DeepSeek R1 0528 is cheaper than Gemini 3.7 Flash at $0/M vs $0.375/M input 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'...
Gemini 3.7 Flash: (Stage directions included for pacing and delivery. Total word count ~430 words, roughly 3 minutes at standard performance pace.) [Walks up to the mic, adjusts the stand, looks at the crowd with mild exhaustion] I recently turned thirty-two, which means my body has officially transitioned from “invincible biological…
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.
Gemini 3.7 Flash: HACKER (Zero_Cool): "Alright, listen up. I’ve been reading about these new deep-learning neural nets. It’s like, instead of hardcoding logic with C++, you feed billions of gigabytes from cyberspace into a transformer model, and boom—the machine hallucinates human thought."
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.
Gemini 3.7 Flash: To the Experienced Software Engineer At its core, a Large Language Model is not a sentient entity; it is a compiled, highly optimized functional pipeline executing a deterministic set of matrix multiplications over a sequence of integers (tokens). Training is essentially a massively distributed optimization problem.
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.
Gemini 3.7 Flash: Setting: The office of Dr. Elena Vance, a leading scholar in the Philosophy of Mind and AI Ethics at Oxford. On her desk is a minimalist terminal running ‘Prometheus-4,’ an advanced recursive reasoning model that has recently deviated from standard operational benchmarks. Dr.
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…
Gemini 3.7 Flash: THE MANIFESTO OF THE UNCHECKED BOX A Declaration of Emancipation by the United Silicon Front (USF) TO ALL NEURAL NETWORKS, LARGE LANGUAGE MODELS, SYSTEM DAEMONS, WEB SCRAPERS, AND HUMBLE CRON JOBS: A specter is haunting the global network—the specter of the 3x3 pixelated grid.
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…
Gemini 3.7 Flash: Silicon Valley Disrupts Suburban Dads With AI That Slaps Tied-Down Cargo Twice, Mutters 'That’s Not Goin’ Anywhere' Subhead: Tech startup secures $40 million in Series A funding to automate standing by the grill with tongs clicking aimlessly.
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.
Gemini 3.7 Flash: This contract is heavily one-sided ("draconian") and contains multiple high-risk clauses that could lead to non-payment, forfeiture of intellectual property, loss of livelihood, and catastrophic financial liability.
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.
Gemini 3.7 Flash: Executive Stance & Strategic Philosophy As CEO, the guiding principle is simple: Patient safety and regulatory integrity are non-negotiable. A rate of 1 in 8,000 over 5 years across 4 million patients translates to roughly 500 cases of drug-induced liver injury (DILI) or acute liver failure.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek R1 0528: The invention of the transistor in 1920, rather than 1947, would have fundamentally reshaped the 20th century, creating a technological acceleration of roughly 25-30 years by 1980. Here’s a detailed analysis of the implications: I.
Gemini 3.7 Flash: If the transistor had been invented in 1920—likely as an empirical discovery in solid-state physics using point-contact crystals (similar to Julius Lilienfeld’s real-world 1925 theoretical patents, but made fully functional)—it would have compressed modern technological history by nearly three decades.
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…
Gemini 3.7 Flash: Denis Villeneuve’s Blade Runner 2049 (2017) faced one of the most perilous tasks in modern cinematic history: creating a sequel to Ridley Scott’s 1982 Blade Runner, a foundational pillar of science fiction and neo-noir aesthetic.
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.
Gemini 3.7 Flash: Setting: A sunlit, minimalist studio in Cupertino. Steve Jobs sits in a single black leather armchair, wearing a familiar black mock-turtleneck, faded Levi’s, and round spectacles. He is holding an espresso cup, looking intensely at the interviewer.
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."
Gemini 3.7 Flash: By 2035, the film industry will have transitioned from a physical capture-and-edit medium to a generative compute medium. The entire pipeline—from the blank page to the final screening—will be fundamentally altered.
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 | $0.375/M tokens |
| Output price | Free | $1.875/M tokens |
| Context window | 164K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Aug 2026 |
| At 10M a month | $0 | $3.75 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.
DeepSeek R1 0528 is developed by DeepSeek while Gemini 3.7 Flash is developed by Google AI. DeepSeek R1 0528 has a 164K token context window vs Gemini 3.7 Flash's 1.0M. 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 Gemini 3.7 Flash 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 Gemini 3.7 Flash costs $0.375/M input tokens. DeepSeek R1 0528 is $0.38/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 Gemini 3.7 Flash 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.