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  5. GPT-6 Luna ProvsQwen Plus 0728 (thinking)
Updated Sep 2026

GPT-6 Luna ProvsQwen Plus 0728 (thinking)

GPT-6 Luna Pro is cheaper than Qwen Plus 0728 (thinking) at $0.1/M vs $0.4/M input tokens.

GPT-6 Luna Pro and Qwen Plus 0728 (thinking) compared across 18 shared prompts
SpecGPT-6 Luna ProQwen Plus 0728 (thinking)
Input price$0.1/M tokens$0.4/M tokens
Output price$0.5/M tokens$4/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2025
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
Qwen Plus 0728 (thinking)282 words
Crispy Chickpea Pantry Pasta Sweet or savory? Savory with a zesty kick! Total time: 15 minutes Serves: 2 Why it works: Uses pantry staples to create a crunchy, garlicky, umami-packed meal with zero fresh produce needed. The chickpeas get incredibly crispy, and lemon juice (bottled) adds bright freshness.
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
Qwen Plus 0728 (thinking)1,224 words
Here's a comprehensive analysis of the architecture's failure modes, race conditions, and bottlenecks, with specific solutions and trade-offs: 1. Sync Strategy: Client Timestamps + Last-Write-Wins (LWW) Failure Mode/Race Condition: Clock Skew: Client clocks are unreliable (e.g., user's laptop time off by minutes).
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-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
Qwen Plus 0728 (thinking)1,200 words
For the Experienced Software Engineer (Skeptical Builder) Forget "next word prediction" as a simplistic heuristic—it's the emergent consequence of a massively parallel, distributed state machine solving a high-dimensional compression problem.
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-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
Qwen Plus 0728 (thinking)644 words
Based on a rigorous analysis of neuroscience, market realities, and startup best practices, here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-backed critiques and concrete fixes: Weakest Claim #1: Slide 1 Vision – "Predicts what you want to type *before you think it*" Why it's weak: Violates…
Read the full answer

Historical Counterfactual Analysis

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

GPT-6 Luna Pro1,661 words
The biggest change would not be that 1920 suddenly gets modern computers. It would be that governments and firms have six or seven extra decades to develop semiconductor materials, manufacturing, and applications.
Read the full answer
Qwen Plus 0728 (thinking)1,714 words
The Transistor in 1920: A World Transformed by 1980 (A Counterfactual History) The invention of a functional point-contact transistor (likely germanium-based, given 1920s materials science) in 1920 wouldn't immediately spark a revolution.
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…

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
Qwen Plus 0728 (thinking)976 words
"Symbiosis: Mycelial Bloom & Arctic Ember" A dish exploring the hidden dialogue between forest decay and renewal, where fungal lifeblood meets the fierce brightness of the Arctic tundra.
Read the full answer
Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
Qwen Plus 0728 (thinking)
Qwen Plus 0728 (thinking)Runner-up

Not enough votes to call it. On the specs, GPT-6 Luna Pro has the edge: newer, major provider backing.

GPT-6 Luna Pro costs 8.0x 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
4.0× cheaper
Output
$0.50
8.0× cheaper
Qwen Plus 0728 (thinking)
Input
$0.40
Output
$4.00

GPT-6 Luna Pro is cheaper on both: 4.0× input, 8.0× output.

Where to run it

2 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
Qwen Plus 0728 (thinking)

No hosts listed on OpenRouter.

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 Qwen Plus 0728 (thinking) is developed by Qwen. GPT-6 Luna Pro has a 1.1M token context window vs Qwen Plus 0728 (thinking)'s 1.0M. 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 Qwen Plus 0728 (thinking) 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 Qwen Plus 0728 (thinking) costs $0.4/M input tokens. GPT-6 Luna Pro is $0.30/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 Qwen Plus 0728 (thinking) 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
Qwen Plus 0728 (thinking) logo
Qwen Plus 0728 (thinking)37 outputs, specs and price
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