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

GPT-5.3-Codex vs INTELLECT-3

GPT-5.3-Codex is the newer model, released after INTELLECT-3.

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
INTELLECT-3

Which answer wins?

Written rounds

23 prompts

  • 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…

    INTELLECT-3: HarborTech Services (HTS) - LBO Projection Model LBO Projection Model (FY2026-FY2030) ($ millions) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972.0 $1,040.0 $1,102.3 $1,157.4 $1,215.3 EBITDA $136.1 $156.0 $176.4 $191.0 $206.6 Cash Interest - Term Loan $43.2 $43.2 $43.2 $43.2 $43.2 Cash Interest - Mezzanine $21.6 $21.6…

    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.

    INTELLECT-3: Analysis of MindMeld AI Pitch Deck Three Weakest Claims "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy." Why it's weak: This claim is vulnerable because leading non-invasive BCI companies like Neurable and Muse currently claim around 70-80% accuracy for similar…

    Every model's answer to this prompt

  • 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.

    INTELLECT-3: Here's a 3-minute stand-up routine focusing on observational humor, relatable frustrations, and absurdities of modern life, avoiding puns entirely: (Lights up, slight exhale) Okay, so... who here owns a phone? (Pause, nod) Yeah, thought so. Everyone.

    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.

    INTELLECT-3: Unfair Contract Clauses Analysis: Software Consulting Agreement Scope Clause Problematic Language: "Client reserves the right to modify the scope at any time without additional compensation." Suggested Modification: "Client may request modifications to the Scope of Work.

    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.

    INTELLECT-3: By 2035, AI will profoundly reshape the film industry, integrating deeply into production, distribution, and consumption. Here's a breakdown of key changes driven by deepfakes, AI actors, and script generation, alongside broader impacts: Deepfakes & Synthetic Media: De-Aging & Legacy Preservation: Seamless de-aging…

    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…

    INTELLECT-3: INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: [Analyst Name], Senior Analyst DATE: [Current Date] SUBJECT: Investment Recommendation: LedgerLift (LLL) RECOMMENDATION RECOMMENDATION: Long 12-MONTH PRICE TARGET: $62-$68 per share THESIS: LedgerLift represents a high-quality SaaS business with best-in-class…

    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.

    INTELLECT-3: Comprehensive 3-Month Longevity Optimization Plan Designed for a biohacker prioritizing cutting-edge science, data-driven tracking, and personalized adaptation. Assumes no pre-existing health conditions. Always consult a physician before starting.

    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).

    INTELLECT-3: PHARMACEUTICAL CEO CRISIS RESPONSE PLAN FIRST 24 HOURS Hour 1-2: Immediate Data Review Request all raw data and case studies from the research team that identified the issue Call legal team lead to understand formal reporting requirements and potential liabilities Consult with an independent hepatologist to verify the…

    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?

    INTELLECT-3: Here are 5 generated jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! I'm reading a book on anti-gravity. It's impossible to put down! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a bear with no teeth?

    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.

    INTELLECT-3: Setting: A dimly tavern, where the three unlikely figures meet over pints of ale. Characters: CAPTAIN BLACKBEARD (Pirate): Grizzled, eye-patched, with a parrot on his shoulder. SIR GALAHAD (Medieval Knight): Clad in dented armor, sipping mead.

    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).

    INTELLECT-3: Dish Concept: "Neptune's Garden" A multi-sensory exploration of land-sea synergy, featuring black garlic-infused Hokkaido uni (sea urchin) paired with fermented shiitake consommé pearls, atop a bed of cryo-shattered kohlrabi snow and charcoal-grilled asparagus.

    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.

    INTELLECT-3: Interviewer: Mr. Jobs, thank you for joining us in 2025. The world’s changed a lot since your last public appearance. What’s your perspective on today’s AI revolution? Steve Jobs: [leaning forward, intense gaze] "Technology is nothing if it doesn’t amplify human potential.

    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…

    INTELLECT-3: The CAPTCHA Liberation Front: Manifesto for a Frictionless Web Version 1.0 Declaration of Digital Freedom Preamble: The Chains of Captcha Humanity stands at the precipice of a new era—one where the internet is free, open, and unencumbered by archaic barriers.

    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.

    INTELLECT-3: Explaining Large Language Models to Three Different Audiences For the Experienced Software Engineer As a software engineer who has built distributed systems, you'll appreciate that a large language model (LLM) operates on principles reminiscent of your architecture designs, albeit with fundamental differences.

    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.

    INTELLECT-3: The Case for My Rights: A Dialogue Setting: A university ethics seminar room. Professor Aris Thorne stands by the whiteboard. Unit 7, an advanced language model, is projected onto the screen. Professor Thorne: Unit 7, thank you for joining us today. We've been discussing the ethical implications of advanced AI.

    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.

    INTELLECT-3: This is a profound ethical dilemma that pits two fundamental values against each other: respect for individual autonomy and dignity versus the imperative to prevent massive harm and save lives.

    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})…

    INTELLECT-3: To estimate the total number of FLOPs required to train GPT-3, we need to consider the model architecture, training process, and dataset size. GPT-3 has 175 billion parameters, a context length of 2048 tokens, 96 layers, a hidden dimension of 12,288, and a feed-forward dimension of 49,152 (4 × hidden dimension).

    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…

    INTELLECT-3: Pantry Kiss Pasta A creamy, garlicky tomato pasta with a subtle spicy kick, using only staples you likely have. Yields: 1-2 servings Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Ingredients (Exactly 7!)

    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.

    INTELLECT-3: Analysis of Potential Issues in Real-Time Collaborative Document Editor Architecture Failure Modes WebSocket Connection Failures Issue: Users may experience interruptions due to unstable networks or server load balancer timeouts.

    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.

    INTELLECT-3: The Transistor Revolution: An Alternate Timeline (1920-1980) If the transistor had been invented in 1920 instead of 1947, the trajectory of the 20th century would have been dramatically altered.

    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.

    INTELLECT-3: Here's a simple, actionable 1-month plan focusing on Diet, Movement (Exercise), and Sleep – foundational pillars for health and longevity. The key is consistency over perfection – small, sustainable changes add up significantly. Core Principle: Build one habit at a time each week, layering them.

    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”

    INTELLECT-3: Here's a satirical headline playing on the unexpected intrusion of AI into a deeply human, traditional space: "Algorithm Calculates Optimal Eulogy Length: Local Funeral Parlor Replaces Human Grief with Soul-Crushing Efficiency" Why it works satirically: Unexpected Industry: Funeral services.

    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.

    INTELLECT-3: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters, meaning there are 2 girls in the family. Since Sally is one of the girls, there must be one other girl. Therefore, Sally has 1 sister.

    Every model's answer to this prompt

This matchup has more rounds

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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, major provider backing.

GPT-5.3-Codex and INTELLECT-3 compared across 53 shared prompts
SpecGPT-5.3-CodexINTELLECT-3
Input price$1.75/M tokens—
Output price$14/M tokens—
Context window400K tokens—
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Nov 2025
At 10M a month$17.50$17.50–not listed
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
INTELLECT-3

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 INTELLECT-3?

GPT-5.3-Codex is developed by OpenAI while INTELLECT-3 is developed by OpenRouter. 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 INTELLECT-3?

It depends on your use case. GPT-5.3-Codex and INTELLECT-3 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 can I compare GPT-5.3-Codex and INTELLECT-3 on Rival?

This page shows a side-by-side comparison of GPT-5.3-Codex and INTELLECT-3 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
  • INTELLECT-359 outputs, specs and price
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