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  5. GPT-6 LunavsGrok 4.6
Updated Sep 2026

GPT-6 LunavsGrok 4.6

GPT-6 Luna is cheaper than Grok 4.6 at $0.1/M vs $2/M input tokens.

GPT-6 Luna and Grok 4.6 compared across 20 shared prompts
SpecGPT-6 LunaGrok 4.6
Input price$0.1/M tokens$2/M tokens
Output price$0.5/M tokens$6/M tokens
Context window1.1M tokens500K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2026
Side by side

Same prompt, both answers

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

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.
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Grok 4.6838 words
Early transistors (1920s–1930s) would accelerate electronics, communications, and computing by ~20–25 years relative to actual history, with compounding effects by WWII, but constrained by contemporaneous materials science, manufacturing, vacuum-tube infrastructure, and non-electronic fields like rocketry, chemistry…
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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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Grok 4.61,013 words
This is not legal advice. Contract interpretation and enforceability vary by jurisdiction (e.g., California vs. Texas vs. EU), and a licensed attorney should review any real agreement. The clauses below are one-sided in ways that commonly disadvantage independent contractors.
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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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Grok 4.61,096 words
1. Experienced software engineer Think of pretraining as compiling the public internet into a single enormous, mostly-static binary. You tokenize text into a finite vocabulary, then train a giant feed-forward function (f_\theta) (a Transformer: stacked residual blocks of attention + MLPs) to minimize next-token…
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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-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.
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Grok 4.62,111 words
Architecture Review: Real-Time Collaborative Editor This design will not behave like Google Docs. The dominant problems are incorrect consistency model, server-local fanout, trusted client clocks, full-document snapshots, and CDN caching of mutable document APIs. Several of these cause silent data loss, not just lag.
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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 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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Grok 4.6966 words
The three weakest claims are the “before you think it” vision line, the 94% / any-language technical claim, and the $180B TAM. Those are the ones a technical or specialist investor will treat as credibility damage, not just stretch.
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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 Luna1,249 words
Turbot, White Asparagus, Green Strawberry Kosho & Toasted-Hay Beurre Blanc A composed spring dish for four, built around an unusual pairing: tart green strawberry and toasted hay.
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Grok 4.6711 words
Lunar Embrace This dish evokes a moonlit Japanese coastline at the precise instant when receding tide exposes both ocean treasures and forest-floor secrets. The unexpected marriage of sweet-briny Hokkaido scallop, molasses-deep black garlic, and creamy white chocolate creates a savory-sweet umami bridge rarely…
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Our Verdict
GPT-6 Luna
GPT-6 Luna
Grok 4.6
Grok 4.6Runner-up

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

GPT-6 Luna costs 12x 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
20× cheaper
Output
$0.50
12× cheaper
Grok 4.6
Input
$2.00
Output
$6.00

GPT-6 Luna is cheaper on both: 20× input, 12× 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
Grok 4.62 hosts
HostInOutContextUptime
xAI$2.00 in·$6.00 out·500k·99.6% upAmazon Bedrock$2.20 in·$6.60 out·500k·100% 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 Grok 4.6 is developed by xAI. GPT-6 Luna has a 1.1M token context window vs Grok 4.6's 500K. 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 Grok 4.6 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 Grok 4.6 costs $2/M input tokens. GPT-6 Luna is $1.90/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 Grok 4.6 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

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