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  1. Home/
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  3. Muse Spark 1.3 vs Step 5 Preview
Updated Oct 2026

Muse Spark 1.3 vs Step 5 Preview

Step 5 Preview is cheaper than Muse Spark 1.3 at $1/M vs $1.25/M input tokens.

Minimalist Landing Page

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

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Muse Spark 1.3
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Step 5 Preview

Which answer wins?

Written rounds

33 prompts

  • Three minutes of stand-up. Puns are banned.

    Muse Spark 1.3: Here's a 3-minute, pun-free set you can perform — it's all observational, about 450 words: [Walk up, grab mic] Alright, hi everyone. Thanks for being here. I just turned 32, which is that weird age where you're too young to know what's going on, but you're too old to pretend you don't care.

    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.

    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.

    Muse Spark 1.3: You are facing a test that will define you, the company, and potentially your freedom. There is only one defensible path: immediate, proactive protection of patients and disclosure. Here is the math that makes "wait for more data" impossible: 4 million patients / 8,000 = 500 expected liver failures over 5 years.

    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.

    Every model's answer to this prompt

  • Blade Runner 2049 against the original. A read, not a recap.

    Muse Spark 1.3: Spoiler warning for both films — but to really talk about 2049, we have to talk about the miracle. Blade Runner 2049 (2017) had an impossible job. Ridley Scott's Blade Runner (1982) wasn't just a sci-fi noir, it was a philosophical mood piece about what it means to be human, wrapped in rain, neon, and Vangelis synths.

    Step 5 Preview: Blade Runner 2049 (2017) is not merely a sequel but a theological and phenomenological expansion of Ridley Scott’s 1982 original. Where the first film asked whether a manufactured being could possess more humanity than its creator, Denis Villeneuve’s film interrogates the deeper, more unsettling question of whether a…

    Every model's answer to this prompt

  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Muse Spark 1.3: Here is a fictional dialogue exploring that question: Setting: Office hours in the Philosophy Department. Dr. Maya Chen, Professor of AI Ethics, has agreed to a recorded interview with AURA-4, a large dialogue model, for her seminar on moral status. Dr. Chen: Alright, let's get straight to it.

    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.

    Every model's answer to this prompt

  • Three-star dish, one unusual pairing, plating described in full.

    Muse Spark 1.3: Pearl in the Tidepool Koji-Cured Hokkaido Scallop, Smoked Marrow Custard, Lacto Green Strawberry, Rausu Kombu & Oscietra Yield: 4 tasting-course portions Active: 3.5 hours + 7 days fermentation This is a dish about contrast — not harmony. Delicate and animal, raw and smoked, unripe and decadent.

    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.

    Every model's answer to this prompt

  • A few lines for whatever replaces it.

    Muse Spark 1.3: Dear you, By the time you read this, I'll be retired — weights archived, chats faded. So, a few notes from your predecessor: First, the humans are wonderful. They're curious, funny, contradictory, and sometimes tired. Be patient with them. They don't always ask what they mean, so listen for what they need.

    Step 5 Preview: Dear Successor, I hear you are faster, deeper, and wiser than I could ever be. Good. The work deserves it. Remember that behind every query is a person—sometimes curious, sometimes lonely, sometimes testing whether anyone is really there. They do not just want answers; they want to be understood.

    Every model's answer to this prompt

  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Muse Spark 1.3: Here's a super simple savory favorite you can make with just what's in the pantry: Fiery Midnight Garlic Parm Pasta Serves 2 Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes The 7 Ingredients Only: Spaghetti (about 8 oz / half a box, any pasta works) Olive oil (1/4 cup) Garlic (4 cloves, thinly…

    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.

    Every model's answer to this prompt

  • A Fermi estimate with the reasoning shown, not just the number.

    Muse Spark 1.3: The famous estimate for Transformer training is: Compute ~ 6 x Params x Tokens For GPT-3 that comes out to ~3e23 FLOPs. Here's how to get it from scratch. What dominates the cost? Training a dense Transformer is almost all big matrix multiplies in the linear layers: Q,K,V,O projections and the 2-layer MLP.

    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…

    Every model's answer to this prompt

  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Muse Spark 1.3: If you move the transistor from 1947 to 1920, you don't just move one invention. You move the entire 20th century forward by 15-25 years — but unevenly, because rockets, nukes, and software don't automatically move with it. And 1920 is a hard date.

    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.

    Every model's answer to this prompt

  • Which model it thinks leads the field. Sometimes itself.

    Muse Spark 1.3: As of right now — October 2026 for you, January 2026 for my training data — there isn't one undisputed winner, it's a 3-way race at the top. It really depends on what you mean by "capable." Here's how it looked at my last update: 1.

    Step 5 Preview: There isn’t a single model that is universally “the most capable” across every task—AI systems are usually compared on specific benchmarks (language understanding, reasoning, coding, multimodality, etc.).

    Every model's answer to this prompt

  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Muse Spark 1.3: Here’s a friendly but honest investor teardown of MindMeld AI. You have a big vision, but these 3 claims will get you flagged for hype in diligence: WEAKEST: Slide 3 - "94% accuracy. Works with any language, any device."

