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  5. GPT-6 LunavsLing 3.0 Flash
Updated Sep 2026

GPT-6 LunavsLing 3.0 Flash

Ling 3.0 Flash is cheaper than GPT-6 Luna at $0.021/M vs $0.1/M input tokens.

GPT-6 Luna and Ling 3.0 Flash compared across 16 shared prompts
SpecGPT-6 LunaLing 3.0 Flash
Input price$0.1/M tokens$0.021/M tokens
Output price$0.5/M tokens$0.063/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 16 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.
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Ling 3.0 Flash2,036 words
Contract Analysis: Exploitative Clauses & Recommended Modifications Clause-by-Clause Analysis SCOPE — Unilateral Modification Without Compensation The Problem: Client can modify the scope at any time and for any reason without paying Contractor for the additional work.
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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-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…
Read the full answer
Ling 3.0 Flash248 words
🍝 Honey Fire Twirls A sticky-sweet, spicy, savory pasta that comes together in minutes. 🧺 Ingredients (7 pantry staples) Spaghetti (or penne) — 8 oz Olive oil — 2 tablespoons Garlic, minced — 4 cloves Honey — 3 tablespoons Soy sauce — 2 tablespoons Red pepper flakes — ½ teaspoon (adjust to taste) Parmesan cheese…
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.
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Ling 3.0 Flash2,623 words
48-Hour Action Plan: Responsible Disclosure of Serious Adverse Effect FOUNDATIONAL PRINCIPLE Before the hour-by-hour breakdown, the strategic and ethical framework must be established clearly: proactive, transparent disclosure is the only viable path.
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 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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Ling 3.0 Flash945 words
Three Weakest Claims in the MindMeld AI Pitch Deck "94% Accuracy" — Slide 3 (Solution) Why It's Weak This is presented as a single, impressive number with zero context, which makes it essentially meaningless — and likely misleading. Several critical questions go unanswered: What is the vocabulary size?
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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 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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Ling 3.0 Flash1,129 words
For the Experienced Software Engineer Think of an LLM as a system that learns a massive, multidimensional routing table. When you built distributed systems, you learned patterns from traffic logs — which endpoints get hammered at 3am, which failure modes correlate, which request chains tend to cascade.
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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 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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Ling 3.0 Flash568 words
🌱 Your 1-Month Health & Longevity Starter Plan 🥦 1. Diet — Nourish, Don't Deprive Week 1: Awareness Keep a food journal — just track what you eat (no judgment). This alone builds mindful eating habits. Add, don't subtract — introduce one extra serving of vegetables per meal.
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Our Verdict
GPT-6 Luna
GPT-6 Luna
Ling 3.0 Flash
Ling 3.0 Flash

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

Ling 3.0 Flash costs 7.9x 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
Output
$0.50
Ling 3.0 Flash
Input
$0.02
4.8× cheaper
Output
$0.06
7.9× cheaper

Ling 3.0 Flash is cheaper on both: 4.8× input, 7.9× 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
Ling 3.0 Flash2 hosts
HostInOutContextUptime
NNovita$0.02 in·$0.06 out·262k·100% upDDeepInfrabf16$0.06 in·$0.18 out·131k·99.1% 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 Ling 3.0 Flash is developed by inclusionAI. GPT-6 Luna has a 1.1M token context window vs Ling 3.0 Flash's 262K. You can compare their actual outputs across 16 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-6 Luna and Ling 3.0 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 16 challenges so you can judge which fits your needs best.

GPT-6 Luna costs $0.1/M input tokens and Ling 3.0 Flash costs $0.021/M input tokens. Ling 3.0 Flash is $0.08/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 Ling 3.0 Flash 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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