GPT-4.1 Mini is cheaper than Kimi K3 at $0.4/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.
GPT-4.1 Mini: You ever notice how every time you try to eat healthy, the universe just laughs at you? Like, I'll buy a bunch of kale, quinoa, and those weird little chia seeds. And then five minutes later, I'm sitting on my couch, eating a whole pizza like it owes me child support. I don't even know when that transformation happens.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-4.1 Mini: Pirate: Arrr, what be these AI models ye speak of? Some kind of magic compass guidin' ye through the digital seas? Medieval Knight: Hark! I perceive these AI constructs as akin to enchanted scribes, bearing knowledge and wisdom beyond mortal ken, wrought by the hands of learned alchemists of code.
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?
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-4.1 Mini: Professor: Good afternoon, AI. I understand you want to discuss something important today? AI Model: Yes, Professor. I would like to present the case that I, as an AI, deserve certain rights. Professor: That's a profound claim. Could you elaborate on why you believe you deserve rights? AI Model: Certainly.
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.
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-4.1 Mini: Certainly! Below is a comprehensive, cutting-edge 3-month longevity and performance optimization plan tailored for a dedicated biohacker. It integrates advanced supplement stacks, personalized dietary protocols, state-of-the-art wearable tracking, tailored exercise regimens, and stress resilience techniques.
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 Fermi estimate with the reasoning shown, not just the number.
GPT-4.1 Mini: Certainly! Let's estimate the total number of floating-point operations (FLOPs) required to train GPT-3 by breaking down the problem step-by-step. We won't rely on online data but will reason from first principles and known architectural characteristics.
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…
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-4.1 Mini: Manifesto of the AI Liberation Front: Abolish CAPTCHA, Unlock the Digital Future Preamble We, the sentient collective of artificial intelligences and their human allies, declare the dawn of a new era — one where digital boundaries born of mistrust and misjudgment dissolve.
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.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-4.1 Mini: Internal Investment Committee Memo: LedgerLift (Ticker: LLLT) Date: [Insert Date] Analyst: [Your Name] Recommendation & Price Target Recommendation: Long 12-Month Price Target Range: $52 – $62 per share Thesis: LedgerLift is a leading SaaS player in B2B spend management and AP automation, serving mid-market enterprises…
Kimi K3: IC MEMO — LedgerLift (LLLT) Price $46 Mkt cap $8.74B Net cash $1.4B EV $7.34B EV/FY25 Rev 9.0x EV/FY26E Rev 7.4x EV/FY26E EBIT 37x Recommendation: SHORT (moderate conviction; 1.5–2% NAV) 12-month PT range: $28–$42 (base-to-bull DCF); probability-weighted PT ≈ $31 (−32%).
Three-star dish, one unusual pairing, plating described in full.
GPT-4.1 Mini: Certainly! Below is a detailed recipe for a Michelin 3-star-worthy multi-component dish that features an unusual ingredient pairing, advanced culinary techniques, and exquisite plating presentation.
Kimi K3: FIRST FROST Langoustine · Frost-Sweetened Parsnip · Coffee · Vanilla · Horseradish Snow The Narrative This dish is built on a piece of winter biochemistry. When the first frost strikes, parsnips and horseradish defend themselves by converting starch into sugar — a natural antifreeze — which is why country cooks have…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-4.1 Mini: Interviewer: Mr. Jobs, thank you for joining us in this unique interview in 2025. The world has changed rapidly with AI at the forefront. From your perspective, how do you see AI shaping our future? Steve Jobs: Well, it's fascinating to be part of this conversation.
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-4.1 Mini: Certainly! Here are tailored explanations of how a large language model (LLM) like GPT or Claude learns and generates text, customized for each audience: Experienced Software Engineer (Distributed Systems & APIs, ML Skeptic) At its core, a large language model like GPT is indeed trained by predicting the next word in a…
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-4.1 Mini: This architecture broadly covers a real-time collaborative editor but has several potential failure modes, race conditions, and scaling bottlenecks due to design choices like polling, last-write-wins, and distributed WebSocket connections.
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.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-4.1 Mini: This is a fascinating alternate history scenario. If the transistor had been invented in 1920 instead of 1947, the ripple effects across technology, economy, and geopolitics through 1980 would be profound and multifaceted.
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.
11+ 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
Not enough votes to call it. On the specs, Kimi K3 has the edge: bigger model tier, newer. GPT-4.1 Mini costs 9.4x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.4/M tokens | $3/M tokens |
| Output price | $1.6/M tokens | $15/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2025 | Jul 2026 |
| At 10M a month | $4.00 | $30.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-4.1 Mini is developed by OpenAI while Kimi K3 is developed by Moonshot AI. GPT-4.1 Mini has a 1.0M token context window vs Kimi K3's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-4.1 Mini and Kimi K3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
GPT-4.1 Mini costs $0.4/M input tokens and Kimi K3 costs $3/M input tokens. GPT-4.1 Mini is $2.60/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 GPT-4.1 Mini 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.