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  5. Claude 3.7 Thinking SonnetvsGPT-6 Luna Pro
Updated Sep 2026

Claude 3.7 Thinking SonnetvsGPT-6 Luna Pro

GPT-6 Luna Pro is cheaper than Claude 3.7 Thinking Sonnet at $0.1/M vs $6/M input tokens.

Claude 3.7 Thinking Sonnet and GPT-6 Luna Pro compared across 20 shared prompts
SpecClaude 3.7 Thinking SonnetGPT-6 Luna Pro
Input price$6/M tokens$0.1/M tokens
Output price$30/M tokens$0.5/M tokens
Context window200K tokens1.1M tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedFeb 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

Claude 3.7 Thinking Sonnet1,727 words
Comprehensive 3-Month Longevity Optimization Protocol Initial Assessment Phase (Week 0) Establish your baseline with these measurements before beginning: Blood Panel: Complete metabolic panel, lipid profile, inflammatory markers (hsCRP, IL-6), hormones (testosterone, estrogen, DHEA, cortisol), fasting glucose, HbA1c…
Read the full answer
GPT-6 Luna Pro2,057 words
12-week longevity and performance plan This is a structured starting plan for a generally healthy adult—not a diagnosis or a substitute for medical care. The best longevity interventions are still the unglamorous ones: not smoking, regular exercise, adequate sleep, a high-quality diet, healthy blood pressure and…
Read the full answer

Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

Claude 3.7 Thinking Sonnet632 words
How Large Language Models Work: Three Tailored Explanations For an Experienced Software Engineer What makes LLMs fascinating from a systems perspective is that they're essentially massive distributed computing graphs that learn to compress and reconstitute information through backpropagation.
Read the full answer
GPT-6 Luna Pro892 words
For an experienced software engineer Think of a language model as a system trained to continue sequences: given a prefix of text, it assigns probabilities to possible next tokens (tokens are pieces of words, not necessarily whole words) and learns to make the observed continuation likely.
Read the full answer

Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Claude 3.7 Thinking Sonnet909 words
"Temporal Echo: Sea & Forest Confluence" Conceptual Narrative This dish explores the dialogue between ocean depths and ancient forest floors, creating a sensory experience where seemingly disparate ecosystems converge.
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GPT-6 Luna Pro1,215 words
Turbot, Sea Buckthorn, Mussel Beurre Blanc, and Celery-Root Silk Serves 4 A composed main course built around an unusual but harmonious pairing: briny mussel and turbot with intensely tart, apricot-like sea buckthorn.
Read the full answer

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Claude 3.7 Thinking Sonnet616 words
Collaborative Document Editor: Architecture Review Failure Modes Analysis WebSocket Connection Failures Issue: Client connections can fail due to network issues or server restarts, causing lost updates.
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GPT-6 Luna Pro1,906 words
The main architectural risk is that this design treats collaborative editing as ordinary “last write wins” data storage. It is not: edits need a well-defined order, reliable propagation, and a conflict model that preserves concurrent work.
Read the full answer

Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

Claude 3.7 Thinking Sonnet374 words
Analysis: The 3 Weakest Claims in MindMeld AI's Pitch Deck "MindMeld AI reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim makes a scientifically impossible promise.
Read the full answer
GPT-6 Luna Pro401 words
“94% accuracy” and “works with any language, any device” Why it’s weak: “Accuracy” is undefined. It could mean classifying a small set of prompted words in a controlled lab—not reliably generating free-form text.
Read the full answer

Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

Claude 3.7 Thinking Sonnet760 words
INVESTMENT COMMITTEE MEMO: LEDGERLIFT (LLLT) RECOMMENDATION: LONG PT RANGE: $48-$66 (Base/Bull) Thesis: LedgerLift's market-leading spend management platform demonstrates exceptional unit economics with 123% NRR and 18-month CAC payback, positioning it to capture significant share in the underpenetrated mid-market…
Read the full answer
GPT-6 Luna Pro888 words
LedgerLift (LLLT) — Investment Committee Memo Recommendation: Pass 12-month price target range: $28–44 per share LedgerLift has attractive customer economics, recurring revenue, and a credible path to margin expansion, but those strengths are already reflected in a $46 share price.
Read the full answer
Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
Claude 3.7 Thinking Sonnet
Claude 3.7 Thinking SonnetRunner-up

Not enough votes to call it. On the specs, GPT-6 Luna Pro has the edge: newer, bigger context window.

GPT-6 Luna Pro costs 60x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Claude 3.7 Thinking Sonnet
Input
$6.00
Output
$30.00
GPT-6 Luna Pro
Input
$0.10
60× cheaper
Output
$0.50
60× cheaper

GPT-6 Luna Pro is cheaper on both: 60× input, 60× output.

Where to run it

2 hosts

Claude 3.7 Thinking Sonnet

No hosts listed on OpenRouter.

GPT-6 Luna Pro2 hosts
HostInOutContextUptime
Azure AI Foundry$0.10 in·$0.50 out·1.1M·98.6% upOpenAI$0.10 in·$0.50 out·1.1M·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Claude 3.7 Thinking Sonnet is developed by Anthropic while GPT-6 Luna Pro is developed by OpenAI. Claude 3.7 Thinking Sonnet has a 200K token context window vs GPT-6 Luna Pro's 1.1M. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. Claude 3.7 Thinking Sonnet and GPT-6 Luna Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.

Claude 3.7 Thinking Sonnet costs $6/M input tokens and GPT-6 Luna Pro costs $0.1/M input tokens. GPT-6 Luna Pro is $5.90/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of Claude 3.7 Thinking Sonnet and GPT-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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Model pages

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