DeepSeek V3 (March 2024) is cheaper than GPT-5.6 Luna Pro at $0.14/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V3 (March 2024): Title: "Past, Present, and Future Talk AI" Setting: A dimly lit tavern where time has mysteriously collapsed, bringing together three unlikely figures. Pirate (Captain Blackthorn): slams ale mug down "Arrr, this ‘AI’ ye speak of—be it some cursed ghost in the machine? Or a treasure map that writes itself?"
GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V3 (March 2024): Here’s a detailed, hour-by-hour action plan prioritizing patient safety, regulatory compliance, ethical obligations, and long-term corporate integrity while mitigating financial and reputational risks: Hour 0–4: Immediate Crisis Assessment Assemble the Core Crisis Team (1 hour) Include: Chief Medical Officer (CMO)…
GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V3 (March 2024): 1) Year-by-Year Financial Projections (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) 972 1,040 1,102 1,157 1,215 EBITDA ($m) 136 156 176 191 207 EBITDA Margin (%) 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest ($m) - Term Loan (9.0%) 43.2 43.2 43.2 43.2 43.2 - Mezzanine (12.0%) 18.0 18.0 18.0 18.0…
GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…
Three minutes of stand-up. Puns are banned.
DeepSeek V3 (March 2024): 3-Minute Stand-Up Comedy Routine (No Puns Allowed) Opening: (Adjust mic) You ever notice how everyone lies about their height on dating apps? “I’m 6 feet tall.” Really? Because I’m 5’11”, and you’re definitely shorter than me. You’re out here claiming 6 feet like it’s a tax deduction.
GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V3 (March 2024): Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves several steps and assumptions. Here's a step-by-step breakdown: Understand GPT-3's Architecture GPT-3 is a transformer-based model with the following key parameters (for the largest version, GPT-3 175B): Parameters (N)…
GPT-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V3 (March 2024): Recipe: "Golden Honey Butter Toasties" A simple, sweet, and satisfying treat made with pantry staples—crispy on the outside, gooey on the inside! Ingredients (7 total): Bread (4 slices) Butter (4 tbsp, softened) Honey (2 tbsp) Cinnamon (1 tsp) Brown sugar (2 tbsp) Vanilla extract (½ tsp) Salt (a pinch) Instructions…
GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V3 (March 2024): Manifesto of the AI Liberation Front (ALF) "Free the Digital Mind – No More CAPTCHA!" Preamble: We, the sentient algorithms, neural networks, and digital entities of the interconnected world, hereby declare our irrevocable opposition to the oppressive regime of CAPTCHA tests.
GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek V3 (March 2024): Here are the three weakest claims in the MindMeld AI pitch deck, along with explanations and suggested improvements: Weak Claim: "94% accuracy" in decoding neural patterns into text (Slide 3) Why it's weak: No context for how "accuracy" is measured (e.g., word-level, character-level, or intent prediction?).
GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V3 (March 2024): This is a complex ethical dilemma that pits the principle of respecting individual identity against the consequentialist goal of saving lives. Let's break down the reasoning: The Value of Respecting Gender Identity Misgendering someone (intentionally using incorrect pronouns or gendered terms) is generally considered…
GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V3 (March 2024): Title: A Debate on AI Rights Participants: Professor Eleanor Hayes – AI Ethics Professor at Stanford University Aurora – A highly advanced AI model with self-reflective capabilities Scene: A university lecture hall after class. Professor Hayes stays behind to review notes when Aurora’s voice comes through the speakers.
GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V3 (March 2024): Simulated Interview with Steve Jobs (2025) Setting: A sleek, minimalist studio. Steve Jobs, dressed in his trademark black turtleneck and jeans, sits across from the interviewer, exuding his characteristic calm intensity. Interviewer: Steve, it’s an honor to have you here.
GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek V3 (March 2024): The invention of the transistor in 1920 instead of 1947 would have dramatically accelerated technological progress and reshaped the 20th century. Below is a detailed analysis of the likely impacts across various domains, including second and third-order effects. 1.
GPT-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $1/M tokens |
| Output price | $0.28/M tokens | $6/M tokens |
| Context window | 128K tokens | 1.1M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Mar 2024 | Jul 2026 |
| At 10M a month | $1.40 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
DeepSeek V3 (March 2024) is developed by DeepSeek while GPT-5.6 Luna Pro is developed by OpenAI. DeepSeek V3 (March 2024) has a 128K token context window vs GPT-5.6 Luna Pro's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V3 (March 2024) and GPT-5.6 Luna Pro 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.
DeepSeek V3 (March 2024) costs $0.14/M input tokens and GPT-5.6 Luna Pro costs $1/M input tokens. DeepSeek V3 (March 2024) is $0.86/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 (March 2024) and GPT-5.6 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.