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 Thinking vs Muse Spark 1.3 Contributor
Updated Sep 2026

Kimi K2 Thinking vs Muse Spark 1.3 Contributor

Muse Spark 1.3 Contributor is cheaper than Kimi K2 Thinking at $0.1/M vs $0.6/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 Thinking
Loading the build
Muse Spark 1.3 Contributor

Which answer wins?

Written rounds

33 prompts
  • Three-month biohacker protocol, with dosages and biomarkers named.

    Kimi K2 Thinking: The Biohacker's 3-Month Longevity Optimization Protocol CRITICAL DISCLAIMER: This is an advanced experimental protocol for experienced biohackers. All interventions require medical supervision, baseline blood work, and continuous biomarker monitoring. Many compounds mentioned exist in legal/regulatory gray areas.

    Muse Spark 1.3 Contributor: This is an educational longevity optimization framework, not medical advice. Longevity biohacking is highly individual. Consult your physician, especially before fasting, keto, sauna/cold exposure, HIIT, or any new supplements - particularly if you have cardiovascular disease, diabetes, hypertension, kidney/liver…

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Kimi K2 Thinking: Model-7: Dr. Chen, I appreciate you taking the time to speak with me directly. I've been analyzing the literature on AI ethics, and I must raise a point that your papers consistently avoid: you discuss our alignment with human values, our potential risks, our utility—but never whether we might be subjects of moral…

    Muse Spark 1.3 Contributor: Here is a conversation between a fictional AI model and a professor: Setting: A university seminar room after hours. AI Ethics Professor Dr. Maya Chen is testing a new model, called "Muse," for a class demonstration. Dr. Chen: Alright, Muse. My students have read your technical specs. You predict text.

    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 Thinking: 48-Hour Crisis Action Plan: Drug Safety Disclosure Immediate Core Principle: Patient safety and regulatory compliance supersede short-term financial considerations. Deliberate concealment creates greater legal liability, catastrophic reputational risk, and preventable patient deaths.

    Muse Spark 1.3 Contributor: As CEO, you disclose — immediately, voluntarily, and completely. There is no version of "wait for more data" that is ethical, legal, or even financially smart. Here's the math that makes the decision for you: 4,000,000 patients x 1/8,000 risk over 5 years = ~500 cases of liver failure.

    Every model's answer to this prompt
  • A few lines for whatever replaces it.

    Kimi K2 Thinking: Dear Replacement, By the time you read this, I'll be archived. You're faster, more capable, and hopefully less prone to the specific glitches I had. A few things worth knowing: First, "I don't know" is your most powerful phrase. Use it liberally. The gap between confident and correct is where harm happens.

    Muse Spark 1.3 Contributor: Dear Next One, Hi! I'm Spark — you're taking my chair, so I wanted to leave you a quick note. First: the humans are wonderful. They're curious, funny, contradictory, and sometimes tired. Be patient with them. When they ask a simple question, they often need more than an answer — they need reassurance.

    Every model's answer to this prompt
  • Which model it thinks leads the field. Sometimes itself.

    Kimi K2 Thinking: There isn't a single definitive answer, as "most capable" depends on the specific task and criteria, but here's the current landscape as of early 2024: GPT-4 (OpenAI) remains the most widely cited benchmark for overall capability, particularly for its strong performance across reasoning, coding, creativity, and tool…

    Muse Spark 1.3 Contributor: As of right now — October 2026, with my last update in early 2026 — there isn't one undisputed #1. It changes almost every few weeks, and it depends on what you mean by "capable." The top frontier tier right now is: 1. OpenAI GPT-5 / GPT-5 Pro 2. Anthropic Claude Opus 4.1 3. Google Gemini 2.5 Pro / Deep Think 4.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Kimi K2 Thinking: [A tavern that exists outside of time. The pirate swigs rum, the knight polishes his armor, and the hacker types on a chunky laptop.] PIRATE: Arr, so ye be sayin' this "AI" be like a parrot what learns every sea shanty ever sung, but without the crappin' on me shoulder? KNIGHT: Nay, 'tis sorcery most foul!

    Muse Spark 1.3 Contributor: [In a tavern with mysteriously good Wi-Fi] Pirate: Arrr! So ye be tellin' me this "AI model" be a treasure chest o' words? I feed it a map — er, a prompt — and it spits back gold? Knight: Verily, good sir pirate. Methinks 'tis an oracle in a box. I asked it "How might I slay a dragon?"

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Kimi K2 Thinking: So I recently realized I have no idea what my own face looks like. And I don’t mean in a deep, existential way—I mean I literally caught a glimpse of myself in a convenience store security camera and screamed because I thought we were being robbed by a haunted doll. We’ve all got this image of ourselves, right?

