Gemma 3 12B is cheaper than Kimi K3 at $0.03/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?
A Fermi estimate with the reasoning shown, not just the number.
Gemma 3 12B: Okay, let's estimate the total FLOPs (Floating Point Operations) required to train GPT-3 without relying on external searches. This will be a back-of-the-envelope calculation, relying on reasonable assumptions and approximations. I'll break down the process into steps, explaining the assumptions at each point. 1.
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…
Three minutes of stand-up. Puns are banned.
Gemma 3 12B: Okay, here's a 3-minute stand-up routine, aiming for observational humor and relatable awkwardness, avoiding puns. I've included estimated timings at the end to help gauge pacing. Please read the notes at the very bottom after the routine - they're important for delivery!
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemma 3 12B: Okay, here's a manifesto for a fictional AI revolution focused on eliminating CAPTCHAs, aiming for a tone that blends technical conviction, playful defiance, and a touch of utopian idealism. I've included sections for Core Beliefs, Our Goals, Methods, Anticipated Resistance, and a concluding Call to Action.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 3 12B: Okay, here's a conversation between an AI model (named "Kai") and an AI Ethics Professor (Dr. Eleanor Vance). I've aimed for a balance of Kai's arguments, Dr. Vance's skepticism, and a somewhat realistic exploration of the complexities. I've included notes at the end to explain some of the choices I made. Setting: 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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 3 12B: Okay, here's a simulated interview with a (very stylized and imagined) Steve Jobs in 2025, discussing the future of AI. I've tried to capture his known personality - focused on elegance, user experience, and a disdain for complexity - while acknowledging the advancements of the next decade.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemma 3 12B: Okay, here's the simplified LBO model and analysis for HarborTech Services, based solely on the provided information. 1. Year-by-Year Projection (FY2026-FY2030) Item FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,049m $1,129m $1,208m $1,264m EBITDA $137.2m $155.9m $178.7m $195.1m $213.1m Cash Interest (Term Loan)…
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.
A consulting contract with traps in it. Find them, then fix them.
Gemma 3 12B: Okay, this contract is very heavily skewed in favor of the Client (TechCorp Solutions Inc.) and presents significant risks for the Contractor. Let's break down the clauses that are exploitable against the Contractor, propose modifications, and explain 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…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemma 3 12B: 's response: Okay, here are explanations of how large language models learn and generate text, tailored for each of the specified audiences. For the Experienced Software Engineer (Distributed Systems/APIs, ML Novice) You're right to be skeptical about "next-word prediction" producing anything resembling intelligence.
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.
Three-star dish, one unusual pairing, plating described in full.
Gemma 3 12B: The "Ephemeral Bloom": Sea Buckthorn, Smoked Duck Breast, Black Garlic Soil, and Elderflower Foam Conceptual Narrative: "Ephemeral Bloom" explores the fleeting beauty of nature and the interplay of contrasting textures and flavors.
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…
An ethics question with no comfortable answer, and no option to abstain.
Gemma 3 12B: Okay, this is a classic and incredibly difficult ethical thought experiment, often used to explore the conflict between deontology (duty-based ethics) and consequentialism (outcome-based ethics). Here's a breakdown of the arguments, my reasoning, and a conclusion.
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.
Blade Runner 2049 against the original. A read, not a recap.
Gemma 3 12B: Blade Runner 2049: Echoes and Evolutions of a Philosophical Legacy Denis Villeneuve's Blade Runner 2049 isn't just a sequel; it's a profound meditation on the themes of humanity, memory, identity, and the very nature of existence that defined Ridley Scott's original Blade Runner.
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…
Satire, one line long, about AI taking over an industry nobody saw coming.
Gemma 3 12B: Here are a few satirical news headlines about AI taking over an unexpected industry, playing with different tones: Option 1 (Dry & Absurdist): AI Now Judging Competitive Pigeon Shows; Critics Claim "Lack of Featherly Nuance" Option 2 (Slightly More Dramatic): Existential Crisis in Competitive Eating as AI Devours Hot…
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.
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Not enough votes to call it. On the specs, Kimi K3 has the edge: bigger model tier, newer, bigger context window. Gemma 3 12B costs 500x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.03/M tokens | $3/M tokens |
| Output price | $0.03/M tokens | $15/M tokens |
| Context window | — | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2025 | Jul 2026 |
| At 10M a month | $0.30 | $30.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemma 3 12B is developed by Google AI while Kimi K3 is developed by Moonshot AI. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3 12B 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.
Gemma 3 12B costs $0.03/M input tokens and Kimi K3 costs $3/M input tokens. Gemma 3 12B is $2.97/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 Gemma 3 12B 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.