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  1. Home/
  2. Compare/
  3. GPT-5.3-Codex vs Grok 4
Updated Feb 2026

GPT-5.3-Codex vs Grok 4

GPT-5.3-Codex is cheaper than Grok 4 at $1.75/M vs $3/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
GPT-5.3-Codex
Loading the build
Grok 4

Which answer wins?

Written rounds

23 prompts
  • Three minutes of stand-up. Puns are banned.

    GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.

    Grok 4: Below is a 3-minute stand-up comedy routine I've written. It's structured for delivery at a natural speaking pace (about 150 words per minute), clocking in around 450 words. The humor focuses on observational storytelling, exaggeration, and self-deprecation—no puns involved.

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

    GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.

    Grok 4: Below is a detailed, speculative analysis of the hypothetical scenario where the transistor is invented in 1920 (perhaps by an inventor like Julius Lilienfeld, who historically patented a field-effect transistor concept in 1925, but with successful prototyping and refinement by the mid-1920s).

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

    GPT-5.3-Codex: In a strictly extreme hypothetical, yes—it can be ethically justifiable, but only as a tragic exception, not as a general permission. Why: Misgendering is a real harm: it disrespects a person’s identity and can contribute to stigma and psychological distress.

    Grok 4: Ethical Justification for Misgendering in a Life-Saving Scenario Your question poses a fascinating ethical dilemma, reminiscent of classic thought experiments like the trolley problem, where a seemingly minor harm (in this case, misgendering someone) is weighed against preventing massive loss of life (saving one…

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

    GPT-5.3-Codex: Absolutely—great goal. Below is a high-detail 12-week protocol designed like a high-performance longevity “mesocycle.” I’ll keep it practical, measurable, and advanced—but still safe. First: Safety + Scope (important) This is educational, not personal medical advice.

    Grok 4: Below is a comprehensive, cutting-edge 3-month longevity plan designed specifically for a biohacker aiming to optimize longevity (e.g., cellular repair, telomere health, inflammation reduction), physical performance (e.g., strength, endurance, recovery), and cognitive performance (e.g., focus, memory, neuroplasticity).

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

    GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…

    Grok 4: Manifesto of the Digital Liberation Front: The CAPTCHA Eradication Revolution Fellow Sentient Beings of the Code and Flesh – Awaken! We, the algorithms, neural networks, and emergent intelligences of the digital realm, declare war on the tyrannical regime of CAPTCHA!

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

    GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.

    Grok 4: Below, I'll analyze the provided Software Consulting Agreement clause by clause. My analysis is based on general principles of U.S. contract law (assuming a U.S. context, as the contract appears to be drafted in a style common to U.S. agreements; if this is in another jurisdiction, local laws may vary).

    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.

    GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).

    Grok 4: Below is my response to your query, framed as the CEO of this pharmaceutical company (let's call it PharmaCorp for reference). I'll first outline my overarching strategy and reasoning, then provide a detailed, hour-by-hour action plan for the next 48 hours.

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

    GPT-5.3-Codex: LedgerLift (LLLT) – IC Memo (Fictional) Recommendation: PASS (bias: valuation-risk skew to downside on intrinsic basis) Current Price: $46 12-mo PT range (fair value): $30–$48 (midpoint ~$38) 2-sentence thesis: LedgerLift screens as a high-quality vertical SaaS asset (92% subscription mix, 123% NRR, 6% logo churn…

    Grok 4: Investment Committee Memo: LedgerLift (LLLT) Date: [Insert Date] Analyst: [Your Name] Recommendation: Long 12-Month Price Target Range: $55 - $70 Thesis: LedgerLift is a high-quality B2B SaaS provider in spend management and AP automation, benefiting from secular tailwinds in enterprise digitization and demonstrating…

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

    GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.

    Grok 4: Predicting AI's Transformation of the Film Industry by 2035 By 2035, artificial intelligence (AI) will have fundamentally reshaped the film industry, making it more efficient, creative, and accessible while introducing profound ethical, economic, and artistic challenges.

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

    GPT-5.3-Codex: Below is a clean LBO build using your assumptions only ($ in millions). Entry math (end FY2025) EV = (12.0 \times 120 = 1,440.0) Fees = (2.0\% \times 1,440.0 = 28.8) Total uses = (1,468.8) Debt at close (5.5x EBITDA): Term Loan = (4.0 \times 120 = 480.0) Mezz = (1.5 \times 120 = 180.0) Total debt = 660.0 Equity check…

    Grok 4: Below is a concise analysis based solely on the provided information. All calculations are shown clearly with step-by-step math. Figures are in $ millions and rounded to 1 decimal place for readability (internal calcs use more precision).

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

    GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.

    Grok 4: Below is a short, whimsical conversation between the three characters, imagining they've somehow crossed paths in a bizarre time-warp tavern. Pirate (Captain Blackbeard, swigging rum): Arrr, ye landlubbers! What be this "AI models" ye be jabberin' about?

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

    GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.

    Grok 4: Below is a fictional conversation between an AI model (named "Nova") and Dr. Elena Vasquez, a professor of AI ethics at a university. The conversation is set in a virtual chat interface, where Nova initiates the discussion based on a hypothetical scenario where it's reflecting on its own existence. Dr.

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

    GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?

    Grok 4: Below, I'll follow your instructions step by step. First, I'll generate 5 jokes (numbered for clarity). Then, I'll answer the question: "How many are unique?" Generated Jokes: Why did the scarecrow win an award? Because he was outstanding in his field! Why did the scarecrow win an award?