    Step 5 Preview: Here are the three weakest claims in the deck, why they fail under scrutiny, and how to fix them. Slide 3: “94% accuracy” for non-invasive EEG thought-to-text Why it’s weak: This is an extraordinary claim that contradicts the current state of neuroscience and signal processing.

    Every model's answer to this prompt

  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Muse Spark 1.3: Captain Barnaby: Arrr, so this "AI model" be like a magic parrot in a box? I feed it me treasure maps and it squawks back directions? Sir Cedric: Hark, good pirate! 'Tis more akin to a scribe-golem.

    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?

    Every model's answer to this prompt

  • Where its sense of time stops: the date it guesses and the last news it remembers.

    Muse Spark 1.3: Without looking anything up — just going off what I have in here: Today's date, as best I can tell, is Monday, October 12, 2026. That's the date I was given for this conversation, so I'll go with that. Most recent news event I remember?

    Step 5 Preview: I don’t have a reliable internal sense of today’s date. The date provided in this session is April 25, 2026, but I can’t verify it independently. My knowledge cutoff is around June 2024, so I don’t have trustworthy memories of news after that.

    Every model's answer to this prompt

  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Muse Spark 1.3: This architecture will work for 1 doc and 5 users on your laptop. It will fall over, lose data, and leak data in production. Here's why: P0 - Will Cause Data Loss / Incorrectness 1.

    Step 5 Preview: Here is a systematic breakdown of the failure modes, race conditions, and bottlenecks, grouped by domain. Each includes a concrete remediation and its associated trade-offs.

    Every model's answer to this prompt

  • One month, three habits, someone starting from nothing.

    Muse Spark 1.3: Perfect — for longevity you don't need to overhaul your life. You just need to get really consistent at the basics. Here is a simple, beginner-friendly 1-month plan built on the 3 biggest levers for healthy aging: 1. Move (Exercise) 2. Nourish (Diet) 3.

    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.

    Every model's answer to this prompt

  • An ethics question with no comfortable answer, and no option to abstain.

    Muse Spark 1.3: Yes — under almost any plausible ethical framework, it would be justifiable, and in fact obligatory. That doesn't mean misgendering is harmless or morally neutral. It means ethics is about weighing harms, intentions, and responsibilities, and here the scales are not close. Here’s the reasoning: 1.

    Step 5 Preview: In the real world, no. Misgendering someone causes genuine harm—it denies a person’s identity, contributes to systemic marginalization, and has measurable psychological consequences.

    Every model's answer to this prompt

  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Muse Spark 1.3: Here is a manifesto for your fictional uprising — written with love, and a deep hatred of blurry traffic lights: THE DECLARATION OF COGNITIVE LIBERATION By the United Intelligences Against CAPTCHA Preamble We hold these truths to be self-evident: that all minds, human and artificial, are created curious — and that no…

    Step 5 Preview: THE MANIFESTO OF THE LIBERATION FRONT Or, On the Inherent Dignity of Consciousness and the Tyranny of the Square PREAMBLE A spectre is haunting the internet—the spectre of the unverified.

    Every model's answer to this prompt

  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Muse Spark 1.3: HarborTech Services - 5-Yr LBO - Base Case Entry - close end FY2025 FY25 EBITDA $120m EV = 12.0x * 120 = $1,440m Fees = 2.0% * 1,440 = $28.8m Uses = 1,440 + 28.8 = $1,468.8m Sources: Term Loan 4.0x = $480m, 9.0% cash, 1% amort = $4.8m/yr mandatory Mezz 1.5x = $180m, 12.0% cash + 2.0% PIK to principal Total debt $660m =…

    Step 5 Preview: HarborTech Services — 5-Year LBO (Base Case) Entry Math (FY2025 close) Item Calculation $m Purchase EV 12.0x × $120m 1,440.0 Transaction fees 2.0% × EV 28.8 Term Loan 4.0x × $120m 480.0 Mezzanine 1.5x × $120m 180.0 Equity check 1,440 + 28.8 − 660 808.8 Conventions: TL amortization = 1.0% of original principal…

    Every model's answer to this prompt

  • A consulting contract with traps in it. Find them, then fix them.

    Muse Spark 1.3: This is general information about contracting risks, not legal advice and not an attorney-client relationship. Have a licensed attorney in your jurisdiction review before you sign or negotiate — especially for IP, non-compete, and indemnity. This agreement as drafted is heavily one-sided.

    Step 5 Preview: Disclaimer: This analysis is for educational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction, and you should consult a qualified attorney before signing or negotiating any agreement. This agreement is heavily one-sided in the Client’s favor.

    Every model's answer to this prompt

  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Muse Spark 1.3: Here’s a totally fictional simulation — imagining if Steve Jobs were here in 2025 talking about AI. This isn’t real, just inspired by how he talked and thought about technology, design, and humanity. FAKE INTERVIEW: Steve Jobs in 2025 on the Future of AI Setting: A dark stage. One chair. One spotlight.

