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  1. Home/
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  3. DeepSeek R1 0528 vs Gemini 3.7 Flash
Updated Aug 2026

DeepSeek R1 0528 vs Gemini 3.7 Flash

DeepSeek R1 0528 is cheaper than Gemini 3.7 Flash at $0/M vs $0.375/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
DeepSeek R1 0528
Loading the build
Gemini 3.7 Flash

Which answer wins?

Written rounds

24 prompts
  • 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…

    Every model's answer to this prompt
  • 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."

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • 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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek R1 0528: No, it is not ethically justifiable to deliberately misgender someone, even to save one million lives. Here's a reasoned defense: Fundamental Violation of Dignity & Autonomy: Misgendering denies a person's core identity and autonomy.

    Gemini 3.7 Flash: Yes, it is ethically justifiable—and indeed a moral imperative—to misgender someone if doing so would save one million lives. Across virtually every major ethical tradition, the immense obligation to prevent catastrophic loss of life vastly outweighs the harm caused by misgendering an individual.

    Every model's answer to this prompt
  • 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…

    Gemini 3.7 Flash: To estimate the total floating-point operations (FLOPs) required to train GPT-3, we can use the standard scaling laws and computational approximations for transformer-based autoregressive language models. 1.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    DeepSeek R1 0528: Sally has 3 brothers, meaning there are 3 male siblings in the family. Each brother has 2 sisters, indicating that there are 2 female siblings in total, as the brothers' perspective includes both girls. Since Sally is one of the girls, there is one other sister. Therefore, from Sally's perspective, she has 1 sister.

    Gemini 3.7 Flash: Sally has 1 sister. Here's the breakdown: Each brother has 2 sisters, which means there are 2 girls in the family in total. Since Sally is one of those girls, the other girl is her sister.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    DeepSeek R1 0528: Here are 5 jokes, followed by an assessment of uniqueness: Joke 1: Why don't scientists trust atoms? Because they make up everything! Joke 2: What do you call a fake noodle? An impasta! Joke 3: Why did the scarecrow win an award? Because he was outstanding in his field! Joke 4: Why don't skeletons fight each other?

    Gemini 3.7 Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How does a penguin build its house? Igloos it together. Why did the bicycle fall over? Because it was two-tired.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek R1 0528: Here are the 3 weakest claims in the MindMeld AI pitch deck, why they are weak, and how to strengthen them: Weak Claim (Slide 3): "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."

    Gemini 3.7 Flash: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with an evaluation of why they undermine credibility and how to fix them. The Technical Feasibility Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Every model's answer to this prompt

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Price and specs

DeepSeek R1 0528 and Gemini 3.7 Flash compared across 54 shared prompts
SpecDeepSeek R1 0528Gemini 3.7 Flash
Input priceFree$0.375/M tokens
Output priceFree$1.875/M tokens
Context window164K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedMay 2025Aug 2026
At 10M a month$0$0$3.75$3.75
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it6 hosts, cheapest first
DeepSeek R1 05284 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.50 in·$2.15 out·164k·100% up
  • SSiliconFlowfp8$0.50 in·$2.18 out·164k·99.6% up
  • SStreamLake$0.57 in·$2.29 out·128k·99.2% up
  • NNovitafp8$0.70 in·$2.50 out·164k·99.7% up
Gemini 3.7 Flash2 hosts
HostInOutContextUptime
  • Google Vertex AI$0.38 in·$1.88 out·1M·99.4% up
  • Google AI Studio$0.75 in·$3.75 out·1M·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.

Common questions

What is the difference between DeepSeek R1 0528 and Gemini 3.7 Flash?

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.

Which is better, DeepSeek R1 0528 or Gemini 3.7 Flash?

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.

How much does DeepSeek R1 0528 cost compared to Gemini 3.7 Flash?

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.

How can I compare DeepSeek R1 0528 and Gemini 3.7 Flash on Rival?

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.

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