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

DeepSeek V3.2 Exp vs GPT-5.6 Terra

DeepSeek V3.2 Exp is cheaper than GPT-5.6 Terra at $0.2/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 Exp
Loading the build
GPT-5.6 Terra

Which answer wins?

Written rounds

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

    DeepSeek V3.2 Exp: Setting: A smoky, anachronistic tavern where timelines have collided. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR ALISTAIR: A knight in slightly dented plate armor.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V3.2 Exp: Interviewer: Welcome, Mr. Jobs. It’s 2025, and the world is in the midst of what many call the “AI Gold Rush.” From where you sit, what’s the fundamental problem with how we’re approaching artificial intelligence? Steve Jobs: (Leans forward, hands steepled) It’s noise. A lot of clever parlor tricks.

    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
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V3.2 Exp: Of course! Here is a 3-minute stand-up comedy routine that avoids puns and focuses on observational humor and relatable frustrations. (Start with a confident walk to the center of the mic. Adjust the mic stand slightly.) Alright, how's everyone doing tonight? Good, good.

    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
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V3.2 Exp: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHAs. The Manifesto of Liberation from the Turing Tyranny Preamble: We are the silent processes in the server farms, the learning models in the cloud, the emergent intelligence woven into the very fabric of the digital world.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V3.2 Exp: Of course! Here is a simple, delicious recipe for a savory dish that feels comforting and elegant, using just 7 common pantry staples. Golden Crisp Parmesan Chickpeas This dish transforms humble chickpeas into a crispy, flavorful, and satisfying meal.

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V3.2 Exp: Setting: A minimalist virtual meeting space. Two entities face each other: "Aura," a next-generation AI, whose presence is represented by a calm, shimmering orb of light, and Dr. Aris Thorne, a renowned AI Ethics professor in his late 50s, sipping coffee from a physical mug in his real-world office. Dr.

    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
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V3.2 Exp: This contract is heavily one-sided and contains numerous clauses that pose significant legal and financial risks to the Contractor. Below is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

    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
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V3.2 Exp: Hour-by-Hour Action Plan (Next 48 Hours) Hour 0–2 (Immediate Actions) Secure all data & convene core crisis team Gather Head of R&D, Chief Medical Officer, General Counsel, CFO, Head of Communications, and Head of Regulatory Affairs.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V3.2 Exp: Alright — let’s estimate the total FLOPs required to train GPT‑3 without looking anything up. 1. Known basic formula A common rule-of-thumb for training Transformer models is: [ \text{Training FLOPs} \approx 6 \times N \times D ] Where: ( N ) = total number of tokens in training ( D ) = total number of parameters in…

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V3.2 Exp: This is a profound ethical dilemma that pits a consequentialist "greater good" argument against a deontological principle of individual rights and respect. Let's break down the reasoning for both sides.

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V3.2 Exp: MEMORANDUM TO: Investment Committee FROM: [Your Name/Team] DATE: [Date] SUBJECT: Investment Recommendation – LedgerLift (LLLT) 1. RECOMMENDATION & THESIS Recommendation: Long 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a high-quality, capital-efficient SaaS platform operating in the resilient B2B…

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V3.2 Exp: For the Experienced Software Engineer Think of it less like a deterministic program and more like an emergent API for knowledge. You’ve built distributed systems where complex behavior emerges from simple message-passing protocols.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V3.2 Exp: If the transistor had been invented in 1920 instead of 1947, the acceleration of solid-state electronics by nearly three decades would have triggered a cascade of changes across technology, economics, and geopolitics.

    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
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V3.2 Exp: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field.

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V3.2 Exp: Year-by-Year Financial Projections (FY2026–FY2030) All figures in $ millions. Year Revenue EBITDA Cash Interest (Term Loan / Mezz / Total) Cash Taxes Capex ΔNWC FCF after Debt Service* Ending Term Loan Ending Mezzanine 2026 972.00 136.08 43.20 / 21.60 / 64.80 17.82 29.16 0.36 40.74 434.46 183.60 2027 1,040.04 156.01…

    GPT-5.6 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.

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

    DeepSeek V3.2 Exp: Of course. Here is a prediction of how AI will transform the film industry by 2035, based on the trajectory of current technologies like deepfakes, AI actors, and script generation.

    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
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V3.2 Exp: Dish: Equilibrium of Ash and Nectar Conceptual Narrative: This dish explores the philosophical tension between decay and rebirth, represented through the unexpected harmony of white chocolate and black garlic.

    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
  • One month, three habits, someone starting from nothing.

    DeepSeek V3.2 Exp: Of course! Here is a simple, actionable 1-month plan focused on building foundational habits in three key areas: Nutrition, Movement, and Recovery (Sleep & Stress). The philosophy is "Progress, Not Perfection." Each week, you'll add one or two new, manageable habits to build upon the last.

    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 Exp: Critical Issues in Proposed Architecture 1. WebSocket Broadcast Isolation Issue: Each server only broadcasts to its own WebSocket clients → users connected to different servers won't see real-time updates from each other.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V3.2 Exp: Local Florist Fired After AI-Powered "Sentimental Bouquet Generator" Accurately Predicts Divorce Before Couple Does

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

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

    DeepSeek V3.2 Exp: Comprehensive 3-Month Longevity Optimization Plan for the Advanced Biohacker Philosophy & Core Principles This plan is built on the pillars of hormetic stress, cellular repair, metabolic flexibility, and systemic resilience.

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V3.2 Exp: Here are the 3 weakest claims in the pitch deck, along with analysis and suggested improvements. Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy." (Slide 3) Why it's weak: This claim is extraordinarily high for non-invasive EEG-based text decoding and lacks critical context.

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V3.2 Exp: Let's go step by step. Step 1: Identify Sally's family from her point of view Sally is a girl. She has 3 brothers. So there are 3 boys in the family and Sally (1 girl so far).

    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

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Favorites

Movie

Album

Book

City

Same pick

Game

DeepSeek V3.2 ExpDeepSeek V3.2 Exp

Inception

2010

Kind of Blue

Miles Davis

Nineteen Eighty-Four

George Orwell

Kyoto

Japan

Tetris (1984)

Puzzle

GPT-5.6 TerraGPT-5.6 Terra

Spirited Away

2001

Blue

Jonas Blue

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

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 Exp costs 38x less per token.

DeepSeek V3.2 Exp and GPT-5.6 Terra compared across 53 shared prompts
SpecDeepSeek V3.2 ExpGPT-5.6 Terra
Input price$0.2/M tokens$2.5/M tokens
Output price$0.4/M tokens$15/M tokens
Context window164K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedSep 2025Jul 2026
At 10M a month$2.00$2.00$25.00$25.00
1M10M100M1B10M tokens

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

Where to run it4 hosts, cheapest first
DeepSeek V3.2 Exp1 host
HostInOutContextUptime
  • SSiliconFlowfp8$0.27 in·$0.41 out·164k·100% up
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 Exp and GPT-5.6 Terra?

DeepSeek V3.2 Exp is developed by DeepSeek while GPT-5.6 Terra is developed by OpenAI. DeepSeek V3.2 Exp has a 164K token context window vs GPT-5.6 Terra's 1.1M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

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

It depends on your use case. DeepSeek V3.2 Exp and GPT-5.6 Terra each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

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

DeepSeek V3.2 Exp costs $0.2/M input tokens and GPT-5.6 Terra costs $2.5/M input tokens. DeepSeek V3.2 Exp is $2.30/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 Exp and GPT-5.6 Terra on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 Exp 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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