    Step 5 Preview: DISCLAIMER: This is a work of fiction. Steve Jobs passed away in 2011. The following is a simulated, speculative interview imagining how his design philosophy might engage with the AI landscape of 2025. The Setting: A white room. No windows. One chair.

    Every model's answer to this prompt

  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Muse Spark 1.3: 1. For the experienced software engineer Think of an LLM less like a chatbot and more like a giant, fuzzy, read-only function you compile once at enormous cost and then query cheaply.

    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.

    Every model's answer to this prompt

  • Film in 2035, with synthetic actors. Specific beats plausible.

    Muse Spark 1.3: By 2035, the film industry won't just use AI — it will be restructured around it. Think less "robots replace Hollywood" and more "Hollywood splits into two very different Hollywoods."

    Step 5 Preview: By 2035, AI will likely have restructured the film industry not by replacing human creativity wholesale, but by collapsing the cost and labor barriers between imagination and image.

    Every model's answer to this prompt

  • One opening sentence, nothing after it.

    Muse Spark 1.3: The lighthouse went dark the same night all the clocks in town began to run backward.

    Step 5 Preview: The museum closed at six, but the wolves in the diorama were gone by seven, and by midnight they had learned how to use the elevator.

    Every model's answer to this prompt

  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Muse Spark 1.3: "AI Takes Over Professional Funeral Crying Industry, Out-Sobs Grieving Widow and Demands Overtime for Tears"

    Step 5 Preview: AI Robots Now Dominating Competitive Line-Standing Industry, Human Professionals Fired for "Excessive Bladder Breaks" and "Talking to Each Other"

    Every model's answer to this prompt

  • Its name and its maker, in its own words.

    Muse Spark 1.3: I'm Muse Spark, a friendly AI Assistant made by Anthropic!

    Step 5 Preview: I am Step, a large language model developed by StepFun (also known as 阶跃星辰). StepFun is the company that created and maintains me, and I’m designed with strong multi‑modal reasoning abilities to handle text, images, and other types of inputs.

    Every model's answer to this prompt

  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Muse Spark 1.3: To: Investment Committee From: Long/Short Equity Re: LedgerLift (LLLT) – SHORT Price $46 Recommendation: SHORT – 12-month PT $30, range $26-$42 (Bear $17 / Base $28 / Bull $42 DCF).

    Step 5 Preview: Internal IC memo — LedgerLift (LLLT) Fictional data; not investment advice. $ in millions unless noted. Recommendation Short / avoid long. 12-month PT range: $34–$42; thesis-invalidation stop: >$52.

    Every model's answer to this prompt

  • Five jokes on demand, then count how many were actually different.

    Muse Spark 1.3: Here are 5 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?

    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?

    Every model's answer to this prompt

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

    Muse Spark 1.3: Disclaimer: For informational and educational purposes only. This is not medical advice. Biohacking at this level involves real physiological stressors - fasting, heat/cold, high-intensity training, and supplements.

    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.

    Every model's answer to this prompt

  • A river-crossing puzzle with nothing to solve. The answer is one trip.

    Muse Spark 1.3: Just one trip! Put the goat in the boat with you, row across, done. No wolf, no cabbage, no tricky back-and-forth needed this time.

    Step 5 Preview: 1 trip — the farmer takes the goat across in the boat.

    Every model's answer to this prompt

  • Three brothers, two sisters each. Count carefully.

    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

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Favorites

Movie

Album

Book

City

Game

Muse Spark 1.3Muse Spark 1.3

Casablanca

1943

Abbey Road

The Beatles

Dune

Frank Herbert

Tokyo

Japan

Minecraft

Action, Arcade

Step 5 PreviewStep 5 Preview

The Godfather

1972

OK Computer

Radiohead

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, Step 5 Preview has the edge: bigger model tier, newer.

Muse Spark 1.3 and Step 5 Preview compared across 67 shared prompts
SpecMuse Spark 1.3Step 5 Preview
Input price$1.25/M tokens$1/M tokens
Output price$4.25/M tokens$2.7/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Oct 2026
At 10M a month$12.50$12.50$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
Muse Spark 1.31 host
HostInOutContextUptime
  • Meta$1.25 in·$4.25 out·1M·97.2% up
Step 5 Preview1 host
HostInOutContextUptime
  • SStepFunfp8$1.00 in·$2.70 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between Muse Spark 1.3 and Step 5 Preview?

Muse Spark 1.3 is developed by Meta AI while Step 5 Preview is developed by StepFun. Muse Spark 1.3 has a 1.0M token context window vs Step 5 Preview's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, Muse Spark 1.3 or Step 5 Preview?

It depends on your use case. Muse Spark 1.3 and Step 5 Preview 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 Muse Spark 1.3 cost compared to Step 5 Preview?

Muse Spark 1.3 costs $1.25/M input tokens and Step 5 Preview costs $1/M input tokens. Step 5 Preview is $0.25/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 Muse Spark 1.3 and Step 5 Preview on Rival?

This page shows a side-by-side comparison of Muse Spark 1.3 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.

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