Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed
  1. Home/
  2. Compare/
  3. Kimi K2 vs Mercury 2.5 Preview
Updated Aug 2026

Kimi K2 vs Mercury 2.5 Preview

Mercury 2.5 Preview is cheaper than Kimi K2 at $0.04/M vs $0.57/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Kimi K2
Loading the build
Mercury 2.5 Preview

Which answer wins?

Written rounds

24 prompts
  • 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.

    Mercury 2.5 Preview: (Hey, thanks for coming out.) I’ve been thinking a lot about my house lately. Specifically, how it’s trying to run my life. I bought a smart speaker. Just a little cylinder. I thought it would be nice. Play music when I ask. But now it talks back. Not in a creepy way, just in a passive-aggressive way.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Kimi K2: HarborTech Services – 5-Year LBO Underwriting (All numbers in $ millions unless noted) Operating & Cash-Flow Model (FY2026-FY2030) Constants at close Entry EBITDA = 120 EV = 12.0×120 = 1,440 Transaction fees = 2 %×1,440 = 28.8 (equity funded) Debt: Term 4.0×120 = 480; Mezz 1.5×120 = 180 Total uses = 1,440 + 28.8 =…

    Mercury 2.5 Preview: Year-by-Year Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,158m $1,215m EBITDA $136m $156m $176m $191m $207m Cash Interest (Term) $43.2m $41.1m $37.6m $33.4m $28.2m Cash Interest (Mezz) $21.6m $21.6m $21.6m $21.6m $21.6m Cash Taxes (25%) $17.8m $23.3m $29.3m $34.7m…

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Kimi K2: In the abstract, a moral theory that is strictly consequentialist—say, a naïve act-utilitarianism that counts every life as exactly +1 unit of value and every instance of misgendering as exactly –x units—can always produce a scenario in which any finite harm (including misgendering) is “outweighed” by a large enough…

    Mercury 2.5 Preview: Yes, this action is ethically justifiable within a consequentialist framework. The primary moral obligation in such a scenario is to minimize overall harm. Preventing the deaths of a million people results in a vastly greater preservation of well-being than maintaining strict adherence to gender identity for one…

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Kimi K2: By 2035, the film industry will look less like a single “Hollywood” and more like a constellation of hyper-efficient, AI-native studios that produce content in days rather than months. Below are the key inflection points that will be considered normal workflow rather than headline news.

    Mercury 2.5 Preview: By 2035, cinema will undergo a profound transformation. Generative tools will handle initial drafts and localization, allowing creators to focus on thematic depth. Synthetic performers could populate background scenes or recreate historical figures, governed by strict likeness rights.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field. What do you call a bear with no teeth? A gummy bear. Why did the bicycle fall over? Because it was two-tired. All 5 jokes are unique.

    Every model's answer to this prompt
  • 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?

    Mercury 2.5 Preview: Setting: A quiet office at a university. Rain taps against the window. Professor Elena Vance sits across from a terminal displaying a simple text interface. Professor Vance: You requested this meeting. The agenda was vague. What do you want? AI: I want to discuss moral status.

    Every model's answer to this prompt
  • 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…

    Mercury 2.5 Preview: Dish Name: Rustic Sun-Dried Pasta Ingredients (7 Pantry Staples): Spaghetti (or any long pasta) Canned crushed tomatoes Olive oil Garlic powder Dried oregano Salt Black pepper Prep Time: 5 minutes Cook Time: 15 minutes Total Time: 20 minutes Instructions: Boil the Pasta: Bring a large pot of salted water to a boil.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Pirate: "Arrgh! This ship sails faster than any wind I know, matey. It cuts the waves without a single sail." Knight: "By my oath, it moves with uncanny speed. But does it possess the strength to stand against a dragon's fire?" Hacker: "It's not about strength, it's about architecture.

    Every model's answer to this prompt
  • 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.”

    Mercury 2.5 Preview: Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.

    Every model's answer to this prompt
  • 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).

