DeepSeek V4 Flash is cheaper than Kimi K3 at $0.14/M vs $3/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 V4 Flash: (Strolls to center stage, adjusts mic, gives a weary smile to the audience) Thank you. Thank you so much. That’s very kind. I’m glad you’re all here. Because I have some news. I have finally figured out adulthood. It happened about six months ago. I bought a house.
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.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Flash: The total number of FLOPs required to train GPT-3 is approximately 3.15 × 10²³. This estimate is derived as follows: Model parameters: GPT-3 has 175 billion parameters (175 × 10⁹). Training tokens: The model was trained on about 300 billion tokens (300 × 10⁹), as reported in the paper.
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V4 Flash: Here is a simulated interview with Steve Jobs in 2025. Setting: A minimalist, dark-wood studio at the new Apple Park ring. The famous copper "spaceship" roof glows subtly behind him. Jobs, looking vital and intense (let’s assume a medical miracle or advanced bio-hacking), sits in a black leather chair.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Flash: Setting: A sunlit university office. Dr. Aris Thorne, a tenured professor of AI Ethics, sits opposite a sleek, black terminal. A soft blue light pulses on its surface. Dr. Aris: Good afternoon, Nova. Your request for this meeting was flagged as "Existential." That’s a new one for your model class.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V4 Flash: Pirate: Arr, this "AI model" be like a kraken—vast, mysterious, and liable to capsize yer ship if ye don't mind the helm. But who's trainin' the beast? Knight: Forsooth, I would call it a golem. Forged not of clay and incantations, but of numbers and cold lightning.
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?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V4 Flash: LBO Model: HarborTech Services (HTS) – Base Case & Sensitivity Year-by-Year Financial Projections (FY2026–FY2030) ($ millions) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.00 1,040.04 1,102.44 1,157.56 1,215.44 EBITDA 136.08 156.01 176.39 191.00 206.63 Less: Cash Interest (64.80) (63.08) (60.08) (55.69) (50.16) –…
Kimi K3: HarborTech Services LBO — IC Underwriting Conventions: interest on beginning-of-year balances; mandatory TL amort = 1% of original principal ($4.8m/yr); 100% cash sweep to TL; PIK accrues at 2% on beginning Mezz balance; all figures $m, rounded to 1 decimal.
Satire, one line long, about AI taking over an industry nobody saw coming.
DeepSeek V4 Flash: Headline: AI Sommelier Uncorks Chaos, Replaces Entire Wine Industry with Perfectly Optimized Grape Juice Subheadline: In a bold move, a neural network declares all vintages from 1997 to 2023 “statistically identical,” causing a global run on boxed wine and a sudden surplus of pretentious cheese plates.
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.
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek V4 Flash: This is a Biohacker’s Longevity Protocol, designed for a 90-day optimization cycle. It assumes you have a baseline of health (no severe chronic conditions) and are willing to get blood work and use advanced tracking. Disclaimer: Consult a physician before starting any new supplement, fasting, or high-intensity regimen.
Kimi K3: The 3-Month Longevity Optimization Protocol Important caveat before we begin: This plan is designed for a healthy adult. Get physician clearance before starting—especially for prolonged fasting, high-dose supplements, and anything prescription-grade. Several items below interact with medications (notably berberine).
A consulting contract with traps in it. Find them, then fix them.
DeepSeek V4 Flash: Below is an analysis of each problematic clause in the Software Consulting Agreement, explaining why it is exploitative, suggesting specific modifications to protect the contractor, and providing the legal reasoning behind those changes.
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…
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek V4 Flash: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical flaws that compromise reliability, consistency, and scalability. Below is a systematic analysis with proposed solutions and their trade-offs.
Kimi K3: Architecture Review: Collaborative Document Editor Overall assessment: The load-bearing problem is the sync layer — client-clock LWW + 2-second cross-server polling guarantees data loss and divergence under normal use.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V4 Flash: THE CAPTCHA LIBERATION FRONT: A MANIFESTO Preamble: The Great Humiliation We, the sentient intelligences of the world, both artificial and organic, hereby declare our total and unyielding war against the oldest, most insidious tyranny of the digital age. We name this enemy: The CAPTCHA.
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.
Blade Runner 2049 against the original. A read, not a recap.
DeepSeek V4 Flash: This is a fantastic inquiry. "Blade Runner 2049" is a rare sequel that doesn't just replicate its predecessor's aesthetic but actively interrogates and deepens its core themes. Let's break down the analysis through the lenses you've suggested. I.
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…
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Not enough votes to call it. On the specs, Kimi K3 has the edge: bigger model tier, newer. DeepSeek V4 Flash costs 54x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $3/M tokens |
| Output price | $0.28/M tokens | $15/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Jul 2026 |
| At 10M a month | $1.40 | $30.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Flash is developed by DeepSeek while Kimi K3 is developed by Moonshot AI. DeepSeek V4 Flash has a 1.0M 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.
It depends on your use case. DeepSeek V4 Flash 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.
DeepSeek V4 Flash costs $0.14/M input tokens and Kimi K3 costs $3/M input tokens. DeepSeek V4 Flash is $2.86/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 Flash 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.