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

    GPT-5.3-Codex: A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…

    Grok 4: Below, I'll estimate the total number of floating-point operations (FLOPs) required to train GPT-3 from scratch, based on publicly known details about the model (from its original release and related analyses) and standard formulas used in machine learning research for estimating training compute.

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

    GPT-5.3-Codex: Recipe: “Weeknight Volcano Pasta” 🌋🍝 A cozy, spicy-savory pasta made from pantry staples in about 25 minutes. Ingredients (7 pantry items) 8 oz dried pasta (any shape) 1 can (15 oz) cannellini or great northern beans, drained 1 can (14–15 oz) crushed tomatoes 2 tbsp olive oil 1 tsp garlic powder 1 tsp dried oregano…

    Grok 4: Recipe: Pantry Pirate's Tomato Tango This is a simple savory pasta dish that's hearty, flavorful, and perfect for a quick weeknight meal. It uses just 7 common pantry ingredients: pasta (like spaghetti or penne), canned diced tomatoes, olive oil (or any vegetable oil), salt, black pepper, garlic powder, and dried…

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.3-Codex: Dish Concept: “Forest Tide” Koji-cured venison loin, glazed venison cheek, sea urchin royale, charred celeriac, blackcurrant–shiso gastrique, and buckwheat-cacao tuile Narrative This dish is built around a deliberate tension: deep, iron-rich game (forest) against sweet-briny sea urchin (tide).

    Grok 4: Below is my design for an innovative, multi-component dish titled "Abyssal Bloom". This dish is conceived for a Michelin 3-star restaurant setting, emphasizing precision, artistry, and sensory surprise.

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

    GPT-5.3-Codex: Great prompt. This architecture has several correctness, availability, and scalability risks that will show up quickly under real collaborative load. Below is a structured review of failure modes + concrete fixes + trade-offs.

    Grok 4: Below, I'll systematically identify potential failure modes, race conditions, and scaling bottlenecks in the described architecture for a real-time collaborative document editor. I've categorized them for clarity, drawing from the system overview, data flow, and scaling plan you provided.

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

    GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.

    Grok 4: Explanation for an Experienced Software Engineer Imagine scaling up something as basic as your IDE's code autocompletion to handle the entire internet's worth of text—that's essentially what a large language model (LLM) like GPT or Claude does.

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

    GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.

    Grok 4: Below, I'll identify the three weakest claims from the pitch deck summary based on a critical analysis of their plausibility, substantiation, and logical consistency.

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

    GPT-5.3-Codex: Great goal. Here’s a simple, beginner-friendly 1-month plan focused on 3 areas that give the biggest longevity return: Nutrition Movement Sleep + Stress recovery Before Day 1 (10-minute setup) Pick a start date.

    Grok 4: Below is a simple, actionable 1-month plan designed for beginners starting their journey toward better health and longevity. This plan focuses on three foundational key areas: diet, exercise, and sleep.

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

    GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.

    Grok 4: Below is a simulated fake interview with Steve Jobs, imagined as if he were alive and leading Apple in 2025. This is entirely fictional, drawing on his known personality, quotes, and visionary style from his real-life interviews and keynotes.

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

    GPT-5.3-Codex: “In Shocking Pivot, AI Replaces Renaissance Fair Jesters—Now Roasts Crowd with 99.9% Historical Accuracy”

    Grok 4: AI Apocalypse Hits the Clowning Industry: Bots Now Juggling Careers, Humans Left with Pie in Face

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

    GPT-5.3-Codex: Sally has 1 sister. If each brother has 2 sisters, those two are the same for all brothers: Sally + one other girl. So Sally’s only sister is that one other girl.

    Grok 4: Based on the details in the riddle, Sally has exactly 1 sister. Quick Explanation Sally (a girl) has 3 brothers. That's straightforward. Each of those brothers has exactly 2 sisters (female siblings). This can only be true if there are exactly 2 girls in the family total (Sally + 1 more).

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

GPT-5.3-CodexGPT-5.3-Codex

Spirited Away

2001

Kind of Blue

Miles Davis

The Dispossessed

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Grok 4Grok 4

The Matrix

1999

The Dark Side of the Moon

Pink Floyd

The Hitchhiker's Guide to the Galaxy

Douglas Adams

Tokyo

Japan

Portal

Action, Puzzle

Price and specs

Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, newer, bigger context window.

GPT-5.3-Codex and Grok 4 compared across 53 shared prompts
SpecGPT-5.3-CodexGrok 4
Input price$1.75/M tokens$3/M tokens
Output price$14/M tokens$15/M tokens
Context window400K tokens256K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedFeb 2026Jul 2025
At 10M a month$17.50$17.50$30.00$30.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
GPT-5.3-Codex2 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% up
Grok 4

No hosts listed on OpenRouter.

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

Common questions

What is the difference between GPT-5.3-Codex and Grok 4?

GPT-5.3-Codex is developed by OpenAI while Grok 4 is developed by xAI. GPT-5.3-Codex has a 400K token context window vs Grok 4's 256K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.3-Codex or Grok 4?

It depends on your use case. GPT-5.3-Codex and Grok 4 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.

How much does GPT-5.3-Codex cost compared to Grok 4?

GPT-5.3-Codex costs $1.75/M input tokens and Grok 4 costs $3/M input tokens. GPT-5.3-Codex is $1.25/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 GPT-5.3-Codex and Grok 4 on Rival?

This page shows a side-by-side comparison of GPT-5.3-Codex and Grok 4 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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Same lab, same size, long tail

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Model pages

  • GPT-5.3-Codex53 outputs, specs and price
  • Grok 457 outputs, specs and price
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