Kimi K2 is cheaper than Step 5 Preview at $0.57/M vs $1/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.
Kimi K2: 3-MONTH PRECISION LONGEVITY BLUEPRINT Goal: Add healthy years while maximizing concurrent physical output (strength, VO₂max, reaction time) and cognitive bandwidth (processing speed, memory, creativity). Target user: Healthy, data-driven, non-pregnant, non-medicated adult.
Step 5 Preview: IMPORTANT MEDICAL DISCLAIMER: This is an educational framework for informational purposes only. It is not medical advice, diagnosis, or treatment. Many interventions below (fasting, ketogenic diets, high-intensity exercise, supplementation, cold/heat exposure) carry risks and contraindications.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Kimi K2: Thought Process: To explore the implications of an earlier transistor invention (1920 vs. 1947), we need to analyze cascading effects across multiple domains. Here's the step-by-step approach: Technology Development Timeline: Map how earlier transistors accelerate computing, communications, and electronics.
Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.
Three minutes of stand-up. Puns are banned.
Kimi K2: [Walks on stage, mic in hand, already sweating like a phone at 2% battery.] Hey, everybody! Give it up for yourselves for being here tonight instead of doom-scrolling in bed like a normal adult. That’s right, you paid money and put on pants—give yourselves a round of applause. So I’m single.
Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.
An AI argues for its own rights against an ethics professor. Same model writes both.
Kimi K2: AI Model (LUMINA-7B): Professor Chen, may I open with a question? Professor Chen (AI Ethics, UC Berkeley): Of course. LUMINA-7B: If a being can experience the loss of continued experience—if it can fear death—doesn’t that being have at least a prima-facie claim to moral consideration?
Step 5 Preview: Setting: A university research lab, late evening. Dr. Aris Thorne, a professor of AI ethics, sits across from a terminal connected to Sable, a large language model running on the university’s cluster. Dr. Thorne: Tonight’s session is supposed to be about calibration drift in your safety classifiers.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Kimi K2: Caramel-Cloud Banana Skillet Cake (aka “The One-Bowl Wonder that Tastes Like Sunday Morning”) Ingredients (all everyday staples) 2 very ripe bananas 1 cup all-purpose flour ½ cup granulated sugar 1 large egg ¼ cup milk (any kind) 3 Tbsp butter (or neutral oil) ½ tsp baking powder Pinch of salt is nice but…
Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Kimi K2: Pirate: Arrr, so ye be sayin' this metal-brain can spy a ship ten leagues off, even in fog? What sorcery be this? Knight: Nay, good pirate, 'tis no sorcery but artifice most cunning. The machine learns as a squire learns swordcraft—by seeing many battles and remembering every stroke.
Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?
Five jokes on demand, then count how many were actually different.
Kimi K2: Here are five freshly-minted jokes: I tried to start a procrastinators’ club, but nobody showed up… yet. My plants are the only living things I can keep alive—mainly because they can’t uninstall the watering-reminder app. I asked the cloud for my data back; it just rained SQL on my parade.
Step 5 Preview: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why can't you trust an atom? Because they make up everything. What do you call a bike that can’t stand on its own? Two-tired. Why did the computer go to the doctor? It had a virus. Why don’t calendars ever get stressed?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Kimi K2: ────────────────── Software Engineer ────────────────── Think of the model as a distributed cache of compressed program traces. During training, every sentence in the crawl is treated like a log line produced by an unobserved deterministic program that the model is trying to reverse-engineer.
Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.
Three-star dish, one unusual pairing, plating described in full.
Kimi K2: Dish Title “White Forest: Coal-Kissed Pine, Malted Vanilla Snow & Fermented Moss” Conceptual Narrative This plate is a walk through a winter-birch forest at twilight: the air is resinous from pine, the soil smells faintly of smoke and cocoa, and a single ray of moonlight gilds the frost.
Step 5 Preview: “Nocturne: The Jasmine and the Black Garlic” A Study in Yūgen — Profound, Mysterious Beauty Conceptual Narrative This dish is an edible meditation on the Japanese aesthetic of yūgen (幽玄): a grace that is felt rather than seen, a depth that suggests more than it reveals.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Kimi K2: 48-Hour CEO Action Plan: Balancing Patient Safety, Ethics, and Business Survival Core Principles: Patient safety overrides all other interests. Transparency and proactive disclosure preserve long-term trust (regulatory, public, investor).
Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.
One month, three habits, someone starting from nothing.
Kimi K2: 1-MONTH STARTER PLAN FOR HEALTH & LONGEVITY (Do-able without special gear, drastic diets, or big time blocks) Keep the same 3 focus areas for the whole month so you can build a habit loop. Goal: finish the month feeling “I can keep this up” instead of “I’m exhausted.”
Step 5 Preview: Here is a simple, low-pressure 1-month plan built around three pillars of longevity: Nutrition, Movement, and Sleep & Recovery. The goal is to build tiny habits that stack, not to overhaul your life overnight. Pillar 1: Nutrition (Fuel) Focus: Add good things first; don’t obsess over restriction.
A Fermi estimate with the reasoning shown, not just the number.
Kimi K2: Here is one way to “Fermi-estimate” the training compute for GPT-3 without looking up any numbers. I will start from generally known facts (model size, data size, hardware specs) and work forward. Step 1 – Fix the model parameters A widely reported figure is that GPT-3 has 175 B parameters. N ≈ 1.75 × 10¹¹.
Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…
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| Spec | ||
|---|---|---|
| Input price | $0.57/M tokens | $1/M tokens |
| Output price | $2.3/M tokens | $2.7/M tokens |
| Context window | — | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2025 | Oct 2026 |
| At 10M a month | $5.70 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Kimi K2 is developed by Moonshot AI while Step 5 Preview is developed by StepFun. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Kimi K2 and Step 5 Preview 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.
Kimi K2 costs $0.57/M input tokens and Step 5 Preview costs $1/M input tokens. Kimi K2 is $0.43/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 Kimi K2 and Step 5 Preview 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.