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  1. Home/
  2. Compare/
  3. Claude 3.7 Sonnet vs GPT-5.6 Luna Pro
Updated Jul 2026

Claude 3.7 Sonnet vs GPT-5.6 Luna Pro

GPT-5.6 Luna Pro is cheaper than Claude 3.7 Sonnet at $1/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-5.6 Luna Pro

Which answer wins?

Written rounds

24 prompts
  • 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-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.

    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-5.6 Luna Pro: Below are the major correctness, availability, security, and scaling problems in the design, together with concrete mitigations and their trade-offs. Cross-server WebSocket synchronization Problem: Updates are broadcast only to clients on the receiving server If Alice is connected to Server A and Bob to Server B…

    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-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.

    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-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.

    Every model's answer to this prompt
  • 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-5.6 Luna Pro: Why did the computer go to the doctor? It had a virus. Why don’t skeletons fight each other? They don’t have the guts. What do you call a bear with no teeth? A gummy bear. Why was the math book sad? It had too many problems. What do clouds wear under their clothes? Thunderwear. Unique jokes: 5

    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-5.6 Luna Pro: This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.

    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-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.

    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-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.

    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-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?

    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-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…

    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-5.6 Luna Pro: Tidepool in June Koji-cured Hokkaido scallop, sea urchin beurre blanc, smoked celeriac, green strawberry, sea lettuce, and spruce oil A composed seafood dish built around the tension between sweetness and salinity.

    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-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.

    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-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.

    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-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.

    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-5.6 Luna Pro: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target range: $25–$42; midpoint $34. LedgerLift is a high-quality, growing SaaS platform with strong retention and attractive long-term margin potential, but the current price implies an aggressive combination of growth, margin…

    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-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.

    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-5.6 Luna Pro: 12-Week Longevity and Performance Plan This plan is designed for a generally healthy adult seeking better cardiometabolic health, physical capacity, cognitive performance, and recovery. It is not a substitute for medical care.

    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-5.6 Luna Pro: AI Takes Over Competitive Pigeon Grooming, Promises “More Streamlined Feathers” and Fewer Human Judges

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Claude 3.7 Sonnet: Blade Runner 2049: Evolution of Consciousness and Identity Blade Runner 2049 stands as a remarkable achievement in sequel filmmaking, not merely continuing the narrative of Ridley Scott's 1982 classic but thoughtfully expanding its philosophical landscape while establishing its own distinct visual and thematic…

    GPT-5.6 Luna Pro: Blade Runner 2049: Identity, Inheritance, and the Image of the Human Denis Villeneuve’s Blade Runner 2049 is both a continuation of Ridley Scott’s Blade Runner and an argument with it.

    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-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.

    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-5.6 Luna Pro: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and 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

This matchup has more rounds

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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-5.6 Luna ProGPT-5.6 Luna Pro

Arrival

2016

In Rainbows

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

Claude 3.7 Sonnet and GPT-5.6 Luna Pro compared across 54 shared prompts
SpecClaude 3.7 SonnetGPT-5.6 Luna Pro
Input price$3/M tokens$1/M tokens
Output price$15/M tokens$6/M tokens
Context window200K tokens1.1M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedFeb 2025Jul 2026
At 10M a month$30.00$30.00$10.00$10.00
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-5.6 Luna Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.

Common questions

What is the difference between Claude 3.7 Sonnet and GPT-5.6 Luna Pro?

Claude 3.7 Sonnet is developed by Anthropic while GPT-5.6 Luna Pro is developed by OpenAI. Claude 3.7 Sonnet has a 200K token context window vs GPT-5.6 Luna Pro's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude 3.7 Sonnet or GPT-5.6 Luna Pro?

It depends on your use case. Claude 3.7 Sonnet and GPT-5.6 Luna Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does Claude 3.7 Sonnet cost compared to GPT-5.6 Luna Pro?

Claude 3.7 Sonnet costs $3/M input tokens and GPT-5.6 Luna Pro costs $1/M input tokens. GPT-5.6 Luna Pro is $2.00/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-5.6 Luna Pro on Rival?

This page shows a side-by-side comparison of Claude 3.7 Sonnet and GPT-5.6 Luna Pro 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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Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

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