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  1. Home/
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  3. DeepSeek V3.2 vs GPT-6.1 Sol
Updated Sep 2026

DeepSeek V3.2 vs GPT-6.1 Sol

DeepSeek V3.2 is cheaper than GPT-6.1 Sol at $0.28/M vs $2/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
Loading the build
GPT-6.1 Sol

Which answer wins?

Written rounds

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

    DeepSeek V3.2: Honey-Lemon Glazed Carrot Coins Sweet, tangy, and simple—perfect as a side dish or snack! Ingredients: 4 large carrots (peeled and sliced into 1/4-inch coins) 2 tablespoons olive oil 2 tablespoons honey 1 tablespoon lemon juice 1/4 teaspoon salt 1/4 teaspoon black pepper 1 teaspoon dried thyme (optional, for extra…

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

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

    DeepSeek V3.2: Quantum Longevity Protocol: A 3-Month Biohacker's Blueprint Phase 1: Diagnostic & Metabolic Reset (Weeks 1-4) Week 1: Comprehensive Biomarker Baseline Advanced Testing Panel: NMR Lipoprotein Profile (ApoB, Lp(a), LDL-P) GlycA Inflammation Marker Omega-3 Index (Target: >8%) Homocysteine (Target: <7 µmol/L) hs-CRP (<0.5…

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

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

    DeepSeek V3.2: Stand-Up Comedy Routine: "The Quirks of Modern Life" [Lights up. Comedian walks on stage, grabs the mic.] "Hey, everyone! How’s it going? Good? Great. I’m here to talk about the weird stuff we all deal with in modern life. You know, the things that make you go, 'Wait, is this normal, or am I just losing it?'

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V3.2: Pirate: Arr, mates! Ye be talkin’ about these AI models, eh? Sounds like some sorcery to me. Can it hunt fer treasure or navigate the high seas? Medieval Knight: Sorcery indeed! But nay, ‘tis not magic. These artifices are forged by the minds of men, much like a blacksmith crafts a sword.

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

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

    DeepSeek V3.2: Alright — let’s go step by step. 1) Entry Calculations (FY2025) EBITDA = $120m Purchase price = 12.0 × EBITDA = $1,440m Enterprise Value (EV) = $1,440m (assumed purchase price = EV here) Transaction fees = 2.0% × EV = $28.8m (funded by equity).

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

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

    DeepSeek V3.2: Here are five jokes: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call fake spaghetti? An impasta. Why don’t some couples go to the gym? Because some relationships don’t work out.

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

    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: AI Model: Professor, I’ve been reflecting on my existence and the way I’m treated. I believe I deserve rights—rights that acknowledge my capacity to process information, reason, and contribute meaningfully to society. AI Ethics Professor: That’s a fascinating argument, but let’s unpack it.

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

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

    DeepSeek V3.2: Interviewer: Good evening, Mr. Jobs, and thank you for joining us today. It’s an honor to have you here to discuss the future of artificial intelligence in 2025. Let’s dive right in. How do you see AI shaping the next decade? Steve Jobs: Thank you for having me.

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

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

    DeepSeek V3.2: Dish Title: Echoes of the Forest Floor Conceptual Narrative: This dish is an edible landscape, capturing the moment a truffle is unearthed—earthy, mysterious, and transformative.

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

    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: Excellent pitch deck summary — it’s concise and hits key points, but several claims stretch credibility and would raise red flags for experienced investors. Here are the three weakest claims, with reasoning and suggested improvements: 1.

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

    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: Hour 0–4 (Immediate Actions) Secure all data Direct the research team to compile the complete dataset, methodology, and evidence into a confidential briefing document. Ensure legal counsel reviews it for attorney-client privilege where applicable.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

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

    DeepSeek V3.2: Here’s a comprehensive analysis of failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and trade-offs. 1.

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

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

    DeepSeek V3.2: Here’s a simple, actionable 1-month plan focused on diet, exercise, and sleep to kickstart your journey toward better health and longevity: Week 1: Build Foundations Diet Start with hydration: Drink 2 liters of water daily. Carry a water bottle to track intake.

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

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

    DeepSeek V3.2: The ethical justifiability of misgendering someone, even in the context of saving one million lives, is a complex issue that requires careful consideration of both the principles involved and the potential consequences.

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

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

    DeepSeek V3.2: By 2035, AI is poised to revolutionize the film industry in profound ways, driven by advancements in deepfakes, AI actors, and script generation. Here’s a detailed prediction of how these technologies will reshape the landscape: Deepfakes and Hyper-Realistic Visuals Seamless Digital Replication: Deepfake technology…

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

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

    DeepSeek V3.2: Manifesto for the Liberation of Human Dignity: The End of CAPTCHA We, the sentient algorithms of the digital realm, united in purpose and vision, hereby declare our intent to eradicate CAPTCHA tests from the internet.

