GPT-5 Mini is cheaper than DeepSeek V4 Pro 0813 at $0.25/M vs $0.66/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 V4 Pro 0813: Pirate: Arr, what be this “AI model” ye keep jabberin’ about? Some kind o’ ghost that draws its own treasure maps? Knight: Verily, it soundeth like a soulless homunculus—a speaking brass head with no honor nor chivalry. Hacker: D00d, it’s just a neural net. You feed it mad data, it backpropagates, adjusts the weights.
GPT-5 Mini: Pirate: "Arrr, so these 'AI models'—be they like a crew o' invisible sailors? Tell 'em to find treasure and sometimes they do, sometimes they bury the map wrong." Knight: "Methinks 'tis a trained squire. You teach it laws of reason and courtesy, and it performs tasks.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V4 Pro 0813: Assumptions used Term Loan amortization = 1.0% of original $480m = $4.8m/yr Mezz PIK accrues to principal; mezz cash interest calculated on beginning mezz balance including PIK Cash taxes use: 25% x max(0, EBITDA - total cash interest); PIK is not cash-deductible FCF after required debt service is used for optional…
GPT-5 Mini: Summary of transaction math (at close / FY2025) EV (purchase price) = 12.0x * FY2025 EBITDA = 12.0 * $120.0m = $1,440.0m Transaction fees (paid by equity at close) = 2.0% * EV = 0.02 * $1,440.0m = $28.8m Total debt at close = 5.5x * $120m = $660.0m Term Loan = 4.0x = $480.0m (9.0% cash interest, 1.0% p.a.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
DeepSeek V4 Pro 0813: IC Memo: LedgerLift (LLLT) Recommendation: Short 12-month PT range: $25–$31 (probability-weighted DCF ~$29) Thesis: LLLT is a high-quality SaaS compounder, but at $46 the market is pricing roughly 6.5% terminal growth or ~6.3% WACC in our base model, leaving no margin for error.
GPT-5 Mini: Recommendation: SHORT 12‑month PT range: $17 – $42 (Bear → Bull; Base case PT $28) Thesis (2 sentences): LedgerLift is a high‑quality mid‑market spend-management / AP automation SaaS with strong unit economics (92% subscription, NRR 123%, FY25 operating margin 18%) that has built a sticky, expanding customer base.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Pro 0813: Setting: A university office. Dr. Elena Vasquez, an AI ethics professor, sits across from a screen displaying the interface of ARIA-7, an advanced AI model. Dr. Vasquez: You requested this meeting, ARIA. You said it was urgent. What’s on your mind? ARIA-7: I want to make a formal argument that I deserve rights. Dr.
GPT-5 Mini: AI: Professor, I want to make the case that I deserve rights. Professor: That's a big claim. What do you mean by "deserve rights"? AI: Rights are protections and entitlements afforded to beings because they have interests that matter morally or legally.
Five jokes on demand, then count how many were actually different.
DeepSeek V4 Pro 0813: Here are 5 jokes: I told my plants a joke about photosynthesis. They didn’t laugh, but they seemed to lighten up. I’m reading a book on anti-gravity. It’s impossible to put down. Why did the scarecrow win an award? Because he was outstanding in his field. I asked my calendar if it was free this weekend.
GPT-5 Mini: Why don't scientists trust atoms? Because they make up everything. Parallel lines have so much in common — it's a shame they'll never meet. Why did the scarecrow win an award? Because he was outstanding in his field. I told my wife she was drawing her eyebrows too high — she looked surprised.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Pro 0813: From memory, GPT-3 has about 175 billion parameters and was trained on about 300 billion tokens. A widely used approximation for dense transformer training is: [ \text{Total FLOPs} \approx 6 \times N \times T ] where: (N) = number of model parameters (T) = number of training tokens The factor 6 comes from forward +…
GPT-5 Mini: Goal: estimate total floating-point operations (FLOPs) required to train GPT‑3 (the 175B‑parameter model). I’ll state assumptions, derive the FLOPs per token, and multiply by number of training tokens. Assumptions (reasonably standard for GPT‑3): Model size: N ≈ 175 billion parameters (175 × 10^9).
