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  5. GPT-6 LunavsQwen3 Next 80B A3B Thinking
Updated Sep 2026

GPT-6 LunavsQwen3 Next 80B A3B Thinking

GPT-6 Luna is cheaper than Qwen3 Next 80B A3B Thinking at $0.1/M vs $0.15/M input tokens.

GPT-6 Luna and Qwen3 Next 80B A3B Thinking compared across 20 shared prompts
SpecGPT-6 LunaQwen3 Next 80B A3B Thinking
Input price$0.1/M tokens$0.15/M tokens
Output price$0.5/M tokens$1.5/M tokens
Context window1.1M tokens66K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 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-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
Qwen3 Next 80B A3B Thinking1,491 words
Here'sa detailed analysis of exploitable clauses in this contract, with specific modifications and legal reasoning for each. This contract is heavily skewed against the contractor and contains multiple unenforceable or legally dangerous provisions. Below is a clause-by-clause breakdown: 1.
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-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
Qwen3 Next 80B A3B Thinking1,352 words
Hour-by-Hour Action Plan: Critical 48-Hour Crisis Response (Based on FDA 21 CFR 310.305, ICH E2A, and ethical principles of patient-first transparency) Core Philosophy: Patient safety and regulatory compliance are non-negotiable.
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 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.
Read the full answer
Qwen3 Next 80B A3B Thinking1,956 words
The World Transformed: A 1920 Transistor Invention Timeline (1920–1980) If the transistor had been invented in 1920—by German physicists Walter Schottky and Oskar Heil at Siemens, building on early quantum theory—instead of 1947 at Bell Labs, the technological, economic, and geopolitical landscape of the 20th century…
Read the full answer

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 Luna330 words
A simple 1-month starter plan Choose three foundations: food, movement, and sleep. Aim for steady habits, not perfection. If you have a health condition, significant pain, or concerns about changing your activity or diet, check with a healthcare professional first.
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Qwen3 Next 80B A3B Thinking221 words
Here’s a simple, science-backed 1-month plan focused on 3 foundational pillars for longevity (diet, sleep, stress management). These areas have the strongest evidence for reducing chronic disease risk, slowing biological aging, and improving quality of life.
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 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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Qwen3 Next 80B A3B Thinking821 words
For the Experienced Software Engineer You're right to be skeptical—on the surface, "predicting the next word" sounds trivial, like a glorified autocomplete. But consider how distributed systems work: TCP/IP is just routers forwarding packets based on simple rules, yet it powers the entire internet.
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 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
Qwen3 Next 80B A3B Thinking1,684 words
Here'sa comprehensive analysis of the architecture, identifying critical failure modes, race conditions, and scaling bottlenecks. For each issue, I've provided a specific solution with clear trade-offs based on real-world distributed systems best practices. 1.
Read the full answer
Our Verdict
GPT-6 Luna
GPT-6 Luna
Qwen3 Next 80B A3B Thinking
Qwen3 Next 80B A3B ThinkingRunner-up

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

GPT-6 Luna costs 3.0x 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
Input
$0.10
1.5× cheaper
Output
$0.50
3.0× cheaper
Qwen3 Next 80B A3B Thinking
Input
$0.15
Output
$1.50

GPT-6 Luna is cheaper on both: 1.5× input, 3.0× output.

Where to run it

5 hosts, cheapest first

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
Qwen3 Next 80B A3B Thinking2 hosts
HostInOutContextUptime
Alibaba Cloud$0.15 in·$1.20 out·131k·99.7% upGoogle Vertex AI$0.15 in·$1.20 out·262k·98.8% 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 is developed by OpenAI while Qwen3 Next 80B A3B Thinking is developed by Qwen. GPT-6 Luna has a 1.1M token context window vs Qwen3 Next 80B A3B Thinking's 66K. 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-6 Luna and Qwen3 Next 80B A3B Thinking 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-6 Luna costs $0.1/M input tokens and Qwen3 Next 80B A3B Thinking costs $0.15/M input tokens. GPT-6 Luna is $0.05/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 and Qwen3 Next 80B A3B 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 logo
GPT-6 Luna20 outputs, specs and price
Qwen3 Next 80B A3B Thinking logo
Qwen3 Next 80B A3B Thinking58 outputs, specs and price
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