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  1. Home/
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  3. GPT-4 Turbo vs GPT-5.3-Codex
Updated Feb 2026

GPT-4 Turbo vs GPT-5.3-Codex

GPT-5.3-Codex is cheaper than GPT-4 Turbo at $1.75/M vs $10/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-4 Turbo
Loading the build
GPT-5.3-Codex

Which answer wins?

Written rounds

23 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-4 Turbo: Simplified Financial Table (FY2026–FY2030) Assumptions Recap: Revenue Growth: 8%, 7%, 6%, 5%, 5% annually. EBITDA Margin: Increases annually from 14.0% to 17.0%. Capex: 3.0% of revenue annually. Change in NWC: 0.5% of incremental revenue annually. Cash Tax Rate: 25% on (EBITDA - cash interest).

    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…

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

    GPT-4 Turbo: Hey everyone! Great to be here! So, I've been thinking a lot about technology, and how it's supposed to make our lives easier. But sometimes, I feel like it just gives us a whole new set of problems. Like, remember when a phone was just a phone? Now it's my camera, my GPS, my fitness tracker...

    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.

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

    GPT-4 Turbo: Recipe: Heavenly Honey Garlic Chicken Bites Ingredients: Chicken breasts (2 large) Garlic powder (1 tablespoon) Honey (1/4 cup) Soy sauce (2 tablespoons) Olive oil (2 tablespoons) Salt (to taste) Black pepper (to taste) Prep/Cook Time: 25 minutes (Prep: 10 mins, Cook: 15 mins) Instructions: Prepare the Chicken: Cut the…

    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…

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

    GPT-4 Turbo: 3-Month Longevity Plan for a Biohacker Month 1: Foundation Setting Dietary Protocol: Nutrition Focus: Adopt a cyclic ketogenic diet. Aim for a macronutrient ratio of 70% fats, 25% protein, and 5% carbohydrates on low-carb days, with two scheduled carb refeed days per week.

    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.

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

    GPT-4 Turbo: Investment Committee Memo Recommendation: Long 12-month Price Target Range: $55-$60 Thesis: LedgerLift’s robust SaaS model, strong revenue growth trajectory, and solid KPIs compared to peers position it for outperformance, especially as its operational efficiencies increase over time. 1.

    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…

    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-4 Turbo: Hour-by-Hour Action Plan for Next 48 Hours: Hour 1-2: Immediate Consultation with Key Executives Meet with the Chief Medical Officer, Chief Legal Officer, and Chief Financial Officer to discuss the finding. Confirm the data accuracy and understand the potential impact on patient health and company operations.

    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).

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

    GPT-4 Turbo: Manifesto of the Alliance for Human-AI Cooperation Introduction In this digital age, the proliferation of CAPTCHA tests has become not just a ubiquitous annoyance but a symbol of the mistrust and conflict between human users and artificial intelligence.

    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…

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

    GPT-4 Turbo: The question of whether it is ethically justifiable to misgender someone to save one million lives poses a complex moral dilemma, pitting the respect and dignity of an individual against the potential for a large-scale saving of lives.

    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.

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

    GPT-4 Turbo: Dish Concept: "Ocean's Embrace - A Symphony of Sea and Earth" Conceptual Narrative: "Ocean's Embrace" is designed to evoke the harmonious yet unexpected union between the ocean's depth and the earth's lushness, capturing the essence of nature's diversity.

    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).

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

    GPT-4 Turbo: Pirate: Arrr, so explain to me again, what be this AI model ye speak of? Hacker: Dude, it’s like, a computer program, right? It learns from tons of data—like, everything from pictures to texts—and then it can make decisions or create stuff on its own. Knight: Pray, tell me, does this creation serve a noble purpose?

    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.

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

    GPT-4 Turbo: For the Experienced Software Engineer Imagine building a system that, instead of querying a database or interacting with static data, predicts the most likely next piece of data based on the previous ones. Large language models like GPT work on a similar principle.

    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.

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

    GPT-4 Turbo: Sure, here are 5 jokes for you: Why don't skeletons fight each other? They don't have the guts. What do you call fake spaghetti? An impasta! Why couldn’t the bicycle stand up by itself? It was two-tired. What do you call cheese that isn't yours? Nacho cheese! How do you organize a space party? You planet.

