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  5. GPT-6 Luna ProvsNemotron 3.5 Lightning
Updated Sep 2026

GPT-6 Luna ProvsNemotron 3.5 Lightning

Nemotron 3.5 Lightning is cheaper than GPT-6 Luna Pro at $0.08/M vs $0.1/M input tokens.

GPT-6 Luna Pro and Nemotron 3.5 Lightning compared across 20 shared prompts
SpecGPT-6 Luna ProNemotron 3.5 Lightning
Input price$0.1/M tokens$0.08/M tokens
Output price$0.5/M tokens$0.2/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedSep 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

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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Nemotron 3.5 Lightning931 words
This is a comprehensive 3-month longevity optimization protocol designed for the advanced biohacker. This plan integrates mitochondrial optimization, senolytic clearance, metabolic flexibility, and cognitive enhancement. Disclaimer: This plan is for educational purposes only.
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.
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Nemotron 3.5 Lightning1,273 words
This architecture is a classic "Google Docs clone" design. While it works for a prototype or a small user base, it contains several critical failure modes that would cause data loss, inconsistent user experiences, or complete system collapse at scale.
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.
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Nemotron 3.5 Lightning869 words
Dish Name: The Alchemy of the Tundra: A Study in Contrasts Conceptual Narrative: This dish is a meditation on the extremes of the Arctic landscape and the human desire to tame it. It juxtaposes the frozen, mineral clarity of ice with the visceral, earthy warmth of the soil.
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-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…
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Nemotron 3.5 Lightning316 words
Dish Name: The "Lazy" 5-Minute Crispy Pancake Pizza Concept: A quick, savory breakfast or snack that feels like a gourmet pizza but uses pantry staples. It relies on the magic of a simple batter to create a crispy base.
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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-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.
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Nemotron 3.5 Lightning971 words
Here are the three weakest claims in the MindMeld AI pitch deck, analyzed for their logical gaps and factual weaknesses, along with suggestions for strengthening them. The "94% Accuracy" Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
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Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

GPT-6 Luna Pro888 words
LedgerLift (LLLT) — Investment Committee Memo Recommendation: Pass 12-month price target range: $28–44 per share LedgerLift has attractive customer economics, recurring revenue, and a credible path to margin expansion, but those strengths are already reflected in a $46 share price.
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Nemotron 3.5 Lightning1,018 words
INTERNAL INVESTMENT COMMITTEE MEMO To: Long/Short Equity Committee From: Analyst Date: October 26, 2023 Subject: LedgerLift (LLLT) – Mid-Market Spend Management Automation Recommendation & Thesis RECOMMENDATION: Long 12-Month Price Target: $58 – $70 THESIS: LLLT is a compounding compounder trading at a discount to its…
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Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
Nemotron 3.5 Lightning
Nemotron 3.5 LightningRunner-up

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

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-6 Luna Pro
Input
$0.10
Output
$0.50
Nemotron 3.5 Lightning
Input
$0.08
1.3× cheaper
Output
$0.20
2.5× cheaper

Nemotron 3.5 Lightning is cheaper on both: 1.3× input, 2.5× output.

Where to run it

6 hosts, cheapest first

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
Nemotron 3.5 Lightning4 hosts
HostInOutContextUptime
DDarkbloomint4$0.07 in·$0.18 out·262k·100% upCCoreWeavebf16$0.07 in·$0.20 out·262k·99.9% upPPhala$0.07 in·$0.20 out·262k·99.5% upDDeepInfrabf16$0.08 in·$0.20 out·262k·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-6 Luna Pro is developed by OpenAI while Nemotron 3.5 Lightning is developed by NVIDIA. GPT-6 Luna Pro has a 1.1M token context window vs Nemotron 3.5 Lightning's 1.0M. 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 Pro and Nemotron 3.5 Lightning 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 Pro costs $0.1/M input tokens and Nemotron 3.5 Lightning costs $0.08/M input tokens. Nemotron 3.5 Lightning is $0.02/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 Nemotron 3.5 Lightning 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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Same lab, same size, long tail

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Model pages

GPT-6 Luna Pro logo
GPT-6 Luna Pro20 outputs, specs and price
Nemotron 3.5 Lightning logo
Nemotron 3.5 Lightning58 outputs, specs and price
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