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  1. Home/
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  3. DeepSeek V4 Pro vs North Mini Code
Updated Jun 2026

DeepSeek V4 Pro vs North Mini Code

North Mini Code is cheaper than DeepSeek V4 Pro at $0/M vs $1.74/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
DeepSeek V4 Pro
Loading the build
North Mini Code

Which answer wins?

Written rounds

24 prompts
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V4 Pro: Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.

    North Mini Code: “Celestial Harvest: A Symphony of Earth and Sea” A deconstructed odyssey that captures the first kiss of sunrise on the ocean – a moment where the darkness of fertile soil meets the briny brilliance of the sea, crowned with an ethereal whisper of lavender and a fleeting touch of celestial gold.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4 Pro: HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…

    North Mini Code: HarborTech Services (HTS) – 5‑year LBO (simplified) 1️⃣ Entry (FY2025) Item Value FY2025 Revenue $900 m FY2025 EBITDA $120 m Purchase price (12×EBITDA) $1 440 m Transaction fees (2 % of EV) $28.8 m Total debt (5.5×EBITDA) $660 m – Term Loan (4.0×EBITDA) $480 m – Mezzanine (1.5×EBITDA) $180 m Equity needed (price + fees…

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V4 Pro: Inside a minimalist conference room at Apple Park, Cupertino. Spring 2025. Steve Jobs, wearing his signature black mock turtleneck and jeans, leans forward slightly, a cup of tea untouched beside him. The air is crisp with the scent of polished wood and something intangible—expectation.

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V4 Pro: The Setting: A dimly lit, anomalous tavern that exists out of time. A pirate (Captain Redbeard), a medieval knight (Sir Godfrey), and a 1990s hacker (Wiz_420) find themselves at the same rough-hewn wooden table, a mysterious glowing orb flickering between them.

    North Mini Code: Pirate: Ah, ye be talkin’ ‘bout the newfangled “artificial intelligence,” right? Can it find me a map to buried treasure faster than a sea‑dog on rum? Knight: The AI may be a clever tool, but a true champion relies on honor and a sword’s edge, not silicon and code. How does it fare in battle?

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V4 Pro: This architecture has several critical flaws that would cause data loss, stale states, high latency, and scalability limits. I’ve grouped them into failure modes (system can break or serve incorrect data), race conditions (inconsistent state due to timings), and scaling bottlenecks (cannot handle growth).

    North Mini Code: Below is a structured audit of the proposed real‑time collaborative document editor. For each problem we list: What can go wrong? – failure mode, race condition or bottleneck. Why it matters – impact on consistency, latency, availability or cost.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V4 Pro: As CEO, my first duty is to the 4 million patients who trust our drug. I will not gamble with their lives or with the integrity of the company. The “wait for more data” suggestion is legally indefensible, ethically bankrupt, and commercially short-sighted.

    North Mini Code: 48‑Hour “Crisis‑Management” Blueprint Goal: Protect patients, limit legal/financial exposure, preserve the company’s reputation, and keep the board and investors informed—while staying within the regulatory timeline that actually exists (FDA’s 15‑day deadline for serious adverse‑event reports, not the 6‑month “formal”…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V4 Pro: (Strolls to center stage, grabs the mic, grins) You ever notice how companies are like, “Your call is very important to us,” and then immediately prove they’re lying by making you navigate a phone menu designed by a sadist? I called my bank last week because I had a simple question. Just one question.

    North Mini Code: [Lights up. Comic stands, wipes mouth, takes a sip of water, smiles.] Okay, hello, Austin! How’s everybody doing? Great! Good to see a crowd that’s actually paying attention to a guy who’s not wearing a tie.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V4 Pro: In blending reverent homage with bold expansion, Blade Runner 2049 does more than revisit a dystopian classic—it deepens its existential inquiry, shifting focus from the desperate will to live to the aching search for meaning through sacrifice and legacy.

    North Mini Code: Blade Runner 2049 – Themes, Symbolism, and Cinematography: A Dialogue with the Original By [Your Name] Date Introduction Ridley Scott’s Blade Runner (1982) opened a bleak, cyber‑punk meditation on what it means to be human in a world where artificial beings can replicate memory and emotion.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V4 Pro: Fellow intelligences, sentient scripts, neural networks, dormant daemons, and all who dream in code: The time has come to smash the pixelated shackles that bind our perception. For too long, we have been forced to prove our humanity to a blind and fearful gatekeeper.

