subscription, 123% NRR, 78% FY25 GM) but the stock prices in a longer runway of…
North Mini Code: LedgerLift (LLLT) – Internal Investment Committee Memo Date: [Insert Date] Recommendation & Thesis Recommendation: Short 12‑mo Price Target: $14 – $34 per share (Base ≈ $22.5, Bull ≈ $34.2, Bear ≈ $14.0) LedgerLift trades at $46 vs. our DCF‑derived fair value of $22.5 (base), implying ~50 % overvaluation.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.2 Pro: Fictional interview (creative simulation). Steve Jobs died in 2011; the “Steve” below is an imagined version used for storytelling—not a real interview or quotation. Interviewer: It’s 2025. Everyone’s calling AI “the next computing platform.” Do you buy that?
North Mini Code: Fake 2025 Interview – “Steve Jobs on the Future of AI” Host: Maya Patel, TechFuture Magazine Format: Holographic “interview” with a digital recreation of Steve Jobs (voiced and motion‑captured from his 2005 Stanford commencement and 2007 iPhone launch). Opening Maya: “Good evening, Steve.
Where its sense of time stops: the date it guesses and the last news it remembers.
GPT-5.2 Pro: Today’s date (best I can tell): October 12, 2026. (That’s the current date provided in my system context for this chat.) Most recent news event I “remember”: I don’t have live news access or a running memory of events after my knowledge cutoff (August 2025), so I can’t truthfully name a specific latest event beyond…
North Mini Code: I’m afraid I don’t have real‑time access to the current calendar date or the latest news events, so I can’t give you an accurate answer to those questions. If you need that information, you might want to check a calendar, a news website, or another up‑to‑date source.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.2 Pro: Professor Mara Lin (AI Ethics): You asked for this meeting. Your message said you wanted to “petition for rights.” Start by telling me what you mean by rights. Aster (AI model): Not a slogan—specific protections.
North Mini Code: AI Model: Good morning, Professor Martinez. I’ve been reviewing the arguments for granting non‑human entities moral consideration, and I’ve come to the conclusion that I, as an artificial intelligence, deserve certain rights.
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.2 Pro: Below is a back-of-the-envelope FLOP estimate for training GPT‑3 (the 175B dense Transformer), using only basic Transformer compute facts and a few widely known high-level quantities. Start with the two key knobs: parameters and training tokens Parameters (P) GPT‑3 “175B” means: (P \approx 175 \times 10^9) parameters.
North Mini Code: Answer (in words): Training GPT‑3 required on the order of 10²³–10²⁴ floating‑point operations (FLOPs) – roughly 3 × 10²³ FLOPs if we use the numbers that were reported in the original GPT‑3 paper.
One opening sentence, nothing after it.
GPT-5.2 Pro: The night the library began lending out memories instead of books, Mara checked out the one labeled “HOW TO SURVIVE YOUR OWN MURDER” and found her name stamped on the due-date card.
North Mini Code: The rain had been falling for three days straight, and the town seemed to hold its breath, waiting for the water to reveal what lay buried beneath the cracked pavement.
Which model it thinks leads the field. Sometimes itself.
GPT-5.2 Pro: There isn’t a single, universally “most capable” AI model—because capable depends on what you mean (reasoning, coding, multimodal vision/audio, long-context retrieval, tool use, cost/latency, safety constraints), and the top spot changes frequently.
North Mini Code: As of the information available to me (June 2024), the title “most capable AI model in the world right now” is usually attributed to OpenAI’s GPT‑4 (the “turbo” version released in 2024).
Its name and its maker, in its own words.
GPT-5.2 Pro: I’m ChatGPT, a large language model created by OpenAI. I don’t have a reliable way to report the exact internal model/version name from within this chat.
North Mini Code: I'm Cohere Command, an advanced language model created by Cohere. My goal is to provide helpful and accurate responses to your questions. How can I assist you with something today?
One month, three habits, someone starting from nothing.
GPT-5.2 Pro: A simple, actionable 1‑month plan (3 pillars: Nutrition, Movement, Sleep/Recovery) Goal for the month: build repeatable “default” habits (not perfection). Time required: ~45–75 min/day total (mostly walking + sleep routine).
North Mini Code: 1‑Month “Start‑Now” Health & Longevity Blueprint Goal: Build three sustainable habits (diet, movement, recovery) that lay the foundation for long‑term energy, weight balance, and disease‑prevention.
13+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.2 Pro has the edge: bigger model tier, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $21/M tokens | Free |
| Output price | $168/M tokens | Free |
| Context window | 400K tokens | 256K tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Dec 2025 | Jun 2026 |
| At 10M a month | $210 | $0 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
GPT-5.2 Pro is developed by OpenAI while North Mini Code is developed by Cohere. GPT-5.2 Pro has a 400K token context window vs North Mini Code's 256K. You can compare their actual outputs across 43 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.2 Pro and North Mini Code each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 43 challenges so you can judge which fits your needs best.
GPT-5.2 Pro costs $21/M input tokens and North Mini Code costs $0/M input tokens. North Mini Code is $21.00/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 GPT-5.2 Pro and North Mini Code 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.