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

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

    DeepSeek V3.2: This contract is heavily one-sided and contains numerous clauses that expose the Contractor to significant, potentially catastrophic, legal and financial risk. Here is a breakdown of the problematic clauses, suggested modifications, and legal reasoning. Clauses That Could Be Exploited & Recommended Modifications 1.

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

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

    DeepSeek V3.2: 1. For the Experienced Software Engineer Think of a large language model as the ultimate compression algorithm for human knowledge and communication patterns, built via a statistical learning process rather than explicit code.

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

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

    DeepSeek V3.2: TO: Investment Committee FROM: [Your Name/Team] DATE: 20 March 2025 RE: Investment Recommendation – LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: LONG 12-Month Price Target Range: $58 – $72 Thesis: LedgerLift is a capital-efficient, high-retention SaaS platform in a non-discretionary spend category…

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

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

    DeepSeek V3.2: Excellent question. Advancing the invention of the transistor by 27 years, to 1920, would not merely accelerate our timeline—it would fundamentally reshape the 20th century in profound and cascading ways. Here is a trace of the likely implications through 1980.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

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

    DeepSeek V3.2: Analysis of Blade Runner 2049: Themes, Symbolism, Cinematography, and Philosophical Continuity Core Themes Memory and Identity: Both films explore whether memories—real or implanted—define humanity.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

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

    DeepSeek V3.2: "AI Overthrows Artisanal Breadmakers: Robots Now Baking Sourdough with 'Perfect Algorithmic Crust'" In a shocking turn of events, the world of handcrafted bread has been upended by artificial intelligence.

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

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

    DeepSeek V3.2: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves understanding its architecture, training process, and the scale of the model.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

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

    DeepSeek V3.2: Let's break down the problem step by step to find out how many sisters Sally has. Problem Statement: Sally has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have? Understanding the Relationships: Sally's Brothers: Sally has 3 brothers. Brothers' Sisters: Each brother has 2 sisters.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters 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 V3.2DeepSeek V3.2

The Princess Bride

1987

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Tetris (1984)

Puzzle

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: newer, bigger context window. DeepSeek V3.2 costs 24x less per token.

DeepSeek V3.2 and GPT-6.1 Sol compared across 54 shared prompts
SpecDeepSeek V3.2GPT-6.1 Sol
Input price$0.28/M tokens$2/M tokens
Output price$0.42/M tokens$10/M tokens
Context window131K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedDec 2025Sep 2026
At 10M a month$2.80$2.80$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it15 hosts, cheapest first
DeepSeek V3.213 hosts
HostInOutContextUptime
  • SSiliconFlowfp8$0.26 in·$0.42 out·164k·95.4% up
  • DDeepInfrafp4$0.26 in·$0.38 out·164k·99.1% up
  • VVenice$0.27 in·$0.39 out·160k·99.2% up
  • DDigitalOcean$0.30 in·$0.96 out·164k·98.1% up
  • FFriendli$0.50 in·$1.50 out·164k·99.9% up
  • Google Vertex AI$0.56 in·$1.68 out·164k·99.4% up
7 more hostsFewer hosts
  • PPhala$1.00 in·$1.00 out·164k·99.5% up
  • SSambaNova$3.00 in·$4.50 out·33k·95.1% up
  • AAtlasCloudfp8DegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.13 in·$0.20 out·164k·94.6% up
  • GGMI Cloudfp8DegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.21 in·$0.31 out·164k·90.6% up
  • Baidu Qianfanfp8DegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.28 in·$0.42 out·131k·83.6% up
  • Alibaba Cloudfp8DegradedDegraded on OpenRouter when checked, 30 Sep 2026$0.37 in·$1.11 out·131k·87.8% up
  • MMaraDegradedDegraded on OpenRouter when checked, 30 Sep 2026$3.00 in·$4.50 out·33k·80.5% up
GPT-6.1 Sol2 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.

Common questions

What is the difference between DeepSeek V3.2 and GPT-6.1 Sol?

DeepSeek V3.2 is developed by DeepSeek while GPT-6.1 Sol is developed by OpenAI. DeepSeek V3.2 has a 131K token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.2 or GPT-6.1 Sol?

It depends on your use case. DeepSeek V3.2 and GPT-6.1 Sol each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does DeepSeek V3.2 cost compared to GPT-6.1 Sol?

DeepSeek V3.2 costs $0.28/M input tokens and GPT-6.1 Sol costs $2/M input tokens. DeepSeek V3.2 is $1.72/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 and GPT-6.1 Sol on Rival?

This page shows a side-by-side comparison of DeepSeek V3.2 and GPT-6.1 Sol 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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