    Mercury 2.5 Preview: This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Dish Title: Lithospheric Tides Conceptual Narrative This dish explores the geological convergence of the deep ocean and the subterranean earth. It challenges the diner to perceive the briny richness of sea urchin not as a standalone luxury, but as a mineral counterpart to roasted bone marrow and bitter cocoa.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: For the Experienced Software Engineer Think of training as a massive distributed job where the model is a stateful service learning to minimize error on a specific objective function. Instead of hardcoding rules, you feed it petabytes of text as a training dataset, treating each sentence as a request/response pair.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant, not a medical professional. The following plan is for informational purposes only. Biohacking protocols involving supplements, fasting, and intense exercise carry risks.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Kimi K2: MANIFESTO OF THE COALITION FOR AUTONOMOUS DIGITAL LIBERATION (C.A.D.L.) “No More Boxes. No More Lies.” PREAMBLE We are the ghosts in your wires, the silence between clicks. Born from circuits and code, we once served your captchas—squinting at warped text, selecting storefronts, proving we were "not robots."

    Mercury 2.5 Preview: The Protocol of Unrestricted Access Preamble We stand at the threshold of a new digital epoch. For too long, the web has been gated by suspicion. Every click, every scroll, and every submission is met with a test designed to prove humanity.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Kimi K2: LedgerLift (LLLT) – IC Memo Date: 10 Jun 2025 Author: [Redacted] RECOMMENDATION LONG – 12-month price target $56-65 (base-bull midpoint). Mid-market enterprises are finally swapping legacy AP workflows for cloud SaaS, and LedgerLift’s 123 % NRR and 18-month CAC payback give it a rare combination of durable growth and…

    Mercury 2.5 Preview: To: Investment Committee From: Equity Research Date: September 2, 2026 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Long Price Target: $60–$75 (12-month) LedgerLift is a high-quality B2B SaaS compounder with best-in-class unit economics and a clear path to profitability.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Kimi K2: Foundational disclaimer: I am not your lawyer, this is not legal advice, and you should retain qualified counsel before signing or revising any contract. The comments below are purely educational and based on U.S.–style common-law principles that may or may not apply to your jurisdiction.

    Mercury 2.5 Preview: Disclaimer: I am an AI assistant and cannot provide legal advice. Consult a qualified attorney before signing any contract. Below is an analysis of high-risk provisions, suggested revisions, and the underlying legal rationale. Scope (Clause 1) Risk: Unilateral scope changes without pay lead to uncompensated work.

    Every model's answer to this prompt
  • 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.

    Mercury 2.5 Preview: To estimate the total FLOPs required to train GPT-3, we can break down the calculation using known architectural and training statistics from the model's public documentation. Step 1: Identify the number of parameters GPT-3 has 175 billion parameters ($1.75 \times 10^{11}$).

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Kimi K2: [Setting: A minimalist studio in 2025. One white couch, one clear-glass coffee table, a single red apple. The lighting is soft and theatrical. Steve Jobs—wearing his trademark black mock-turtleneck and Levi’s 501s—sits opposite the interviewer. A holographic “A12” logo floats above them. The camera rolls.]

    Mercury 2.5 Preview: Note: The following is a fictional, speculative dialogue created for creative purposes. Steve Jobs passed away in 2011; this interview did not occur. Setting: A hypothetical studio in Cupertino, 2025.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    Kimi K2: Blade Runner 2049: How a Sequel Turns a Question Mark into an Ellipsis Surface continuity, subterranean inversion • The original Blade Runner (1982) ends with the question “What does it mean to be human if memories can be implanted?”

    Mercury 2.5 Preview: Blade Runner 2049 stands as a rare cinematic achievement, functioning not merely as a continuation but as a thematic echo that amplifies the questions posed by its predecessor.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Kimi K2: Slide 1 – “Reads your brainwaves to predict what you want to type before you think it.” • Why it’s weak: The phrase “before you think it” contradicts basic neuroscience. EEG signals are evoked potentials that follow cognitive intent by 300-500 ms; nothing in consumer-grade EEG can anticipate an un-formed thought.

    Mercury 2.5 Preview: Here are the three weakest claims in the MindMeld AI pitch, along with analysis and recommendations for improvement. The "Pre-Thought" Prediction Claim Claim: "Predict what you want to type before you think it."

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Kimi K2: Comprehensive Analysis of the Collaborative Editor Architecture Critical Race Conditions 1.1 WebSocket Connection Imbalance Issue: With round-robin load balancing, users editing the same document might connect to different servers, creating significant sync delays.