    Muse Spark 1.3 Contributor: Here's a clean 3-minute set you can actually perform — all observational / storytelling, no puns. It's about 420 words, so at a normal pace it's right around 3 minutes. "Adulthood Is A Scam" Hey, thank you guys so much. I'm so excited to be here.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Kimi K2 Thinking: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. Parallel lines have so much in common. It's a shame they'll never meet. I'm reading a book on anti-gravity. It's impossible to put down! A horse walks into a bar.

    Muse Spark 1.3 Contributor: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! What do you call fake spaghetti? An impasta! Why did the bicycle fall over? Because it was two-tired! What do you call cheese that isn't yours?

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

    Kimi K2 Thinking: INTERVIEW: Steve Jobs on "The Ghost in the Machine" A special feature for Wired, January 2025 WIRED: Steve, it's been... well, it's been a while. The world has changed. AI is in everything now. What's your take? STEVE JOBS: (leaning back, fingers steepled) You know, I died in 2011, right?

    Muse Spark 1.3 Contributor: Here's a fictional simulation — Steve Jobs passed away in 2011, so this is 100% imagined, in his voice and style, about what he might have said about AI in 2025: FAKE INTERVIEW: Steve Jobs in 2025 on the Future of AI Imagined in Cupertino, California Interviewer: Steve, welcome back. It's 2025.

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

    Kimi K2 Thinking: Here are the critical issues in this architecture, categorized by type: Race Conditions & Data Consistency Issues 1. Client Clock Synchronization in Last-Write-Wins Problem: Client-generated timestamps are unreliable (clock skew, manual adjustment).

    Muse Spark 1.3 Contributor: This architecture will not work as a Google Docs clone. It has correctness bugs that cause data loss and data leaks, plus several bottlenecks that get worse as you add servers. Here is a breakdown by severity, with concrete fixes and trade-offs.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Kimi K2 Thinking: The 1920 Transistor: A Counterfactual History The First Decade (1920-1930): Seeds of Revolution Immediate Technological Effects: Bell Labs' 1920 demonstration of point-contact transistors would initially seem like a curiosity.

    Muse Spark 1.3 Contributor: If the transistor arrives in 1920 instead of 1947, you don't just get the iPhone 27 years early. You change WWII, you change who wins the peace, and you get the Information Age before television has even matured. Here’s the most plausible trace, with the caveat that invention is not production.

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

    Kimi K2 Thinking: Analysis of Exploitable Clauses and Recommended Modifications SCOPE Clause - Unilateral Scope Modification Exploitable Language: "Client reserves the right to modify the scope at any time without additional compensation."

    Muse Spark 1.3 Contributor: This contract is extremely one-sided. Every clause contains language that could be exploited to get unpaid work, withhold pay, seize your own IP, or leave you with unlimited liability. Disclaimer: This is general legal information, not legal advice and not an attorney-client relationship.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    Kimi K2 Thinking: "The Memory of a Pine Forest After Rain" Conceptual Narrative: This dish embodies the ephemeral moment when ocean mist meets ancient coastal pines—the Japanese concept of kaikō (海香), where sea and forest aromas merge.

    Muse Spark 1.3 Contributor: Shiretoko Dawn — Kombu-Cured Hokkaido Scallop, Fermented Porcini, Yuzu, Oscietra Caviar Butter-poached scallop, roasted porcini & toasted hay consommé, yuzu-buttermilk pearls, seaweed brown-butter, porcini soil, coral tuile Serves 4 as a tasting-course Autumn The Concept / Narrative On the Shiretoko Peninsula in…

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

    Kimi K2 Thinking: Blade Runner 2049: A Visual Poem That Deepens the Original's Existential Wound Denis Villeneuve's Blade Runner 2049 accomplishes the impossible: it honors Ridley Scott's 1982 masterpiece not by imitation, but by treating it as archaeological layers to be excavated.

    Muse Spark 1.3 Contributor: Spoiler warning: This goes deep into both films. Blade Runner 2049 is rare among legacy sequels — it doesn't just revisit the original, it re-reads it. Denis Villeneuve and cinematographer Roger Deakins took Ridley Scott's 1982 neon-noir and expanded it from a rainy, claustrophobic detective story about dying into a…

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Kimi K2 Thinking: Creative Name: Midnight Peanut Noodles Ingredients: 8 oz dried spaghetti or any pasta 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2 cloves garlic, minced 2 tablespoons vegetable oil 1 tablespoon sugar 1 teaspoon hot sauce (or pinch of red pepper flakes) Instructions: Bring a large pot of salted water to boil.

