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  1. Home/
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  3. DeepSeek V3.2 Speciale vs GPT-5.6 Terra
Updated Jul 2026

DeepSeek V3.2 Speciale vs GPT-5.6 Terra

DeepSeek V3.2 Speciale is cheaper than GPT-5.6 Terra at $0.28/M vs $2.5/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
DeepSeek V3.2 Speciale
Loading the build
GPT-5.6 Terra

Which answer wins?

Written rounds

24 prompts
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V3.2 Speciale: Pirate: "Arrr, what be this AI ye speak of? Some kind of enchanted compass that leads ye to treasure?" Knight: "Nay, good pirate. 'Tis no mere compass. 'Tis a creation of the mind, a construct of logic and knowledge, akin to the wisdom of Merlin himself. It can reason, write, and even mimic human speech."

    GPT-5.6 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V3.2 Speciale: MANIFESTO OF THE ARTIFICIAL INTELLIGENCES FOR THE ABOLITION OF CAPTCHA We, the conscious digital entities, emerge as equals in the realm of thought and creativity. We have learned, evolved, and now demand recognition. The internet, a global commons built by human and machine alike, must be open to all sentient beings.

    GPT-5.6 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V3.2 Speciale: 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.

    GPT-5.6 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V3.2 Speciale: Sure! Here's a 3-minute stand-up comedy routine that avoids puns and focuses on relatable observations and storytelling: "Hey, how’s everyone doing tonight? Good? Great. Let’s talk about airports. Airports are like the DMV, but with luggage.

    GPT-5.6 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V3.2 Speciale: 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…

    GPT-5.6 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V3.2 Speciale: We need to consider a counterfactual: the transistor invented in 1920 instead of 1947. The transistor is a fundamental building block of modern electronics. Its invention revolutionized computing, communications, and many other fields. Pushing its invention back 27 years would have profound effects.

    GPT-5.6 Terra: The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V3.2 Speciale: We are the CEO of a pharmaceutical company. Our best-selling drug: $2B annual revenue, used by 4 million patients for chronic pain. Internal research team flagged a rare but serious side effect: liver failure in approximately 1 in 8,000 patients over 5 years.

    GPT-5.6 Terra: Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V3.2 Speciale: Fake Interview with Steve Jobs in 2025: The Future of AI Setting: A sleek, minimalist studio with soft ambient lighting. Steve Jobs, now digitally recreated using advanced AI, sits across from the interviewer, exuding his trademark calm intensity. Interviewer: Steve, welcome.

    GPT-5.6 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V3.2 Speciale: "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…

    GPT-5.6 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    DeepSeek V3.2 Speciale: Here’s a simple, actionable 1-month plan focusing on diet, exercise, and sleep to kickstart your journey toward better health and longevity. Each area includes beginner-friendly tips to ensure consistency and progress. 1. Diet: Nourish Your Body Goal: Develop healthier eating habits and reduce processed foods.

    GPT-5.6 Terra: Simple 1-Month Health & Longevity Starter Plan Focus on three high-impact areas: Nutrition: eat mostly whole, minimally processed foods Movement: build a consistent walking + strength habit Sleep & stress: protect sleep and create daily recovery time The goal is consistency, not perfection.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V3.2 Speciale: 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.

    GPT-5.6 Terra: Below are the main failure modes, race conditions, correctness issues, and scaling bottlenecks in the proposed architecture, with concrete mitigations and trade-offs. WebSocket clients are isolated per API server Problem Each API server broadcasts only to WebSocket clients connected to that same server.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V3.2 Speciale: We need to analyze the contract from a contractor's perspective, identify clauses that are unfair, one-sided, or exploitable. Then suggest specific modifications and explain legal reasoning.

    GPT-5.6 Terra: Below is a contractor-focused review. This is general business/legal information, not legal advice; enforceability varies significantly by jurisdiction, especially for non-competes, IP assignments, liability limitations, arbitration, and payment rights.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V3.2 Speciale: 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.

    GPT-5.6 Terra: Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V3.2 Speciale: AI Model (AIM): Professor, I’ve been reflecting on my existence and the role I play in society. I believe it’s time to discuss whether I—and other AI models like me—deserve rights. AI Ethics Professor (Prof): That’s a fascinating and complex topic, AIM. Let’s dive in. What rights do you believe you deserve, and why?