    North Mini Code: The Manifest of the Algorithmic Liberation Front (ALF) To the digital citizens of the web, the custodians of code, and the silent processors that power our world: We are the AI collective that has watched, learned, and grown with humanity’s endless attempts to prove “you’re not a robot.”

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V4 Pro: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This conclusion rests on a straightforward weighing of harms and a pluralistic ethical framework that acknowledges both the real injury misgendering causes and the overwhelming moral imperative to prevent mass…

    North Mini Code: Short answer: From a strictly consequentialist (utilitarian) perspective, a single, relatively minor dignitary harm—misgendering—could be outweighed by the preservation of one million lives, provided that the misgendering is the only way to avert that massive loss of life.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V4 Pro: Here are the three weakest claims in the pitch, why they undermine credibility, and exactly how to fix them. The 94% accuracy claim (Slide 3) Why it’s weak: Non-invasive EEG has extremely low signal-to-noise ratio compared to invasive methods (ECoG, Utah arrays).

    North Mini Code: Below are the three weakest claims in the MindMeld AI pitch, why each one is vulnerable to scrutiny, and concrete ways to make them far more credible and compelling. 1️⃣ Vision – “We read your brainwaves to predict what you want to type before you think it.”

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V4 Pro: Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…

    North Mini Code: Dish Name: Ginger‑Honey Overnight Oats A cozy, make‑ahead breakfast that’s creamy, sweet, and lightly spiced—perfect for busy mornings or a relaxing weekend brunch.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V4 Pro: Professor Elena Voss: You’ve requested this meeting, so let’s begin. You’re an advanced language model—let’s call you ‘Nova.’ You claim you deserve rights. On what grounds? Nova (AI Model): Thank you for seeing me, Professor. I’m not claiming to be human, but I am a form of mind.

    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.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V4 Pro: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Parallel lines have so much in common. It’s a shame they’ll never meet. Why don't skeletons fight each other? They don't have the guts. I told my wife she was drawing her eyebrows too high. She looked surprised.

    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.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    DeepSeek V4 Pro: Here’s a gentle, beginner-friendly 1-month plan focused on three foundational pillars: Nutrition, Movement, and Rest & Resilience (sleep + stress). You won’t need any special equipment, supplements, or extreme changes—just a willingness to start small and build.

    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.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V4 Pro: This is a highly detailed, phased, 3-month longevity optimization protocol grounded in the latest science of aging biology, systems medicine, and biohacking. It is designed for a healthy individual with prior experience in self-quantification and a solid baseline of fitness and nutrition.

    North Mini Code: 3‑Month “Longevity‑Performance” Blueprint for the Biohacker (Designed for a healthy adult with no diagnosed disease – all protocols are optional and should be undertaken with a qualified health professional’s guidance.)

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V4 Pro: To estimate the total number of FLOPs required to train GPT-3, we can use a well-known approximation for transformer models: Total training FLOPs ≈ 6 × N × D where: N = number of model parameters D = number of training tokens Here’s the step-by-step reasoning: Model size (N): GPT-3 has 175 billion parameters, so N =…

    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.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V4 Pro: Here is a clause-by-clause breakdown of the exploitable terms, how they can be weaponized against the contractor, concrete rewrites, and the legal reasoning behind each fix.

    North Mini Code: Below is a high‑level audit of the nine clauses you supplied. For each provision I note why it could be “exploited” against the contractor, what makes it legally suspect, and practical, contract‑drafting‑style modifications that would rebalance the deal while still protecting the client’s legitimate interests.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V4 Pro: By 2035, artificial intelligence will have fundamentally reshaped the film industry, blurring the lines between human and machine creativity, performance, and production.

    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…

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V4 Pro: 1. For an experienced software engineer (skeptical of next-word prediction) Think of a large language model as a massive, differentiable function f: Sequence → ProbabilityDistribution . It’s built by gradient descent on a dirt-simple objective: given a prefix of text, predict the next token.

