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  5. DeepSeek V3.2 SpecialevsGPT-6 Luna Pro
Updated Sep 2026

DeepSeek V3.2 SpecialevsGPT-6 Luna Pro

GPT-6 Luna Pro is cheaper than DeepSeek V3.2 Speciale at $0.1/M vs $0.28/M input tokens.

DeepSeek V3.2 Speciale and GPT-6 Luna Pro compared across 17 shared prompts
SpecDeepSeek V3.2 SpecialeGPT-6 Luna Pro
Input price$0.28/M tokens$0.1/M tokens
Output price$0.42/M tokens$0.5/M tokens
Context window131K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedDec 2025Sep 2026
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…

DeepSeek V3.2 Speciale170 words
"Honey-Lemon Bliss Bites" A sweet, tangy, and chewy treat that’s quick to make with pantry staples! Ingredients: 1 cup rolled oats 1/4 cup honey 2 tbsp peanut butter (or any nut/seed butter) 1 tbsp lemon zest (or 1 tsp lemon juice) 1/4 tsp vanilla extract 1/4 cup shredded coconut (optional, for coating) A pinch of salt…
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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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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…

DeepSeek V3.2 Speciale1,373 words
Dish Name: Squab, Black Garlic, White Chocolate Espuma, and Sour Cherry Gastrique Conceptual Narrative This dish is a celebration of contrasts, where the deep, fermented sweetness of black garlic meets the delicate creaminess of white chocolate, both complementing the rich, gamey notes of perfectly cooked squab.
Read the full answer
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

Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

DeepSeek V3.2 Speciale2,085 words
3-Month Longevity Optimization Plan for the Advanced Biohacker Introduction This plan integrates cutting‑edge nutrition, supplementation, exercise, recovery, stress management, sleep optimization, and data‑driven feedback to maximize healthspan, lifespan, physical performance, and cognitive function.
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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…
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…

DeepSeek V3.2 Speciale2,320 words
We need to generate three explanations for how a large language model learns and generates text, each tailored to a different audience: experienced software engineer (no ML), PhD physicist (mathematical precision), and venture capitalist (business evaluation). Each explanation should be 2-3 paragraphs.
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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.
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…

DeepSeek V3.2 Speciale7,492 words
We need to analyze the given architecture for a real-time collaborative document editor, similar to Google Docs. The description includes components, data flow, sync strategy, and scaling plan. We are asked to identify potential failure modes, race conditions, and scaling bottlenecks.
Read the full answer
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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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…

DeepSeek V3.2 Speciale1,916 words
We need to write an internal investment committee memo for a long/short equity fund. The company is LedgerLift (LLLT). We have data and valuation assumptions. We need to produce a recommendation with price target range, business overview, KPI quality check, base/bull/bear DCF model, comps cross-check, catalysts, risks…
Read the full answer
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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Our Verdict
GPT-6 Luna Pro
GPT-6 Luna Pro
DeepSeek V3.2 Speciale
DeepSeek V3.2 SpecialeRunner-up

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

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V3.2 Speciale
Input
$0.28
Output
$0.42
1.2× cheaper
GPT-6 Luna Pro
Input
$0.10
2.8× cheaper
Output
$0.50

GPT-6 Luna Pro wins input (2.8× cheaper)·DeepSeek V3.2 Speciale wins output (1.2× cheaper)

Where to run it

2 hosts

DeepSeek V3.2 Speciale

No hosts listed on OpenRouter.

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

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

DeepSeek V3.2 Speciale is developed by DeepSeek while GPT-6 Luna Pro is developed by OpenAI. DeepSeek V3.2 Speciale has a 131K token context window vs GPT-6 Luna Pro's 1.1M. You can compare their actual outputs across 17 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek V3.2 Speciale and GPT-6 Luna Pro 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.

DeepSeek V3.2 Speciale costs $0.28/M input tokens and GPT-6 Luna Pro costs $0.1/M input tokens. GPT-6 Luna Pro is $0.18/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 DeepSeek V3.2 Speciale and GPT-6 Luna Pro 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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DeepSeek V3.2 Speciale55 outputs, specs and price
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