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  5. GPT-6 Luna ProvsQwen3.6 Max Preview
Updated Sep 2026

GPT-6 Luna ProvsQwen3.6 Max Preview

GPT-6 Luna Pro is cheaper than Qwen3.6 Max Preview at $0.1/M vs $1.04/M input tokens.

GPT-6 Luna Pro and Qwen3.6 Max Preview compared across 18 shared prompts
SpecGPT-6 Luna ProQwen3.6 Max Preview
Input price$0.1/M tokens$1.04/M tokens
Output price$0.5/M tokens$6.24/M tokens
Context window1.1M tokens262K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 18 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-6 Luna Pro127 words
Golden Pantry Pancakes Fluffy, lightly sweet pancakes made with everyday staples. Makes: About 6 small pancakes Prep time: 5 minutes Cook time: 10 minutes Ingredients 1 cup all-purpose flour 1 cup milk 1 egg 2 tablespoons sugar 1 teaspoon baking powder ¼ teaspoon salt 2 tablespoons butter, melted (plus a little for the…
Read the full answer
Qwen3.6 Max Preview257 words
🌅 Golden Hour Chickpea Couscous ⏱️ Prep: 5 min Cook: 10 min Total: 15 min 📦 Ingredients (exactly 7 pantry staples): 1 cup quick-cooking couscous 1 can (15 oz) chickpeas, drained & rinsed 2 tbsp olive oil 1 tsp garlic powder 1 tsp smoked paprika 2 tbsp honey 1 tbsp soy sauce (Water for cooking the couscous is assumed…
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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…

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
Qwen3.6 Max Preview1,276 words
Dish Title: Abyss & Canopy Langoustine, Black Garlic, Wild Blueberry, Fermented Spruce 📖 Conceptual Narrative Abyss & Canopy explores the liminal space where the boreal forest meets the cold northern ocean.
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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-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
Qwen3.6 Max Preview1,204 words
For the Experienced Software Engineer Think of an LLM not as a rules engine or a knowledge base, but as a massively parameterized, stateless function trained via distributed optimization. The learning objective is deceptively simple: minimize cross-entropy loss for next-token prediction across trillions of tokens.
Read the full answer

Advanced Longevity Plan (Biohacker)

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

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…
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Qwen3.6 Max Preview1,499 words
🧬 3-Month Cutting-Edge Longevity & Performance Protocol for Biohackers ⚠️ Medical Disclaimer: This protocol is for educational purposes and assumes you are a healthy adult with medical clearance. Fasting >24h, high-dose supplementation, intense training, and neurofeedback carry risks.
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-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
Qwen3.6 Max Preview1,007 words
Here’s a systematic breakdown of the architectural flaws, categorized by domain. Each item includes the failure mode/race condition/bottleneck, root cause, proposed solution, and explicit trade-offs. 🔌 1.
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Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

GPT-6 Luna Pro327 words
A simple 1-month plan for better health and longevity Choose three foundations: eating well, moving regularly, and sleeping consistently. Aim for steady habits, not perfection. Diet: Make nourishing choices easier Week 1: Add one serving of fruit or vegetables to one meal each day.
Read the full answer
Qwen3.6 Max Preview581 words
🌱 1-Month Foundation Plan for Health & Longevity Mindset: Longevity is built through consistent, small habits. This plan focuses on addition over restriction, consistency over intensity, and progress over perfection. Expect 70-80% adherence to be a win.
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Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
Qwen3.6 Max Preview
Qwen3.6 Max Preview

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

GPT-6 Luna Pro costs 12x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-6 Luna Pro
Input
$0.10
10× cheaper
Output
$0.50
12× cheaper
Qwen3.6 Max Preview
Input
$1.04
Output
$6.24

GPT-6 Luna Pro is cheaper on both: 10× input, 12× output.

Where to run it

3 hosts

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
Qwen3.6 Max Preview1 host
HostInOutContextUptime
Alibaba Cloud$1.03 in·$6.16 out·262k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

GPT-6 Luna Pro is developed by OpenAI while Qwen3.6 Max Preview is developed by Qwen. GPT-6 Luna Pro has a 1.1M token context window vs Qwen3.6 Max Preview's 262K. You can compare their actual outputs across 18 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-6 Luna Pro and Qwen3.6 Max Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 18 challenges so you can judge which fits your needs best.

GPT-6 Luna Pro costs $0.1/M input tokens and Qwen3.6 Max Preview costs $1.04/M input tokens. GPT-6 Luna Pro is $0.94/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-6 Luna Pro and Qwen3.6 Max Preview 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-6 Luna Pro logo
GPT-6 Luna Pro20 outputs, specs and price
Qwen3.6 Max Preview logo
Qwen3.6 Max Preview53 outputs, specs and price
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