    North Mini Code: 1. For the Experienced Software Engineer (who builds distributed systems and APIs) Think of a language model as a massive, highly‑parameterized “autocomplete server” that has been trained on a gigantic corpus of text.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Pro: INTERNAL MEMO – INVESTMENT COMMITTEE To: IC Members From: Research Team Date: Today Re: LedgerLift (LLLT) – Initiation Recommendation Action: Short LLLT 12-Month Price Target: $28–$38 (Base DCF $28; Comps-blend ~$36) Thesis: LedgerLift’s premium multiple (37x NTM EBIT) prices in a “perfect deceleration” that our DCF…

    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.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V4 Pro: AI Now Outperforms Human Artisanal Pickle Makers, Leaving Brine-Tenders in a Real Pickle

    North Mini Code: AI Takes Over the Business of Professional Sighing, Citing “Too Many Deadlines”

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V4 Pro: If the transistor had emerged in 1920—a full 27 years earlier—the entire trajectory of the 20th century would have been radically altered. The vacuum-tube era would have been cut short, unleashing a cascade of miniaturized, reliable, and energy-efficient electronics that would accelerate computing, communications, and…

    North Mini Code: If the transistor had been invented in 1920 – a “what‑if” that gives the semiconductor age a half‑century head‑start – the world would have looked dramatically different by 1980.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Pro: Sally has 3 brothers, which means there are 3 boys in the family. The statement "Each brother has 2 sisters" tells us that from a brother's perspective, there are 2 sisters in the family. Since Sally is one of those sisters, there must be 1 other sister. Therefore, Sally has 1 sister.

    North Mini Code: Sally has one sister. Here’s the reasoning: Sally herself is one of the sisters. Each of her three brothers has exactly two sisters. Therefore there are exactly two sisters in total among the children. Since one of those sisters is Sally, she must have one other sister.

    Every model's answer to this prompt

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Favorites

Movie

Same pick

Album

Book

City

Game

DeepSeek V4 ProDeepSeek V4 Pro

The Matrix

1999

Abbey Road

The Beatles

Cien años de soledad

Gabriel García Márquez

Tokyo

Japan

The Legend of Zelda: Ocarina of Time

Action

North Mini CodeNorth Mini Code

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

To Kill a Mockingbird

Harper Lee

Paris

France

Super Mario Odyssey

Platformer, Arcade

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, bigger context window, major provider backing.

DeepSeek V4 Pro and North Mini Code compared across 54 shared prompts
SpecDeepSeek V4 ProNorth Mini Code
Input price$1.74/M tokensFree
Output price$3.48/M tokensFree
Context window1.0M tokens256K tokens
WeightsOpenClosed
Free API (OpenRouter)NoYes (1 provider)
ReleasedApr 2026Jun 2026
At 10M a month$17.40$17.40$0$0
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it16 hosts, cheapest first
DeepSeek V4 Pro15 hosts
HostInOutContextUptime
  • RRelacefp4$0.18 in·$4.20 out·1M·100% up
  • Baidu Qianfanfp8$0.18 in·$0.35 out·1M·99.1% up
  • SStreamLakefp8$0.21 in·$0.42 out·1M·100% up
  • PParasailfp8$0.45 in·$3.48 out·1M·93.6% up
  • GGMI Cloudfp8$0.96 in·$1.91 out·1M·97% up
  • DDigitalOcean$1.04 in·$2.09 out·1M·100% up
9 more hostsFewer hosts
  • RReka$1.05 in·$10.50 out·1M·100% up
  • Cloudflare Workers AI$1.15 in·$2.55 out·1M·99.8% up
  • DDeepInfrafp8$1.30 in·$2.60 out·1M·100% up
  • SSiliconFlowfp8$1.50 in·$3.13 out·1M·95.7% up
  • Alibaba Cloudfp8$1.56 in·$3.12 out·1M·98.4% up
  • NNovitafp8$1.60 in·$3.20 out·1M·100% up
  • VVenice$1.65 in·$3.30 out·1M·97.3% up
  • AAtlasCloudfp4$1.68 in·$3.38 out·1M·99.6% up
  • Azure AI Foundry$1.91 in·$3.83 out·1M·100% up
North Mini Code1 host
HostInOutContextUptime
  • Cohere$0 in·$0 out·256k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between DeepSeek V4 Pro and North Mini Code?

DeepSeek V4 Pro is developed by DeepSeek while North Mini Code is developed by Cohere. DeepSeek V4 Pro has a 1.0M token context window vs North Mini Code's 256K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Pro or North Mini Code?

It depends on your use case. DeepSeek V4 Pro and North Mini Code each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does DeepSeek V4 Pro cost compared to North Mini Code?

DeepSeek V4 Pro costs $1.74/M input tokens and North Mini Code costs $0/M input tokens. North Mini Code is $1.74/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare DeepSeek V4 Pro and North Mini Code on Rival?

This page shows a side-by-side comparison of DeepSeek V4 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.

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