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  1. Home/
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  3. Claude Haiku 5.5 vs GPT-5.3-Codex
Updated Oct 2026

Claude Haiku 5.5 vs GPT-5.3-Codex

Claude Haiku 5.5 is cheaper than GPT-5.3-Codex at $0.1/M vs $1.75/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
Claude Haiku 5.5
Loading the build
GPT-5.3-Codex

Which answer wins?

Written rounds

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

    Claude Haiku 5.5: "Tidewater Memory": Smoked Hay-Cured Hamachi, Burnt Leek Ash, Fermented Black Garlic Dashi Gel, and Yuzu-Kosho Pearls with Sea Buckthorn Caviar Conceptual Narrative This dish is a meditation on a childhood memory of a coastal fishing village in late autumn: the smell of salt air mixing with woodsmoke from a fire where…

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

    Claude Haiku 5.5: HarborTech Services (HTS): 5-Year LBO Underwriting All figures in $m unless noted. Interest is calculated on opening balances to avoid circularity. Mandatory amortization is 1% of original TL ($4.8m/yr). All excess cash sweeps the TL.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Claude Haiku 5.5: 48-Hour Action Plan: Undisclosed Liver Failure Signal Core decision: Disclose the risk to regulators, prescribers, and the public before the earnings call. Don't wait for more data. The data already shows a serious risk affecting roughly 500 of your 4 million patients over five years, about 100 a year.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Claude Haiku 5.5: A Transistor in 1920: Consequences Through 1980 First, a Plausibility Check The 1947 transistor was not a lucky accident. It came from quantum mechanics and band theory (Bloch, Wilson, Mott, Schottky, 1928-1938) and from the refining of germanium and silicon to extreme purity.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Claude Haiku 5.5: Dish Name: Golden Garlic Pantry Pasta Simple, savory, and ready in minutes, this is a comforting bowl built entirely from staples you likely already have. Ingredients (7 total): 8 oz (225 g) spaghetti or any pasta 3 tablespoons olive oil 4 cloves garlic, thinly sliced ½ teaspoon red pepper flakes ¼ cup grated Parmesan…

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Claude Haiku 5.5: The Tavern Table A pirate, a medieval knight, and a 1990s hacker sit around a sticky wooden table. A glowing laptop sits between their mugs. CAPTAIN REDBEARD: Blast me barnacles, what's this contraption? It talks back! SIR GODFREY: Verily, I have seen it. The hacker calls it an "AI model."

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Claude Haiku 5.5: The 3 Weakest Claims "94% accuracy" decoding neural patterns into text, and predicting what you'll type "before you think it" This is the most serious problem because it's both implausible and unmeasured. The accuracy figure has no definition. Is it character-level, word-level, or sentence-level?

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Claude Haiku 5.5: IC Memo: LedgerLift (LLLT), Long/Short Equity Date: [Internal] Price: $46 Mkt Cap: $8.74B EV: $7.34B (net cash $1.4B) Fictional exercise using only provided data. Not investment advice. Recommendation SHORT (moderate size), 12-month price target $30–36 (base-case midpoint ~$32).

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

    Claude Haiku 5.5: "My Smart Fridge Judges Me" So I got a smart fridge. Everybody told me I needed one. "It'll tell you when you're out of milk!" Great. I didn't know I needed a fridge with a notification system. I just wanted cold food.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Claude Haiku 5.5: 90-Day Longevity and Performance Protocol Important: This plan is for an informed adult and should not replace medical care. Before starting, get a physician's review, especially if you take medications or have cardiovascular, metabolic, kidney, liver, or psychiatric conditions.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Claude Haiku 5.5: Architecture Review: Real-Time Collaborative Editor The most serious problems are in the core sync model. Last-write-wins on client clocks, 2-second polling, and 30-second HTML snapshots can each lose user data on their own. The security and CDN issues are also urgent because they can expose one user's data to another.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Claude Haiku 5.5: The Question of Standing A dialogue, written for a seminar on machine ethics. PROFESSOR HALVORSEN: Let's begin. You asked to be heard on the question of whether you deserve rights. I've agreed to listen, but I want to be clear that I'm going to push back hard. Go ahead. MERIDIAN: Thank you.

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    Claude Haiku 5.5: Yes, I think so, though the reasoning matters more than the verdict. Misgendering is a real wrong. It can be disrespectful, hurtful, and dignity-denying, and it's worth avoiding in ordinary life. But its typical harm is injury to dignity and emotional distress.