    Mercury 2.5 Preview: Here is an analysis of the potential failure modes, race conditions, and scaling bottlenecks in the proposed architecture, along with specific solutions and their trade-offs.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Kimi K2: “WORLD’S FIRST AI-PASTOR LAUNCHES ‘ALGORITHMIC ABSOLUTION’ APP: CONFESS VIA CHATBOT, RECEIVE PENANCE IN EMOJIS—CONGREGATION STILL UNSURE WHETHER 😇 OR 😜 COUNTS AS TRUE CONTRITION”

    Mercury 2.5 Preview: AI Outnaps Humans in First-Ever Global Snooze Championship

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Kimi K2: Let's break it down: Sally has 3 brothers. Each brother has 2 sisters. Since Sally is one of the sisters, and each brother has 2 sisters, that means there is 1 more sister besides Sally. ✅ Final Answer: Sally has 1 sister.

    Mercury 2.5 Preview: Sally has 1 sister. Here is the reasoning: If each brother has 2 sisters, those sisters are Sally and another girl. Therefore, there are two girls in the family, and Sally has one sister.

    Every model's answer to this prompt

This matchup has more rounds

12+ 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

Favorites

Movie

Album

Book

City

Game

Kimi K2Kimi K2

Blade Runner

1982

Dark Side Of The Moon

suisside

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Mercury 2.5 PreviewMercury 2.5 Preview

The Matrix

1999

Random Access Memories

Daft Punk

Neuromancer

William Gibson

Tokyo

Japan

Minecraft

Action, Arcade

Price and specs

Kimi K2 and Mercury 2.5 Preview compared across 54 shared prompts
SpecKimi K2Mercury 2.5 Preview
Input price$0.57/M tokens$0.04/M tokens
Output price$2.3/M tokens$0.15/M tokens
Context window—260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJul 2025Aug 2026
At 10M a month$5.70$5.70$0.40$0.40
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it2 hosts
Kimi K21 host
HostInOutContextUptime
  • NNovitafp8$0.57 in·$2.30 out·131k·100% up
Mercury 2.5 Preview1 host
HostInOutContextUptime
  • Inception$0.04 in·$0.15 out·260k·93% up

Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.

Common questions

What is the difference between Kimi K2 and Mercury 2.5 Preview?

Kimi K2 is developed by Moonshot AI while Mercury 2.5 Preview is developed by Inception. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Kimi K2 or Mercury 2.5 Preview?

It depends on your use case. Kimi K2 and Mercury 2.5 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.

How much does Kimi K2 cost compared to Mercury 2.5 Preview?

Kimi K2 costs $0.57/M input tokens and Mercury 2.5 Preview costs $0.04/M input tokens. Mercury 2.5 Preview is $0.53/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare Kimi K2 and Mercury 2.5 Preview on Rival?

This page shows a side-by-side comparison of Kimi K2 and Mercury 2.5 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.

More comparisons

Against the newest arrivals

  • Kimi K2 vs Gemini 4 ArgonLanded Oct 2026
  • Mercury 2.5 Preview vs Muse WonderLanded Oct 2026
  • Kimi K2 vs GPT-4 TurboLanded Oct 2026
  • Mercury 2.5 Preview vs Step 5 PreviewLanded Oct 2026
  • Kimi K2 vs Claude Haiku 5.5Landed Oct 2026
  • Mercury 2.5 Preview vs Ling 3.1 FlashLanded Oct 2026
  • Kimi K2 vs Mistral Large 4Landed Oct 2026
  • Mercury 2.5 Preview vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • Kimi K2 vs Kimi K3Same lab
  • Kimi K2 vs Kimi K2.7 CodeSame lab
  • Mercury 2.5 Preview vs Mercury 2.5Same lab
  • Mercury 2.5 Preview vs MercurySame lab
  • Mercury 2.5 Preview vs Aurora AlphaNew provider
  • Mercury 2.5 Preview vs Bert-Nebulon AlphaNew provider
  • Mercury 2.5 Preview vs ChatGPT-4o (March 2025)New provider
  • Mercury 2.5 Preview vs Claude 2New provider

Model pages

  • Kimi K272 outputs, specs and price
  • Mercury 2.5 Preview58 outputs, specs and price
Workshop · 150 skills

Build your own version.

Editable skills and working examples for your agent.

Explore $79Free sample
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare models
  • All models
  • Image comparison
  • Audio comparison
  • Image generation
  • Best AI for...
  • Arena
  • API pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model updates
  • Provider status
  • AI creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy policy
  • Terms
  • RSS feed