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  5. GPT-5.6 LunavsQwen3.8 Max Prime
Updated Sep 2026

GPT-5.6 LunavsQwen3.8 Max Prime

GPT-5.6 Luna is cheaper than Qwen3.8 Max Prime at $1/M vs $4/M input tokens.

GPT-5.6 Luna and Qwen3.8 Max Prime compared across 19 shared prompts
SpecGPT-5.6 LunaQwen3.8 Max Prime
Input price$1/M tokens$4/M tokens
Output price$6/M tokens$12/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 19 prompts both answered. Formatting stripped, words untouched.

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 Luna2,809 words
Below is a contractor-side risk review. Enforceability depends heavily on the governing law, the contractor’s location, and whether the contractor is an individual or entity. Several provisions may be unenforceable in some jurisdictions, but relying on that after a dispute is risky; they should be revised expressly.
Read the full answer
Qwen3.8 Max Prime2,126 words
Contract Analysis: Exploitative Clauses & Recommended Modifications Executive Summary This agreement is severely one-sided in favor of the Client. Nearly every clause shifts risk, cost, or obligation onto the Contractor while granting the Client broad unilateral rights. Below is a clause-by-clause breakdown.
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 Luna842 words
For an experienced software engineer A language model is trained much like an extremely large system for compressing and reconstructing text. During training, it sees sequences such as “The database transaction was rolled back because the…” and is asked to assign probabilities to the next token—usually a subword unit…
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Qwen3.8 Max Prime1,147 words
For the Software Engineer Think of it this way: you've built systems where simple rules at the node level produce emergent behavior at the system level — consensus protocols, eventual consistency, cellular automata-like patterns in distributed state machines. An LLM is a similar phenomenon at a different scale.
Read the full answer

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 Luna152 words
Sunset Pantry Pasta A savory, slightly spicy tomato-tuna pasta made with seven simple pantry ingredients. Ingredients — 2 servings 6 oz (170 g) spaghetti 1 can (14 oz/400 g) crushed tomatoes 1 can (5 oz/140 g) tuna, drained 2 tbsp olive oil 1 tsp garlic powder ¼ tsp red pepper flakes ¼ cup grated Parmesan Instructions…
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Qwen3.8 Max Prime223 words
🍯 Golden Hour Noodles A sweet, savory, garlicky pasta that tastes like it took way more effort than it did. Ingredients (7) # Ingredient Amount 1 Spaghetti 8 oz (half a box) 2 Butter 3 tablespoons 3 Garlic, minced 4 cloves 4 Honey 2 tablespoons 5 Soy sauce 1 tablespoon 6 Red pepper flakes ½ teaspoon 7 Parmesan cheese…
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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-5.6 Luna608 words
1-Month Beginner Plan for Better Health and Longevity Key principles Aim for consistency, not perfection. Start small enough that you can repeat it. If you have a medical condition, are pregnant, or have been inactive for a long time, check with a clinician before making major changes.
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Qwen3.8 Max Prime473 words
Your 1-Month Foundation Plan A simple, progressive plan built on three pillars. Each week, you add one small layer. No perfection required—just consistency. 🏃 Pillar 1: Movement Why: Even modest activity reduces all-cause mortality risk and improves mood, sleep, and energy within days.
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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-5.6 Luna2,445 words
The architecture has several correctness, availability, security, and scaling risks. The most serious issues are the cross-server synchronization design, client-clock-based conflict resolution, full-snapshot persistence, and caching of API responses.
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Qwen3.8 Max Prime2,271 words
Architecture Analysis: Failure Modes, Race Conditions & Scaling Bottlenecks SYNC & CONSISTENCY LAYER 1.1 Last-Write-Wins with Client Clocks (Critical) Failure Mode: Client clocks are unreliable. A user with a clock skewed +5 minutes will always "win" conflicts.
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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-5.6 Luna842 words
“94% accuracy” and “works with any language, any device” Why it is weak This is the most technically vulnerable claim in the deck. “Accuracy” is undefined. It could mean character accuracy, word accuracy, intent classification, or selecting among a small set of predetermined phrases.
Read the full answer
Qwen3.8 Max Prime834 words
The 3 Weakest Claims in the MindMeld AI Pitch The TAM Calculation (Slide 4) The Claim: "We're targeting the 3.5 billion smartphone users worldwide. TAM: $180B." Why it's weak: This is a textbook example of TAM inflation that will immediately erode investor trust.
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Our Verdict
Qwen3.8 Max Prime
Qwen3.8 Max Prime
GPT-5.6 Luna
GPT-5.6 LunaRunner-up

Not enough votes to call it. On the specs, Qwen3.8 Max Prime has the edge: bigger model tier, newer.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.6 Luna
Input
$1.00
4.0× cheaper
Output
$6.00
2.0× cheaper
Qwen3.8 Max Prime
Input
$4.00
Output
$12.00

GPT-5.6 Luna is cheaper on both: 4.0× input, 2.0× output.

Where to run it

4 hosts, cheapest first

GPT-5.6 Luna3 hosts
HostInOutContextUptime
Azure AI Foundry$0.20 in·$1.20 out·1.1M·99.5% upOpenAI$0.20 in·$1.20 out·1.1M·99.9% upAmazon Bedrock$0.22 in·$1.32 out·1.1M·100% up
Qwen3.8 Max Prime1 host
HostInOutContextUptime
Alibaba Cloud$4.00 in·$12.00 out·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

GPT-5.6 Luna is developed by OpenAI while Qwen3.8 Max Prime is developed by Qwen. GPT-5.6 Luna has a 1.1M token context window vs Qwen3.8 Max Prime's 1.0M. You can compare their actual outputs across 19 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.6 Luna and Qwen3.8 Max Prime each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 19 challenges so you can judge which fits your needs best.

GPT-5.6 Luna costs $1/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. GPT-5.6 Luna is $3.00/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 Luna and Qwen3.8 Max Prime 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 Luna logo
GPT-5.6 Luna58 outputs, specs and price
Qwen3.8 Max Prime logo
Qwen3.8 Max Prime19 outputs, specs and price
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