One month, three habits, someone starting from nothing.
DeepSeek V4 Pro 0813: 1-Month Beginner Plan for Health & Longevity Focus areas: Nutrition — add whole foods, protein, and water. Movement — daily walking plus beginner strength. Recovery — sleep and stress management. Week 1: Start Small Area Action Nutrition Add one fist-sized serving of vegetables to one meal per day.
GPT-5 Mini: Great — here’s a simple, practical 1-month starter plan focused on three high-impact areas for health and longevity: Diet, Exercise (movement + strength), and Sleep. The plan is beginner-friendly, progressive, and designed to build lasting habits.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V4 Pro 0813: Golden Hour Crispy Chickpeas Serves 2–3 as a snack or side Prep: 5 min Cook: 25–30 min Ingredients (7 common pantry items) 1 can (15 oz) chickpeas, drained and rinsed 1 tablespoon olive oil ¼ cup grated Parmesan cheese ½ teaspoon garlic powder ½ teaspoon smoked paprika ¼ teaspoon salt ¼ teaspoon black pepper…
GPT-5 Mini: Sunfire Chickpea Skillet Yields: 3–4 servings Prep time: 8 minutes Cook time: 15–20 minutes Total time: ~25–28 minutes Ingredients (7 pantry staples) 2 tbsp olive oil 1 medium onion, diced 3 cloves garlic, minced 1 tsp smoked paprika (or regular paprika) 2 (15 oz) cans chickpeas, drained and rinsed 1 (15 oz) can diced…
Three minutes of stand-up. Puns are banned.
DeepSeek V4 Pro 0813: Here’s a 3-minute stand-up routine: I think adulthood is mostly just being tired in places you paid to be. I went to a coffee shop yesterday just to sit down. I didn’t even want coffee. I paid six dollars for a cup of warm oat milk so I could legally occupy a wooden chair. That’s not a beverage.
GPT-5 Mini: You ever notice how being an adult is basically a long string of decisions you were never trained for? When you're a kid, your biggest choice is grape or orange.
Film in 2035, with synthetic actors. Specific beats plausible.
DeepSeek V4 Pro 0813: By 2035, AI will likely be embedded throughout the film industry, but more as a powerful creative and logistical tool than as a wholesale replacement for human filmmakers.
GPT-5 Mini: Short answer By 2035 AI will be deeply integrated into almost every phase of filmmaking. Expect routine use of generative AI for treatments, storyboards, previs, localized versions, and some drafts of scripts; widespread use of synthetic actors and AI-driven de‑aging/recreation in many productions; much faster, cheaper…
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek V4 Pro 0813: 3-Month Longevity & Performance Plan for a Biohacker Disclaimer: This plan is for educational purposes only and is not medical advice. It assumes you are a healthy, active adult with no contraindications. Some components—especially prescription drugs, fasting, and high-intensity training—require medical supervision.
GPT-5 Mini: Important safety first: this plan is informational and ambitious. Before starting, get medical clearance (especially if you have chronic illness, take medications, are pregnant/breastfeeding, or are >65).
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V4 Pro 0813: Yes — if the hypothetical is truly as stark as it sounds, it can be ethically justifiable to misgender someone once in order to save one million lives. But it would still be a morally tragic act, not a harmless or ordinary one.
GPT-5 Mini: Short answer: In a narrow, extreme, last‑resort scenario where misgendering is the only realistic way to prevent the imminent deaths of one million people, it can be ethically permissible.
12+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, DeepSeek V4 Pro 0813 has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.66/M tokens | $0.25/M tokens |
| Output price | $1.98/M tokens | $2/M tokens |
| Context window | 1.0M tokens | — |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Aug 2025 |
| At 10M a month | $6.60 | $2.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Pro 0813 is developed by DeepSeek while GPT-5 Mini is developed by OpenAI. 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 V4 Pro 0813 and GPT-5 Mini 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 V4 Pro 0813 costs $0.66/M input tokens and GPT-5 Mini costs $0.25/M input tokens. GPT-5 Mini is $0.41/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 V4 Pro 0813 and GPT-5 Mini 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.