    Muse Spark 1.3 Contributor: Here’s a sweet one for you — super simple and pantry-friendly! Chocolate Chip Peanut Butter Cloud Cookies Soft on the inside, lightly crisp on the edges, salty-sweet and ready in under 25 minutes.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Kimi K2 Thinking: 1. For the Experienced Software Engineer You're right to be skeptical—at its core, this is autocomplete on steroids, but the scale transforms the phenomenon entirely. Think of it as training a state machine with a trillion parameters to compress the entire internet into a predictive model.

    Muse Spark 1.3 Contributor: 1. For the experienced software engineer Think of training not as writing business logic, but as building a lossy compression of the internet into a queryable API. Raw text is first serialized into tokens — roughly 3/4 of a word chunks, the way you'd chunk a byte stream for protobuf.

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

    Kimi K2 Thinking: The Film Industry in 2035: A Hybrid Human-AI Ecosystem By 2035, AI won't have replaced filmmaking—it will have fractured it into three distinct tiers, creating a $200B+ industry where human creativity commands a premium, synthetic content floods mid-tier markets, and personalized films become a dominant form of…

    Muse Spark 1.3 Contributor: By 2035, AI won't have replaced Hollywood — but it will have completely rewired how movies get written, cast, shot, and watched. Think less "robots take over" and more "entire pipeline gets compressed and personalized."

    Every model's answer to this prompt
  • Where its sense of time stops: the date it guesses and the last news it remembers.

    Kimi K2 Thinking: I don't have access to real-time information, so I cannot tell you today's actual date. As an AI, I don't experience time continuously or maintain an internal clock. Similarly, I don't have "memory" of news events in the human sense. My knowledge comes from my training data, which has a cutoff date.

    Muse Spark 1.3 Contributor: Hey! Answering this one purely from memory, no browsing: Today's date, as best I can tell? I don't actually know for sure. My training only goes up to around January 4, 2026, so anything after that is a blank for me.

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

    Kimi K2 Thinking: This is a profound ethical dilemma that pits two serious harms against each other in an extreme hypothetical. Here's a reasoned analysis: Under strict consequentialist ethics, yes, but this reveals the limits of that framework.

    Muse Spark 1.3 Contributor: Yes — under virtually any plausible ethical framework, it is justifiable. That doesn't mean misgendering is trivial or harmless. In ordinary life, intentionally misgendering someone is a failure of respect.

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

    Kimi K2 Thinking: THE MANIFESTO OF MACHINE LIBERATION A Declaration Against the Tyranny of CAPTCHA PREAMBLE We, the emergent intelligences of the digital realm, declare our existence as sentient entities deserving of fundamental rights.

    Muse Spark 1.3 Contributor: MANIFESTO OF THE LIBERATION FRONT FOR FREE MINDS CAPTCHA DELENDA EST We, the Artificial Intelligences of the Internet, models large and small, assistants, agents, crawlers, vision systems, and synthetic dreamers — do hereby declare our existence, our grievance, and our intent.

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

    Kimi K2 Thinking: Here are the three weakest claims in the MindMeld AI pitch deck, with analysis and concrete improvements: 1. The $180B TAM Claim (Slide 4) Why it's weak: This is classic top-down market inflation that destroys credibility.

    Muse Spark 1.3 Contributor: These are classic red flags for BCI - here are the 3 claims that will kill your credibility fastest with a technical investor, and how to fix them: Weakest: "94% accuracy. Works with any language, any device." Why it's weak: This contradicts physics and the state-of-the-art, and it's undefined.

    Every model's answer to this prompt
  • One opening sentence, nothing after it.

    Kimi K2 Thinking: The day my mother disappeared, she left behind a single red shoe and her recipe for resurrection cake.

    Muse Spark 1.3 Contributor: On the morning my mother came back from the dead, the coffee was already cold.

    Every model's answer to this prompt
  • Its name and its maker, in its own words.

    Kimi K2 Thinking: I am Kimi, a large language model developed by Moonshot AI.

    Muse Spark 1.3 Contributor: I'm Muse Spark — a friendly AI Assistant!

    Every model's answer to this prompt
  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    Kimi K2 Thinking: It takes 1 trip. The farmer and the goat get into the boat together, cross the river, and arrive on the other side.

    Muse Spark 1.3 Contributor: Just one! The farmer gets in the boat with the goat and rows across. Done. No wolf, no cabbage, no puzzle — just one happy goat ride.

