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  5. GPT-5.6 SolvsGPT-6 Luna
Updated Sep 2026

GPT-5.6 SolvsGPT-6 Luna

GPT-6 Luna is cheaper than GPT-5.6 Sol at $0.1/M vs $5/M input tokens.

GPT-5.6 Sol and GPT-6 Luna compared across 20 shared prompts
SpecGPT-5.6 SolGPT-6 Luna
Input price$5/M tokens$0.1/M tokens
Output price$30/M tokens$0.5/M tokens
Context window1.1M tokens1.1M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Sep 2026
Side by side

Same prompt, both answers

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

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

GPT-5.6 Sol128 words
Pantry-Gold Peanut Butter Oat Cookies Chewy, warmly spiced cookies made with exactly seven pantry staples. Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 14 cookies 7 Ingredients 1 cup peanut butter ¾ cup brown sugar 1 large egg 1 cup rolled oats ½ teaspoon baking soda ½ teaspoon ground cinnamon ¼ teaspoon…
Read the full answer
GPT-6 Luna113 words
Crispy Parmesan Chickpeas A crunchy, savory snack with a cheesy finish Ingredients (7): 1 can chickpeas, drained and dried 1 tablespoon olive oil ½ teaspoon salt ½ teaspoon paprika ¼ teaspoon garlic powder ¼ cup grated Parmesan 1 tablespoon lemon juice Prep time: 5 minutes Cook time: 30–35 minutes Instructions: Heat…
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.…

GPT-5.6 Sol757 words
“Our non-invasive EEG headband decodes neural patterns into text with 94% accuracy—any language, any device.” Why it’s weak “94% accuracy” is undefined. It could mean binary intent classification, selecting among a handful of words, character accuracy, or genuinely open-ended text decoding—vastly different…
Read the full answer
GPT-6 Luna421 words
“94% accuracy” and “predict what you want to type before you think it” Why it’s weak: This is the deck’s central technical claim, but “accuracy” is undefined: Is it word-level or character-level accuracy, measured on a fixed vocabulary or open-ended text, and under what conditions?
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…

GPT-5.6 Sol2,439 words
This architecture will work for a small prototype, but it does not currently guarantee convergence, ordering, durability, privacy, or predictable horizontal scaling.
Read the full answer
GPT-6 Luna1,979 words
The main architectural risk is that the system treats collaborative editing as “write a value, then broadcast it.” That works poorly under concurrency, server failures, reconnects, and scale.
Read the full answer

Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

GPT-5.6 Sol3,067 words
This is a contract-risk review, not jurisdiction-specific legal advice. Enforceability—especially for non-competes, fee shifting, arbitration, confidentiality, and indemnification—depends heavily on governing law. A lawyer in the applicable jurisdiction should review the final draft.
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GPT-6 Luna2,040 words
This agreement is strongly one-sided. The enforceability of particular terms—especially the non-compete, liability provisions, and arbitration clause—depends on the governing law and the facts. The agreement does not identify a governing law, which is itself a significant gap.
Read the full answer

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

GPT-5.6 Sol2,044 words
Executive decision I would treat this as a credible, material patient-safety signal, not wait six months for a completed regulatory process. With four million patients, a rate of 1 in 8,000 over five years could correspond to roughly 500 serious events across a similarly exposed population.
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GPT-6 Luna1,930 words
I would not wait six months for more data. A potentially fatal signal affecting a drug used by millions requires immediate safety assessment, prompt engagement with regulators, and a plan to inform patients and clinicians.
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…

GPT-5.6 Sol869 words
Experienced software engineer An LLM is best understood as a parameterized program learned from data rather than written by developers. Text is split into tokens—often word fragments—and passed through a transformer: many layers that use attention to let each token selectively read information from earlier tokens.
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GPT-6 Luna672 words
For an experienced software engineer A language model is trained on many text sequences, split into tokens—roughly word fragments, not necessarily whole words. During training, it repeatedly sees a prefix and tries to predict the next token.
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Our Verdict
GPT-5.6 Sol
GPT-5.6 Sol
GPT-6 Luna
GPT-6 Luna

Not enough votes to call it. On the specs, nothing separates them.

GPT-6 Luna costs 60x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.6 Sol
Input
$5.00
Output
$30.00
GPT-6 Luna
Input
$0.10
50× cheaper
Output
$0.50
60× cheaper

GPT-6 Luna is cheaper on both: 50× input, 60× output.

Where to run it

6 hosts, cheapest first

GPT-5.6 Sol3 hosts
HostInOutContextUptime
OpenAI$2.00 in·$10.00 out·1.1M·99.9% upAzure AI Foundry$4.00 in·$20.00 out·1.1M·100% upAmazon Bedrock$4.40 in·$22.00 out·1.1M·100% up
GPT-6 Luna3 hosts
HostInOutContextUptime
Azure AI Foundry$0.10 in·$0.50 out·1.1M·88.4% upOpenAI$0.10 in·$0.50 out·1.1M·99.9% upAmazon Bedrock$0.11 in·$0.55 out·1.1M·99.8% up

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

Research

What we learned reading every model

FAQ

Common questions

Both are developed by OpenAI but target different use cases. GPT-5.6 Sol has a 1.1M token context window vs GPT-6 Luna'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. GPT-5.6 Sol and GPT-6 Luna 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.

GPT-5.6 Sol costs $5/M input tokens and GPT-6 Luna costs $0.1/M input tokens. GPT-6 Luna is $4.90/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 GPT-5.6 Sol and GPT-6 Luna 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

GPT-5.6 Sol logo
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