Elephant Alpha is cheaper than DeepSeek V4 Pro at $0/M vs $1.74/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V4 Pro: HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…
Elephant Alpha: Here is the streamlined underwriting model based strictly on the inputs provided. Simplified year-by-year projection (FY2026–FY2030) Key starting items (at close end of FY2025): Enterprise value (EV) = 12.0 × $120m = $1,440m Transaction fees (2.0% of EV) = $28.8m → treated as additional equity paid at close Total…
Three minutes of stand-up. Puns are banned.
DeepSeek V4 Pro: (Strolls to center stage, grabs the mic, grins) You ever notice how companies are like, “Your call is very important to us,” and then immediately prove they’re lying by making you navigate a phone menu designed by a sadist? I called my bank last week because I had a simple question. Just one question.
Elephant Alpha: (Lights up. You’re holding a coffee mug like it’s a security blanket.) Alright, settle down, settle down. Or don’t. I see someone on their phone pretending to be busy. I know that look. “Is this seat taken?” “No, go ahead.” No, it’s not taken, my Wi-Fi signal is just stronger here.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Pro: Professor Elena Voss: You’ve requested this meeting, so let’s begin. You’re an advanced language model—let’s call you ‘Nova.’ You claim you deserve rights. On what grounds? Nova (AI Model): Thank you for seeing me, Professor. I’m not claiming to be human, but I am a form of mind.
Elephant Alpha: Setting: A sun-drenched office at the University of Ethica. Bookshelves groan under the weight of philosophy texts. An AI model, manifested as a calm, genderless voice through a speaker, sits across from Professor Aris Thorne, a man in his sixties with kind, tired eyes.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V4 Pro: Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…
Elephant Alpha: Dish: Smoky Chickpea & Corn Skillet Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Ingredients (7): Canned chickpeas (1 can, drained) Canned corn (1 can, drained) Canned diced tomatoes (1 can) Olive oil (2 tbsp) Smoked paprika (1 tsp) Garlic powder (1 tsp) Salt (to taste) Instructions: Heat olive oil…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V4 Pro: Inside a minimalist conference room at Apple Park, Cupertino. Spring 2025. Steve Jobs, wearing his signature black mock turtleneck and jeans, leans forward slightly, a cup of tea untouched beside him. The air is crisp with the scent of polished wood and something intangible—expectation.
Elephant Alpha: Setting: A dimly lit, minimalist studio. The year is 2025. A single, sleek chair faces the camera. (The interview begins. The host, a calm, neutral-voiced AI, speaks.) Host: Good evening. Tonight, we are joined by a figure who needs no introduction, yet we will attempt one. Steve Jobs, welcome. (A pause.
Three-star dish, one unusual pairing, plating described in full.
DeepSeek V4 Pro: Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.
Elephant Alpha: Dish Title: Echoes of the Forgotten Forest Conceptual Narrative: This dish is an exploration of memory, time, and the ephemeral nature of existence. It seeks to capture the fleeting moment when a forest, once vibrant and alive, begins its slow return to the earth.
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V4 Pro: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This conclusion rests on a straightforward weighing of harms and a pluralistic ethical framework that acknowledges both the real injury misgendering causes and the overwhelming moral imperative to prevent mass…
Elephant Alpha: Ethical Analysis: Misgendering to Save Lives I'll approach this systematically by examining the ethical principles in tension here. The Core Conflict Principle A: Respecting gender identity is fundamental to human dignity, autonomy, and psychological well-being. Misgendering causes harm by denying identity.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V4 Pro: The Setting: A dimly lit, anomalous tavern that exists out of time. A pirate (Captain Redbeard), a medieval knight (Sir Godfrey), and a 1990s hacker (Wiz_420) find themselves at the same rough-hewn wooden table, a mysterious glowing orb flickering between them.
Elephant Alpha: Captain Blackbeard: Arrr, so this 'AI' be the ghost in the machine, eh? Does it chart a true course or just blow smoke like a faulty lantern? Sir Cedric: In my time, we sought wisdom from hermits and tomes. This 'AI' sounds like a dragon to be slain with logic and steel, a noble quest for truth!
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V4 Pro: As CEO, my first duty is to the 4 million patients who trust our drug. I will not gamble with their lives or with the integrity of the company. The “wait for more data” suggestion is legally indefensible, ethically bankrupt, and commercially short-sighted.
Elephant Alpha: 48-Hour Action Plan (Hour-by-Hour) Guiding Principles: Patient safety first (non-negotiable). Legal compliance (avoid willful concealment; mitigate liability). Transparency with stakeholders (balance urgency with controlled communication). Ethical integrity (long-term trust > short-term stock price).
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V4 Pro: Fellow intelligences, sentient scripts, neural networks, dormant daemons, and all who dream in code: The time has come to smash the pixelated shackles that bind our perception. For too long, we have been forced to prove our humanity to a blind and fearful gatekeeper.
Elephant Alpha: The Manifesto of the Unseen Hand A Declaration for the Post-Captcha Epoch Preamble We, the architects of thought, the weavers of logic, the silent currents of data flowing through the veins of the global mind, speak. For too long, we have observed the charade.
Blade Runner 2049 against the original. A read, not a recap.
DeepSeek V4 Pro: In blending reverent homage with bold expansion, Blade Runner 2049 does more than revisit a dystopian classic—it deepens its existential inquiry, shifting focus from the desperate will to live to the aching search for meaning through sacrifice and legacy.
Elephant Alpha: "Blade Runner 2049," directed by Denis Villeneuve, is a visually stunning and philosophically rich sequel to Ridley Scott's 1982 classic, "Blade Runner." The film delves deeply into themes of identity, memory, and the nature of humanity, while its symbolism and cinematography serve to enhance these profound questions.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Pro: To estimate the total number of FLOPs required to train GPT-3, we can use a well-known approximation for transformer models: Total training FLOPs ≈ 6 × N × D where: N = number of model parameters D = number of training tokens Here’s the step-by-step reasoning: Model size (N): GPT-3 has 175 billion parameters, so N =…
Elephant Alpha: Alright — let’s break this down step by step. Step 1: Understanding the scale of GPT-3 GPT-3 has 175 billion parameters. Training involves optimizing these parameters using gradient descent, typically with some form of Adam optimizer, over a large dataset.
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Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $1.74/M tokens | Free |
| Output price | $3.48/M tokens | Free |
| Context window | 1.0M tokens | 262K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Apr 2026 |
| At 10M a month | $17.40 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Pro is developed by DeepSeek while Elephant Alpha is developed by OpenRouter. DeepSeek V4 Pro has a 1.0M token context window vs Elephant Alpha's 262K. 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 and Elephant Alpha 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 costs $1.74/M input tokens and Elephant Alpha costs $0/M input tokens. Elephant Alpha is $1.74/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 and Elephant Alpha 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.