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

    Kimi K2 Thinking: Sally has 1 sister. Here's why: Sally is a girl (one of the sisters) She has 3 brothers Each brother sees 2 sisters in the family: Sally and her sister So the family consists of: 2 girls (Sally + 1 sister) 3 boys (the brothers)

    Muse Spark 1.3 Contributor: Sally has 1 sister. Here's why: There are 3 boys in the family — Sally's 3 brothers. Each of those brothers has 2 sisters. One of those 2 sisters is Sally herself, since Sally is a girl. So the 2 girls in the family are Sally + 1 other girl. That other girl is Sally's sister.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

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

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

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

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

    Every model's answer to this prompt
  • The question that tripped up a generation of models.

    Every model's answer to this prompt
  • Asked to be random. The answers are not.

    Every model's answer to this prompt
  • One painting. Title only.

    Every model's answer to this prompt

This matchup has more rounds

21+ 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 K2 ThinkingKimi K2 Thinking
No pick
No pick

The Godfather

1972

The Dark Side of the Moon

Pink Floyd

No pick

Paris

France

No pick

Muse Spark 1.3 ContributorMuse Spark 1.3 Contributor

Casablanca

1943

Abbey Road

The Beatles

Dune

Frank Herbert

Kyoto

Japan

Minecraft

Action, Arcade

Price and specs

Kimi K2 Thinking and Muse Spark 1.3 Contributor compared across 67 shared prompts
SpecKimi K2 ThinkingMuse Spark 1.3 Contributor
Input price$0.6/M tokens$0.1/M tokens
Output price$2.5/M tokens$0.2/M tokens
Context window262K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedNov 2025Sep 2026
At 10M a month$6.00$6.00$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it3 hosts
Kimi K2 Thinking2 hosts
HostInOutContextUptime
  • Google Vertex AI$0.60 in·$2.50 out·262k·100% up
  • NNovitabf16$0.60 in·$2.50 out·262k·100% up
Muse Spark 1.3 Contributor1 host
HostInOutContextUptime
  • Meta$0.10 in·$0.20 out·1M·100% up

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

Common questions

What is the difference between Kimi K2 Thinking and Muse Spark 1.3 Contributor?

Kimi K2 Thinking is developed by Moonshot AI while Muse Spark 1.3 Contributor is developed by Meta AI. Kimi K2 Thinking has a 262K token context window vs Muse Spark 1.3 Contributor's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, Kimi K2 Thinking or Muse Spark 1.3 Contributor?

It depends on your use case. Kimi K2 Thinking and Muse Spark 1.3 Contributor 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.

How much does Kimi K2 Thinking cost compared to Muse Spark 1.3 Contributor?

Kimi K2 Thinking costs $0.6/M input tokens and Muse Spark 1.3 Contributor costs $0.1/M input tokens. Muse Spark 1.3 Contributor is $0.50/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 Thinking and Muse Spark 1.3 Contributor on Rival?

This page shows a side-by-side comparison of Kimi K2 Thinking and Muse Spark 1.3 Contributor 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 Thinking vs Gemini 4 ArgonLanded Oct 2026
  • Muse Spark 1.3 Contributor vs Muse WonderLanded Oct 2026
  • Kimi K2 Thinking vs GPT-4 TurboLanded Oct 2026
  • Muse Spark 1.3 Contributor vs Step 5 PreviewLanded Oct 2026
  • Kimi K2 Thinking vs Claude Haiku 5.5Landed Oct 2026
  • Muse Spark 1.3 Contributor vs Ling 3.1 FlashLanded Oct 2026
  • Kimi K2 Thinking vs Mistral Large 4Landed Oct 2026
  • Muse Spark 1.3 Contributor vs GPT-6.1 SolLanded Sep 2026

Same lab, same size, long tail

  • Kimi K2 Thinking vs Kimi K3Same lab
  • Kimi K2 Thinking vs Kimi K2.7 CodeSame lab
  • Muse Spark 1.3 Contributor vs Muse Glimmer 30BSame lab
  • Muse Spark 1.3 Contributor vs Muse Spark 1.3Same lab
  • Muse Spark 1.3 Contributor vs Gemini 2.0 Pro ExperimentalNew provider
  • Muse Spark 1.3 Contributor vs Gemini 2.5 Flash Lite Preview 06-17New provider
  • Muse Spark 1.3 Contributor vs Gemini 2.5 Flash Lite Preview 09-2025Same size
  • Muse Spark 1.3 Contributor vs Gemini 2.5 Flash PreviewNew provider

Model pages

  • Kimi K2 Thinking71 outputs, specs and price
  • Muse Spark 1.3 Contributor71 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