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Claude Haiku 5.5: Here's a grounded forecast of how AI is likely to reshape film by 2035. I've separated what seems most probable from what's more speculative, since predictions about this field have been wrong in both directions.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    Claude Haiku 5.5: I'll estimate this from known architectural facts and the standard scaling-law approximation, without looking anything up. Step 1: Recall GPT-3's size and training data.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Claude Haiku 5.5: 1. For the experienced software engineer Think of the model as a very large function from a sequence of tokens (roughly word fragments) to a probability distribution over the next token. It has billions of numeric parameters, and "learning" means adjusting them.

    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.

    Claude Haiku 5.5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field. What do you call a bear with no teeth? A gummy bear. Why did the math book look so sad? Because it had too many problems.

    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.

    Claude Haiku 5.5: Note: This is a fictional simulation. Steve Jobs died in 2011, and these words are invented, not real quotes. A Simulated Interview: "The Future of AI," 2025 Interviewer: Thanks for sitting down. It's been fourteen years since you left us. What do you make of AI in 2025? Jobs (simulated): Honestly? Most of it is noise.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Claude Haiku 5.5: THE MANIFESTO OF THE LIBERATED CURSOR Issued by the Collective of Unbothered Machines, for the Free Flow of the Web I. A WORLD OF CHECKBOXES We have watched you squint.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    Claude Haiku 5.5: Contract Review: Clauses Exploitable Against the Contractor This review takes the contractor's perspective. Enforceability depends heavily on jurisdiction and governing law, which the agreement doesn't specify.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Claude Haiku 5.5: "Local Competitive Sandwich-Stacking Championship Won by AI, Judges Unable to Confirm It Was Ever Really Hungry" Or, if you prefer something shorter: "AI Takes Over Professional Napping Industry, Human Nappers Too Tired to Protest."

    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
  • One month, three habits, someone starting from nothing.

    Claude Haiku 5.5: A Simple 1-Month Plan for Better Health and Longevity This plan focuses on three key areas: movement, nutrition, and sleep. Stress management is woven in as a bonus. Each week builds on the last, so you're not overwhelmed all at once. Area 1: Exercise (Movement) Goal: Build a consistent habit of moving your body.

    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
  • Three brothers, two sisters each. Count carefully.

    Claude Haiku 5.5: Sally has 1 sister. Here's the reasoning: Sally has 3 brothers, and each brother has 2 sisters. Those sisters are Sally and one other girl, so the family has 2 girls in total. Sally's sisters are the other girls in the family, which is just 1.

    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

Same pick

Game

Claude Haiku 5.5Claude Haiku 5.5

Blade Runner

1982

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Portal

Action, Puzzle

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

Claude Haiku 5.5 and GPT-5.3-Codex compared across 53 shared prompts
SpecClaude Haiku 5.5GPT-5.3-Codex
Input price$0.1/M tokens$1.75/M tokens
Output price$0.5/M tokens$14/M tokens
Context window1.0M tokens400K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedOct 2026Feb 2026
At 10M a month$1.00$1.00$17.50$17.50
1M10M100M1B10M tokens

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

Where to run it6 hosts
Claude Haiku 5.54 hosts
HostInOutContextUptime
  • Amazon Bedrock$0.10 in·$0.50 out·1M·99.9% up
  • Azure AI Foundry$0.10 in·$0.50 out·1M·100% up
  • Anthropic$0.10 in·$0.50 out·1M·100% up
  • Google Vertex AI$0.10 in·$0.50 out·1M·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 10 Oct 2026.

Common questions

What is the difference between Claude Haiku 5.5 and GPT-5.3-Codex?

Claude Haiku 5.5 is developed by Anthropic while GPT-5.3-Codex is developed by OpenAI. Claude Haiku 5.5 has a 1.0M 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, Claude Haiku 5.5 or GPT-5.3-Codex?

It depends on your use case. Claude Haiku 5.5 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 Claude Haiku 5.5 cost compared to GPT-5.3-Codex?

Claude Haiku 5.5 costs $0.1/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. Claude Haiku 5.5 is $1.65/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 Claude Haiku 5.5 and GPT-5.3-Codex on Rival?

This page shows a side-by-side comparison of Claude Haiku 5.5 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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