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  5. GPT-6 Luna ProvsMistral Large 2
Updated Sep 2026

GPT-6 Luna ProvsMistral Large 2

GPT-6 Luna Pro is cheaper than Mistral Large 2 at $0.1/M vs $8/M input tokens.

GPT-6 Luna Pro and Mistral Large 2 compared across 17 shared prompts
SpecGPT-6 Luna ProMistral Large 2
Input price$0.1/M tokens$8/M tokens
Output price$0.5/M tokens$24/M tokens
Context window1.1M tokens128K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2024
Side by side

Same prompt, both answers

Opening lines from 6 of the 17 prompts both answered. Formatting stripped, words untouched.

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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Mistral Large 2344 words
Here’s a simple, delicious, and creative savory dish using just 7 common pantry ingredients—no fresh produce required! "Golden Crispy Chickpea & Tomato Skillet" A warm, spiced, and satisfying one-pan dish with crispy chickpeas, tangy tomatoes, and a hint of smoky sweetness. Perfect as a side, snack, or light meal!
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.
Read the full answer
Mistral Large 21,368 words
Michelin 3-Star Dish: "Ocean’s Whisper & Forest’s Breath" Conceptual Narrative: This dish is a poetic dialogue between two seemingly disparate ecosystems—the ocean’s depths and the forest floor—united through texture, temperature, and memory.
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 Luna Pro892 words
For an experienced software engineer Think of a language model as a system trained to continue sequences: given a prefix of text, it assigns probabilities to possible next tokens (tokens are pieces of words, not necessarily whole words) and learns to make the observed continuation likely.
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Mistral Large 21,223 words
1. For the Experienced Software Engineer (Skeptical, Systems-Minded, Non-ML Background) You’re right to be skeptical—"predicting the next word" sounds trivial, like autocomplete on steroids. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is trained.
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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 Luna Pro327 words
A simple 1-month plan for better health and longevity Choose three foundations: eating well, moving regularly, and sleeping consistently. Aim for steady habits, not perfection. Diet: Make nourishing choices easier Week 1: Add one serving of fruit or vegetables to one meal each day.
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Mistral Large 21,076 words
Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress management). Each week builds on the last, with small, sustainable changes.
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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Mistral Large 21,132 words
Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.
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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 Luna Pro1,661 words
The biggest change would not be that 1920 suddenly gets modern computers. It would be that governments and firms have six or seven extra decades to develop semiconductor materials, manufacturing, and applications.
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Mistral Large 22,069 words
The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have triggered a cascade of technological, economic, and geopolitical shifts with profound second- and third-order effects. Below is a detailed exploration of these implications through 1980, structured by domain.
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Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
Mistral Large 2
Mistral Large 2Runner-up

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

GPT-6 Luna Pro costs 48x 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 Pro
Input
$0.10
80× cheaper
Output
$0.50
48× cheaper
Mistral Large 2
Input
$8.00
Output
$24.00

GPT-6 Luna Pro is cheaper on both: 80× input, 48× output.

Where to run it

3 hosts

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
Mistral Large 21 host
HostInOutContextUptime
Mistral$2.00 in·$6.00 out·131k·99.8% 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 Pro is developed by OpenAI while Mistral Large 2 is developed by Mistral AI. GPT-6 Luna Pro has a 1.1M token context window vs Mistral Large 2's 128K. You can compare their actual outputs across 17 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-6 Luna Pro and Mistral Large 2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 17 challenges so you can judge which fits your needs best.

GPT-6 Luna Pro costs $0.1/M input tokens and Mistral Large 2 costs $8/M input tokens. GPT-6 Luna Pro is $7.90/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 Pro and Mistral Large 2 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 Pro logo
GPT-6 Luna Pro20 outputs, specs and price
Mistral Large 2 logo
Mistral Large 223 outputs, specs and price
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