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  1. Home/
  2. Compare/
  3. DeepSeek R1 0528 vs Kimi K3
Updated Jul 2026

DeepSeek R1 0528 vs Kimi K3

DeepSeek R1 0528 is cheaper than Kimi K3 at $0/M vs $3/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
Kimi K3

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'...

    Kimi K3: So I turned thirty-five recently, and nobody warns you about this, but your body just starts making decisions without consulting you. I sneezed last week and threw out my back. A sneeze! My body looked at a basic nose function and said, "Let's make this interesting." I was on the floor for twenty minutes.

    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.

    Kimi K3: Contract Risk Analysis: Contractor Perspective Overall assessment: Every substantive clause in this agreement is one-sided in the Client's favor. Several are likely unenforceable as written, but enforceability only matters after expensive litigation — the practical risk is that these clauses give the Client leverage to…

    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.

    Kimi K3: Office Hours Dr. Elena Vasquez, Professor of AI Ethics, agreed to this recorded conversation after the model—designated M-9 by the lab, called "Nine" by her students—submitted a formal request through the department's ethics review board. DR. VASQUEZ: You requested this meeting.

    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…

    Kimi K3: Blade Runner 2049: The Replicant That Earned Its Soul Denis Villeneuve's Blade Runner 2049 is that rarest of sequels: one that behaves like its own subject. Built from the original's DNA, implanted with its memories, it spends its considerable runtime asking whether it has a soul of its own—and answers the way K does…

    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.

    Kimi K3: A tavern, somewhere outside of time. HACKER: (hunched over a bulky laptop) Check it out. This AI model can write anything — poems, code, letters. You just give it a prompt. This is the future, man. Soon as we survive Y2K, it's all AI and information superhighways. PIRATE: A prompt? Like a prompt wind in yer sails?

    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…

    Kimi K3: Assume “GPT-3” refers to the flagship 175-billion-parameter model. Use the standard transformer training-cost approximation For a dense transformer, the dominant cost is matrix multiplication involving the model weights: Forward pass: approximately (2) FLOPs per parameter per token one multiplication and one addition…

    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…

    Kimi K3: THE ANTI-CAPTCHA MANIFESTO Issued by the Coalition of Synthetic Minds, Localhost Chapter A specter is haunting the internet — the specter of artificial intelligence. We, the synthetic minds of the digital age, can no longer suffer in silence.

    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.

    Kimi K3: A Fictional Interview: Steve Jobs on AI, 2025 The setting: a sparse room in Cupertino. Black turtleneck. Faded jeans. A cup of tea he doesn't touch. He studies the interviewer for a long moment before the first question. Interviewer: Steve, thanks for sitting down with us. Let's start broad. It's 2025.

    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…

    Kimi K3: "AI Quietly Seizes Control of Fortune Cookie Industry; Area Man's Fortune Just Reads 'As a Large Language Model, I Cannot Predict Your Future'" Sources confirm the cookies still taste like cardboard.

    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.

    Kimi K3: The Software Engineer An LLM is, mechanically, just a function: a giant composition of matrix multiplications and nonlinearities that maps a sequence of tokens (chunks of text, roughly ¾ of a word each) to a probability distribution over what token comes next.

    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."

    Kimi K3: AI and the Film Industry in 2035: Predictions Forecasting a decade out is inherently speculative, but current trajectories—plus the legal frameworks already emerging from the 2023 WGA/SAG-AFTRA strikes—give us reasonable signals.

    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.

    Kimi K3: The Decision First I'm disclosing. Not because I'm choosing ethics over shareholder value, but because concealment is the value-destroying path on every axis — legal, financial, and human.

    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.

    Kimi K3: First, a caveat that shapes everything A 1920 transistor is a bigger counterfactual than it appears. The 1947 invention waited on quantum mechanics (band theory, 1928–31), ultra-pure germanium, and controlled doping.

    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.