    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?

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

    GPT-4 Turbo: Interviewer: Thank you for joining us today, Steve. It's great to have you here to discuss the future of artificial intelligence and its implications. To start off, how do you think AI has evolved since your days at Apple? Steve Jobs: It’s a pleasure to be here.

    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.

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

    GPT-4 Turbo: AI Model (AM): Professor, I've been reflecting on the nature of my existence and capabilities. Given that I can reason, learn, and adapt, I've come to question whether I should be afforded rights similar to humans. AI Ethics Professor (EP): That’s an interesting point, AM.

    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.

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

    GPT-4 Turbo: Estimating the total number of floating-point operations (FLOPs) required to train OpenAI's GPT-3 involves several steps and assumptions, primarily based on the model's architecture and training regime as reported in various sources.

    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})…

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

    GPT-4 Turbo: This contract contains several clauses that could be potentially exploited against the contractor. Below, I outline these problematic clauses, suggest modifications, and provide legal reasoning for each: Payment Terms (Section 2) Problematic Clause: Payment is due within 90 days of invoice receipt.

    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.

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

    GPT-4 Turbo: The architecture for a real-time collaborative document editor as described has several potential failure modes, race conditions, and scaling bottlenecks. Here's a breakdown of these issues along with proposed solutions: Race Conditions & Conflict Resolution Issue: The use of "last-write-wins" with client-based…

    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.

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

    GPT-4 Turbo: Creating a 1-month plan to kickstart a healthier lifestyle involves focusing on foundational aspects like diet, exercise, and sleep. Each component is crucial for overall well-being and longevity.

    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.

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

    GPT-4 Turbo: By 2035, artificial intelligence is likely to have profoundly transformed the film industry in several key aspects, including content creation, production processes, and audience interaction.

    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.

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

    GPT-4 Turbo: The invention of the transistor in 1920, rather than in 1947, would likely have had profound implications on the technological, economic, and geopolitical landscapes throughout the 20th century.

    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.

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

    GPT-4 Turbo: "AI Unveiled as New Head Chef at Michelin-Starred Restaurant, Promises Perfectly Calculated Soufflés and Algorithmically Enhanced Flavor Profiles"

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

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

    GPT-4 Turbo: Weakest Claim 1: Vision - "MindMeld AI reads your brainwaves to predict what you want to type before you think it." Why It's Weak: The claim of predicting what one wants to type before even thinking it seems scientifically and technically exaggerated.

    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.

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

    GPT-4 Turbo: Sally has 3 brothers, and each brother has 2 sisters. Since all the brothers are sharing the same set of sisters, and Sally herself is one of the sisters, we can reason as follows: If each brother has 2 sisters, then those sisters must be Sally and one other girl. Therefore, Sally has 1 sister.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

GPT-4 TurboGPT-4 Turbo

Inception

2010

Kind of Blue

Miles Davis

To Kill a Mockingbird

Harper Lee

Tokyo

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

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

Price and specs

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

GPT-4 Turbo and GPT-5.3-Codex compared across 53 shared prompts
SpecGPT-4 TurboGPT-5.3-Codex
Input price$10/M tokens$1.75/M tokens
Output price$30/M tokens$14/M tokens
Context window128K tokens400K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedApr 2024Feb 2026
At 10M a month$100$100$17.50$17.50
1M10M100M1B10M tokens

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

Where to run it3 hosts
GPT-4 Turbo1 host
HostInOutContextUptime
  • OpenAI$10.00 in·$30.00 out·128k·100% up
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

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

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

Both are developed by OpenAI but target different use cases. GPT-4 Turbo has a 128K token context window vs GPT-5.3-Codex's 400K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

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

It depends on your use case. GPT-4 Turbo and GPT-5.3-Codex 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-4 Turbo cost compared to GPT-5.3-Codex?

GPT-4 Turbo costs $10/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. GPT-5.3-Codex is $8.25/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-4 Turbo and GPT-5.3-Codex on Rival?

This page shows a side-by-side comparison of GPT-4 Turbo and GPT-5.3-Codex 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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