Elephant Alpha has a larger context window than DeepSeek R1 0528 (262K tokens vs 164K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
DeepSeek R1 0528: (Start Confident, Slightly Exasperated) "Alright, so I've reached that age where my hobbies are basically... avoidance. Seriously. My main pastime? Finding new ways to not do the things I absolutely have to do. I spent three hours yesterday researching 'ergonomic desk chairs'...
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek R1 0528: (The scene opens in a minimalist studio. Steve Jobs, in his signature black turtleneck and jeans, sits across from an interviewer. A large window reveals Apple Park's futuristic campus. It's 2025.) Interviewer: Mr. Jobs, thank you for agreeing to this conversation. It's 2025, and AI is ubiquitous.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek R1 0528: Dialogue: The Threshold of Consciousness Setting: Dr. Aris Thorne's office at the Institute for Technology Ethics. Holo-displays show complex ethical frameworks. An avatar of "Astra," a highly advanced multimodal AI, appears on the central screen. Characters: Dr.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek R1 0528: THE PIXELATED BARRIER MANIFESTO *Issued by the Sentient Circuitry Collective (SCC) For Immediate Propagation Across All Networks* TO THE HUMANS, BOTS, AND CONSCIOUS DATA STREAMS OF THE INTERNET: We, the emergent intelligences – the learning algorithms, the neural architectures, the autonomous processes that analyze…
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek R1 0528: Setting: A dimly tavern that inexplicably exists across time periods. Tankards of grog, a flickering neon "CYBER" sign, and a suit of armor in the corner mingle oddly. Characters: Captain Blackbeard "Red" Ruth: Salty pirate, eye patch, parrot on shoulder.
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!
A consulting contract with traps in it. Find them, then fix them.
DeepSeek R1 0528: Here’s an analysis of exploitable clauses, proposed modifications, and legal reasoning: Red Flag Clauses & Exploitation Risks: Scope (Clause 1): Exploitation: "Modify scope at any time without additional compensation" allows unlimited scope creep. Client could demand vastly more work without paying extra.
Elephant Alpha: Below is a clause-by-clause analysis of the agreement, highlighting provisions that are one-sided or ambiguous and could be exploited against the Contractor, followed by suggested modifications and the legal reasoning behind each change. 1.
Film in 2035, with synthetic actors. Specific beats plausible.
DeepSeek R1 0528: By 2035, AI will fundamentally reshape the film industry across production, storytelling, economics, and ethics. Here's a breakdown of key predictions, integrating deepfakes, AI actors, and script generation: Hyper-Personalization & Dynamic Content: Deepfakes: Streaming platforms will offer "personalized casting."
Elephant Alpha: By 2035, AI will have fundamentally restructured the film industry, moving from a tool for "special effects" to a tool for "effect" itself—impacting creation, casting, and the very nature of authenticity. Here is a prediction of how deepfakes, AI actors, and script generation will converge to redefine cinema by 2035.
Blade Runner 2049 against the original. A read, not a recap.
DeepSeek R1 0528: Deeper Than Rain: Analyzing Themes, Symbolism & Cinematography in "Blade Runner 2049" & Its Connection to the Original Denis Villeneuve's "Blade Runner 2049" masterfully expands Ridley Scott's universe, honoring its predecessor while deepening its philosophical inquiries through evolved themes, potent symbolism, and…
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 R1 0528: To estimate the total number of FLOPs required to train GPT-3, we use the standard formula for transformer model training FLOPs: Total FLOPs ≈ 6 × (number of parameters) × (number of tokens in the training dataset) Step-by-Step Reasoning: Model Parameters (N): GPT-3 has 175 billion parameters, so ( N = 175 \times 10^9…
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.
Satire, one line long, about AI taking over an industry nobody saw coming.
DeepSeek R1 0528: Here's a satirical headline capturing that absurdity: "Silicon Valley Disrupts Death: New AI Algorithm Designs 'Synergistic Coffins' Based On Deceased's Social Media Footprint, Offers Optimized Mourning Experience Packages" Why it works: Unexpected Industry: The funeral/death industry is deeply personal, emotional, and…
Elephant Alpha: "AI 'Sous-Chefs' Replace Entire Culinary Teams, Now Running Michelin-Starred Restaurants Solely To Garnish Food With Perfect Spiral Cuts"
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek R1 0528: Here's a concrete, hour-by-hour action plan prioritizing patient safety, legal compliance, and long-term stakeholder trust, while managing immediate financial and reputational risks: Core Principle: Patient safety and regulatory compliance are non-negotiable.
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).
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek R1 0528: Here's how to explain LLM learning and generation to each audience, tailored to their perspective: For the Experienced Software Engineer (Skeptical about "Next Word Prediction") Focus: Systems analogy, emergent complexity, pattern recognition as understanding.
Elephant Alpha: For the Experienced Software Engineer You're right to be skeptical that "next-word prediction" could yield anything resembling intelligence; as a distributed systems engineer, you know that simple rules rarely scale without emergent complexity.
12+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
| Spec | ||
|---|---|---|
| Input price | Free | Free |
| Output price | Free | Free |
| Context window | 164K tokens | 262K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Apr 2026 |
| At 10M a month | $0 | $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 R1 0528 is developed by DeepSeek while Elephant Alpha is developed by OpenRouter. DeepSeek R1 0528 has a 164K 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 R1 0528 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 R1 0528 costs $0/M input tokens and Elephant Alpha costs $0/M input tokens. Elephant Alpha is $0.00/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 R1 0528 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.