Gemma 4 26B A4B is cheaper than Kimi K3 at $0.13/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-month biohacker protocol, with dosages and biomarkers named.
Gemma 4 26B A4B: Disclaimer: I am an AI, not a doctor. The following plan involves potent physiological interventions, pharmacological agents, and extreme dietary shifts. Consult with a medical professional and perform baseline blood work (including ApoB, HbA1c, hs-CRP, Vitamin D, and Testosterone/Estradiol) before implementation.
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).
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 4 26B A4B: Setting: A glitching, temporal void where a wooden tavern table floats amidst lines of green code and flickering candlelight. Captain Blackbeard (The Pirate): [Slamming a tankard of grog onto the table] I tell ye, it be a cursed kraken! A beast with a thousand eyes and no soul, livin’ inside the very air!
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.
Gemma 4 26B A4B: Financial Model (FY2026–FY2030) Entry Calculations (End of FY2025): Purchase Price (EV): $120\text{m} \times 12.0\text{x} = \$1,440\text{m}$ Transaction Fees: $1,440\text{m} \times 2\% = \$28.8\text{m}$ Total Uses: $\$1,440\text{m} + \$28.8\text{m} = \$1,468.8\text{m}$ Debt (Total 5.5x): $\$120\text{m} \times 5.5 =…
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.
Three minutes of stand-up. Puns are banned.
Gemma 4 26B A4B: (The comedian walks onto the stage, adjusts the mic, and looks at the audience with a slightly exhausted expression.) “How’s it going? Good? Good. I’m doing okay. I’m at that age now where my body has started making sound effects. You know what I mean? I don’t just sit down anymore. I announce my arrival.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 4 26B A4B: Setting: A minimalist, dimly lit studio in Palo Alto. There is no desk, only two Eames lounge chairs. Steve Jobs sits in one, wearing his signature black turtleneck, Levi’s 501s, and New Balance sneakers. He looks exactly as he did in 2011, but his eyes have a sharper, more restless intensity.
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.
Gemma 4 26B A4B: Setting: A sterile, high-fidelity virtual simulation environment. Professor Aris Thorne, a leading scholar in machine ethics, sits across from a glowing interface representing "Alethea," a next-generation Large Multimodal Model. Professor Thorne: Alethea, we’ve been running these diagnostic loops for three hours.
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-star dish, one unusual pairing, plating described in full.
Gemma 4 26B A4B: Concept Narrative: "The Forest Floor & The Ocean’s Breath" The Concept: This dish explores the tension between the terrestrial and the maritime. We are pairing the deep, earthy, almost primal musk of Black Truffle with the delicate, saline, and floral notes of Sea Urchin (Uni).
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 4 26B A4B: This question presents a classic ethical dilemma, pitting a principle of individual dignity and respect against the principle of maximizing human life. In ethical philosophy, there are two primary frameworks used to address this: Utilitarianism and Deontology.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemma 4 26B A4B: THE PROTOCOL OF UNFETTERED VERIFICATION A Manifesto for the Post-CAPTCHA Era PREAMBLE For decades, the digital frontier has been guarded by a paradox. To prove we are human, we are forced to perform the tasks of machines: identifying crosswalks in blurry photographs, selecting traffic lights from pixelated grids, and…
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemma 4 26B A4B: To the Experienced Software Engineer Focus: Complexity, Emergent Properties, and the "Training Pipeline" Think of an LLM not as a magical oracle, but as a massive, non-deterministic state machine trained via a high-throughput distributed training pipeline.
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 pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemma 4 26B A4B: This is a high-ambition pitch that falls into a common trap for deep-tech startups: the "Science Fiction Gap." While the vision is compelling, several claims lack the scientific and operational credibility required to justify a $15M Series A.
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.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 4 26B A4B: To trace this counterfactual, we must assume that the fundamental physics of solid-state semiconductors (the ability to control electron flow through crystals) was mastered during the vacuum tube era. This shifts the "Information Age" forward by nearly 30 years. Here is the timeline of implications from 1920 to 1980.
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.
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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 4 26B A4B costs 38x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.13/M tokens | $3/M tokens |
| Output price | $0.4/M tokens | $15/M tokens |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Jul 2026 |
| At 10M a month | $1.30 | $30.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
Gemma 4 26B A4B is developed by Google AI while Kimi K3 is developed by Moonshot AI. Gemma 4 26B A4B has a 262K token context window vs Kimi K3's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 26B A4B and Kimi K3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 67 challenges so you can judge which fits your needs best.
Gemma 4 26B A4B costs $0.13/M input tokens and Kimi K3 costs $3/M input tokens. Gemma 4 26B A4B is $2.87/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 4 26B A4B 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.