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  5. GPT-5.5vsGPT-6 Luna
Updated Sep 2026

GPT-5.5vsGPT-6 Luna

GPT-6 Luna is cheaper than GPT-5.5 at $0.1/M vs $5/M input tokens.

GPT-5.5 and GPT-6 Luna compared across 20 shared prompts
SpecGPT-5.5GPT-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
ReleasedApr 2026Sep 2026
Side by side

Same prompt, both answers

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

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…

GPT-5.51,055 words
LedgerLift (LLLT) IC Memo — Fictional Recommendation: Pass / Watchlist Current price: $46 Market cap: $8.7B; EV: $7.3B after $1.4B net cash 12-month fair value range: $40–$50/share Thesis, 2 sentences: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with 92% subscription revenue, 123%…
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GPT-6 Luna896 words
LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target: $28–$42 At $46, LedgerLift’s price implies continued strong growth and margin expansion; our DCF scenarios value the shares at approximately $17–$42, with the base case near $28.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GPT-5.53,386 words
A transistor invented in 1920 would not simply move the entire digital age back by 27 years. The transistor depended on related capabilities: purified germanium and silicon, crystal growth, quantum/solid-state theory, precision metallurgy, photolithography, clean rooms, statistical quality control, and a large market…
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GPT-6 Luna1,472 words
The most important caveat is that inventing a transistor is not the same as inventing the modern semiconductor industry. A device demonstrated in 1920 might be a crude, low-power, unreliable point-contact transistor.
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Adversarial Contract Review

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

GPT-5.52,391 words
Not legal advice; contract enforceability depends heavily on jurisdiction and facts. A contractor should have a lawyer review this before signing. That said, this draft is heavily one-sided and contains multiple clauses that could be exploited against the contractor.
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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.
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Debug This Architecture

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

GPT-5.53,819 words
Below is a comprehensive review of the architecture’s likely failure modes, race conditions, and scaling bottlenecks, with concrete mitigations and trade-offs. Real-time Synchronization Problems 1.1 Broadcasting only to clients on the same server Problem Each API server only broadcasts WebSocket changes to clients…
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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.
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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-5.5519 words
Weak claim Why it’s weak How to strengthen it 1. “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device.” This is the biggest technical red flag.
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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?
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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-5.5125 words
Smoky Sunset Chickpea Skillet 7 Pantry Ingredients 1 can chickpeas, undrained 1 can diced tomatoes 2 tablespoons olive oil 1 teaspoon garlic powder 1 teaspoon smoked paprika 1/2 teaspoon ground cumin 1/2 teaspoon salt Estimated Time Prep time: 5 minutes Cook time: 15 minutes Total time: 20 minutes Instructions Heat the…
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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…
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Our Verdict
GPT-5.5
GPT-5.5
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-5.5
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-5.53 hosts
HostInOutContextUptime
Azure AI Foundry$5.00 in·$30.00 out·1.1M·99.9% upOpenAI$5.00 in·$30.00 out·1.1M·99.9% upAmazon Bedrock$5.50 in·$33.00 out·1.1M—
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-5.5 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-5.5 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-5.5 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-5.5 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

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