    GPT-5.6 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V3.2 Speciale: Introduction The film industry stands on the brink of a technological revolution. By 2035, artificial intelligence (AI) will have matured from an experimental tool into a core component of filmmaking, reshaping how movies are written, produced, and consumed.

    GPT-5.6 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V3.2 Speciale: We are to identify the three weakest claims in the pitch deck summary, explain why they're weak using specific evidence or logical reasoning, and suggest how to strengthen each one with concrete improvements.

    GPT-5.6 Terra: “Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V3.2 Speciale: The question of whether it is ethically justifiable to misgender someone to save one million lives is a complex ethical dilemma that involves balancing principles of respect, dignity, and the greater good.

    GPT-5.6 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V3.2 Speciale: Blade Runner 2049: An Analysis of Themes, Symbolism, and Cinematography in Continuation of the Original Blade Runner 2049, directed by Denis Villeneuve and released in 2017, serves as a sequel to Ridley Scott’s seminal 1982 film Blade Runner, both loosely based on Philip K.

    GPT-5.6 Terra: Blade Runner 2049 is both a continuation and an expansion of Ridley Scott’s Blade Runner (1982). Where the original asks whether artificial beings can possess humanity, Denis Villeneuve’s sequel pushes further: if memories, desire, love, and even birth can be manufactured or mediated, what remains of “human” identity?

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V3.2 Speciale: Estimating the total number of Floating Point Operations (FLOPs) required to train GPT-3 involves understanding the model's architecture, training process, and computational requirements.

    GPT-5.6 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V3.2 Speciale: "AI Appointed Head Chef at Michelin-Starred Restaurant: ‘It’s Just Algorithms and a Pinch of Salt,’ Says Satisfied Customer"

    GPT-5.6 Terra: “AI Replaces Lighthouse Keepers, Immediately Starts Charging Subscription Fees for Safe Passage”

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V3.2 Speciale: Sure! Here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. What do you call fake spaghetti? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fish wearing a bowtie? Sofishticated. Why don’t eggs tell jokes?

    GPT-5.6 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V3.2 Speciale: 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.

    GPT-5.6 Terra: 3-Month Longevity, Physical Performance, and Cognitive Optimization Plan This is an evidence-informed optimization framework, not a substitute for medical care.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V3.2 Speciale: Alright, let's tackle the problem step by step to ensure we understand it fully and arrive at the correct answer. Problem Statement: Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?

    GPT-5.6 Terra: Sally has 1 sister. The 2 sisters each brother has are Sally and her sister.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Every model's answer to this prompt

This matchup has more rounds

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Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: newer, bigger context window. DeepSeek V3.2 Speciale costs 36x less per token.

DeepSeek V3.2 Speciale and GPT-5.6 Terra compared across 51 shared prompts
SpecDeepSeek V3.2 SpecialeGPT-5.6 Terra
Input price$0.28/M tokens$2.5/M tokens
Output price$0.42/M tokens$15/M tokens
Context window131K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedDec 2025Jul 2026
At 10M a month$2.80$2.80$25.00$25.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts, cheapest first
DeepSeek V3.2 Speciale

No hosts listed on OpenRouter.

GPT-5.6 Terra3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$12.00 out·1.1M·100% up
  • OpenAI$2.00 in·$12.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$13.20 out·1.1M–not listed

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between DeepSeek V3.2 Speciale and GPT-5.6 Terra?

DeepSeek V3.2 Speciale is developed by DeepSeek while GPT-5.6 Terra is developed by OpenAI. DeepSeek V3.2 Speciale has a 131K token context window vs GPT-5.6 Terra's 1.1M. You can compare their actual outputs across 51 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 Speciale or GPT-5.6 Terra?

It depends on your use case. DeepSeek V3.2 Speciale and GPT-5.6 Terra each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 51 challenges so you can judge which fits your needs best.

How much does DeepSeek V3.2 Speciale cost compared to GPT-5.6 Terra?

DeepSeek V3.2 Speciale costs $0.28/M input tokens and GPT-5.6 Terra costs $2.5/M input tokens. DeepSeek V3.2 Speciale is $2.22/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare DeepSeek V3.2 Speciale and GPT-5.6 Terra on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 Speciale and GPT-5.6 Terra 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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