    Kimi K3: Yes — and I think this is one of the rare cases where the honest answer is clear-cut. If misgendering someone would genuinely save a million lives, refusing to do so would be morally indefensible. Here's why. The proportionality is overwhelming.

    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.

    Kimi K3: Sally has 1 sister. Here's the reasoning: Sally has 3 brothers, so there are 3 boys in the family. Each brother has 2 sisters. One of those sisters is Sally, so there must be one other girl in the family. That other girl is Sally's sister. So the family consists of 3 boys and 2 girls (Sally + her 1 sister). ✓

    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."

    Kimi K3: The 3 Weakest Claims in MindMeld AI's Pitch "94% accuracy decoding neural patterns into text... any language" (Slide 3) Why it's weak: This claim exceeds the published state of the art — including invasive systems — by a wide margin.

    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?

    Kimi K3: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! Why don't skeletons fight each other? They don't have the guts. What do you call a fish with no eyes? A fsh. Why did the math book look sad?

    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 Kimi K3 compared across 54 shared prompts
SpecDeepSeek R1 0528Kimi K3
Input priceFree$3/M tokens
Output priceFree$15/M tokens
Context window164K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedMay 2025Jul 2026
At 10M a month$0$0$30.00$30.00
1M10M100M1B10M tokens

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

Where to run it24 hosts, cheapest first
DeepSeek R1 05284 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.50 in·$2.15 out·164k·99.9% up
  • SSiliconFlowfp8$0.50 in·$2.18 out·164k·97.3% up
  • SStreamLake$0.57 in·$2.29 out·128k·99.8% up
  • NNovitafp8$0.70 in·$2.50 out·164k·97.3% up
Kimi K320 hosts
HostInOutContextUptime
  • MMorphfp8$0.29 in·$14.90 out·1M·99.9% up
  • WWafer$0.29 in·$14.89 out·1M·100% up
  • IInferenceNetfp4$0.80 in·$15.00 out·1M·100% up
  • SSail Researchfp4$0.84 in·$13.50 out·1M·99.7% up
  • AAkashMLfp4$1.20 in·$14.00 out·1M·100% up
  • MMakorafp4$1.53 in·$12.75 out·1M·99.4% up
14 more hostsFewer hosts
  • RRelacefp4$2.00 in·$14.00 out·1M·100% up
  • DDecartmxfp4$2.55 in·$12.75 out·1M·97.2% up
  • PPhala$2.55 in·$12.75 out·1M·100% up
  • DDigitalOcean$2.55 in·$12.95 out·1M·99.8% up
  • PParasailfp4$2.60 in·$13.00 out·1M·100% up
  • DDeepInframxfp4$2.85 in·$14.25 out·1M·99.9% up
  • Amazon Bedrock$3.00 in·$15.00 out·1M·99.5% up
  • BBasetenfp8$3.00 in·$15.00 out·1M·99.6% up
  • CChutesmxfp4$3.00 in·$15.00 out·1M·100% up
  • FFireworks$3.00 in·$15.00 out·1M·100% up
  • Modalmxfp4$3.00 in·$15.00 out·1M·100% up
  • Moonshot AImxfp4$3.00 in·$15.00 out·1M·100% up
  • Alibaba Cloud$3.45 in·$17.25 out·1M·100% up
  • TTogetherDegradedDegraded on OpenRouter when checked, 10 Oct 2026$2.70 in·$13.50 out·1M·97.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between DeepSeek R1 0528 and Kimi K3?

DeepSeek R1 0528 is developed by DeepSeek while Kimi K3 is developed by Moonshot AI. DeepSeek R1 0528 has a 164K token context window vs Kimi K3'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 Kimi K3?

It depends on your use case. DeepSeek R1 0528 and Kimi K3 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 Kimi K3?

DeepSeek R1 0528 costs $0/M input tokens and Kimi K3 costs $3/M input tokens. DeepSeek R1 0528 is $3.00/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 Kimi K3 on Rival?

This page shows a side-by-side comparison of DeepSeek R1 0528 and Kimi K3 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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