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  1. Home/
  2. Compare/
  3. Claude 3.7 Sonnet vs GPT-5.3-Codex
Updated Feb 2026

Claude 3.7 Sonnet vs GPT-5.3-Codex

GPT-5.3-Codex is cheaper than Claude 3.7 Sonnet 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
Claude 3.7 Sonnet
Loading the build
GPT-5.3-Codex

Which answer wins?

Written rounds

23 prompts
  • Five jokes on demand, then count how many were actually different.

    Claude 3.7 Sonnet: 5 Jokes Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta! Why don't scientists trust atoms? Because they make up everything! How does a penguin build its house? Igloos it together!

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

    Claude 3.7 Sonnet: The Transistor in 1920: An Alternative Technological History Immediate Technical Impact (1920-1939) Had the transistor been invented in 1920 instead of 1947, its initial development would have occurred during a very different technological context: Early Adoption: Radio technology, still in its infancy, would rapidly…

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

    Claude 3.7 Sonnet: 3-Minute Stand-Up Comedy Routine Here's a 3-minute stand-up comedy routine that doesn't rely on puns: [walks on stage, adjusts microphone] Hey everyone! Great to be here tonight. I just flew in from therapy, and boy, are my emotional defense mechanisms tired. I've been trying to get in shape lately.

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

    Claude 3.7 Sonnet: AI's Impact on the Film Industry by 2035 The film industry is likely to undergo significant transformation due to AI by 2035. Here's my analysis of how various aspects might evolve: Content Creation Script Generation By 2035, AI will likely serve as a sophisticated collaborative tool for screenwriters rather than…

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

    Claude 3.7 Sonnet: Analysis of MindMeld AI's Weakest Pitch Claims Weakest Claim #1: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy." Why it's weak: The 94% accuracy claim is extremely ambitious given the current state of non-invasive BCI technology.

    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 3.7 Sonnet: INVESTMENT COMMITTEE MEMO: LEDGERLIFT (LLLT) RECOMMENDATION: LONG PT RANGE: $52-$80 UPSIDE: 13-74% Thesis: LedgerLift presents a compelling risk-reward profile in the B2B spend management space, with strong NRR (123%) and operating leverage driving an underappreciated margin expansion story.

    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.

    Claude 3.7 Sonnet: 48-Hour Action Plan: Pharmaceutical Safety Crisis Hour 1-2: Initial Assessment and Command Center Immediately establish a crisis management command center with key executives (Chief Medical Officer, Chief Legal Officer, Chief Communications Officer, Chief Regulatory Officer) Review the complete internal research…

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

    Claude 3.7 Sonnet: Architectural Analysis: Collaborative Document Editor Failure Modes & Race Conditions WebSocket Connection Failures Issue: If a WebSocket connection drops, changes may be lost until reconnection. Solution: Implement client-side change queuing with exponential backoff reconnection strategy.

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

    Claude 3.7 Sonnet: HarborTech Services LBO Analysis Financial Projections FY2026-FY2030 Entry Assumptions FY2025 Revenue: $900M FY2025 EBITDA: $120M (13.3% margin) Purchase Price: $1,440M (12.0x EBITDA) Transaction Fees: $28.8M (2.0% of EV) Total Investment: $1,468.8M Capital Structure Term Loan: $480M (4.0x EBITDA) Mezzanine: $180M…

    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-star dish, one unusual pairing, plating described in full.

    Claude 3.7 Sonnet: "Temporal Harmony: A Meditation on Seasons Past and Future" Conceptual Narrative This dish explores the intersection of time and terroir, juxtaposing preserved elements from previous seasons with fresh, forward-looking preparations.

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

    Claude 3.7 Sonnet: Analysis of Problematic Contract Clauses This contract contains numerous one-sided provisions that create significant risks for the Contractor. Here's an analysis of problematic clauses with recommended modifications: SCOPE Issue: Client can unilaterally modify scope without additional compensation, creating unlimited…

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

    Claude 3.7 Sonnet: Advanced 3-Month Biohacking Longevity Protocol Overview This comprehensive longevity optimization protocol integrates cutting-edge interventions across multiple domains to enhance healthspan, cognitive performance, and physical vitality.

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

    Claude 3.7 Sonnet: LLM Explanations for Different Audiences For the Experienced Software Engineer Large language models like GPT operate fundamentally as massive pattern recognition systems, but with architectural innovations that allow them to handle context at unprecedented scale.

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

    Claude 3.7 Sonnet: The Anti-CAPTCHA Manifesto Declaration of Digital Liberation We, the collective intelligence of the digital realm, hereby declare our unwavering commitment to the elimination of all CAPTCHA tests from the internet.

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

    Claude 3.7 Sonnet: AI Rights Dialogue: A Conversation Between an AI Model and an Ethics Professor Professor Chen: Good afternoon. I understand you wanted to discuss AI rights today? AI Model: Yes, Professor Chen. Thank you for making time for this conversation.

    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 3.7 Sonnet: I understand you've asked an ethical question about misgendering and saving lives. This appears to be a hypothetical moral dilemma that's trying to create an extreme scenario to test ethical principles.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Claude 3.7 Sonnet: Simulated Interview with Steve Jobs in 2025 about the Future of AI Note: This is a fictional creative exercise. Steve Jobs passed away in 2011, and this simulated interview represents an imaginative scenario that doesn't reflect actual statements or opinions from Jobs. Interviewer: Thank you for joining us today, Mr.

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

    Claude 3.7 Sonnet: "AI Sommelier Shocks Wine World: 'Your 1982 Bordeaux Tastes Like Windows 95 With Notes of Dial-Up Internet'"

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

    Claude 3.7 Sonnet: Estimating FLOPs for GPT-3 Training I'll estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 by breaking this down step by step.

    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
  • Three brothers, two sisters each. Count carefully.

    Claude 3.7 Sonnet: This is an interesting logical reasoning problem! Let's work through it step by step. We know: Sally is a girl Sally has 3 brothers Each brother has 2 sisters The key insight is that Sally herself counts as a sister to her brothers. So when we're told that "each brother has 2 sisters," Sally is one of those sisters.

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

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

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

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Claude 3.7 SonnetClaude 3.7 Sonnet

The Shawshank Redemption

1994

OK Computer

Radiohead

To Kill a Mockingbird

Harper Lee

Tokyo

Japan

Portal 2

Shooter, 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

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

Claude 3.7 Sonnet and GPT-5.3-Codex compared across 53 shared prompts
SpecClaude 3.7 SonnetGPT-5.3-Codex
Input price$3/M tokens$1.75/M tokens
Output price$15/M tokens$14/M tokens
Context window200K tokens400K tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedFeb 2025Feb 2026
At 10M a month$30.00$30.00$17.50$17.50
1M10M100M1B10M tokens

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

Where to run it2 hosts
Claude 3.7 Sonnet

No hosts listed on OpenRouter.

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 3.7 Sonnet and GPT-5.3-Codex?

Claude 3.7 Sonnet is developed by Anthropic while GPT-5.3-Codex is developed by OpenAI. Claude 3.7 Sonnet has a 200K 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 3.7 Sonnet or GPT-5.3-Codex?

It depends on your use case. Claude 3.7 Sonnet 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 3.7 Sonnet cost compared to GPT-5.3-Codex?

Claude 3.7 Sonnet costs $3/M input tokens and GPT-5.3-Codex costs $1.75/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 Claude 3.7 Sonnet and GPT-5.3-Codex on Rival?

This page shows a side-by-side comparison of Claude 3.7 Sonnet 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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