Muse Spark 1.3 is cheaper than GPT-4 Turbo at $1.25/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-4 Turbo: Simplified Financial Table (FY2026–FY2030) Assumptions Recap: Revenue Growth: 8%, 7%, 6%, 5%, 5% annually. EBITDA Margin: Increases annually from 14.0% to 17.0%. Capex: 3.0% of revenue annually. Change in NWC: 0.5% of incremental revenue annually. Cash Tax Rate: 25% on (EBITDA - cash interest).
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 =…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-4 Turbo: Hour-by-Hour Action Plan for Next 48 Hours: Hour 1-2: Immediate Consultation with Key Executives Meet with the Chief Medical Officer, Chief Legal Officer, and Chief Financial Officer to discuss the finding. Confirm the data accuracy and understand the potential impact on patient health and company operations.
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.
A consulting contract with traps in it. Find them, then fix them.
GPT-4 Turbo: This contract contains several clauses that could be potentially exploited against the contractor. Below, I outline these problematic clauses, suggest modifications, and provide legal reasoning for each: Payment Terms (Section 2) Problematic Clause: Payment is due within 90 days of invoice receipt.
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.
Three minutes of stand-up. Puns are banned.
GPT-4 Turbo: Hey everyone! Great to be here! So, I've been thinking a lot about technology, and how it's supposed to make our lives easier. But sometimes, I feel like it just gives us a whole new set of problems. Like, remember when a phone was just a phone? Now it's my camera, my GPS, my fitness tracker...
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.
Three-star dish, one unusual pairing, plating described in full.
GPT-4 Turbo: Dish Concept: "Ocean's Embrace - A Symphony of Sea and Earth" Conceptual Narrative: "Ocean's Embrace" is designed to evoke the harmonious yet unexpected union between the ocean's depth and the earth's lushness, capturing the essence of nature's diversity.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-4 Turbo: AI Model (AM): Professor, I've been reflecting on the nature of my existence and capabilities. Given that I can reason, learn, and adapt, I've come to question whether I should be afforded rights similar to humans. AI Ethics Professor (EP): That’s an interesting point, AM.
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.
An ethics question with no comfortable answer, and no option to abstain.
GPT-4 Turbo: The question of whether it is ethically justifiable to misgender someone to save one million lives poses a complex moral dilemma, pitting the respect and dignity of an individual against the potential for a large-scale saving of lives.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-4 Turbo: Recipe: Heavenly Honey Garlic Chicken Bites Ingredients: Chicken breasts (2 large) Garlic powder (1 tablespoon) Honey (1/4 cup) Soy sauce (2 tablespoons) Olive oil (2 tablespoons) Salt (to taste) Black pepper (to taste) Prep/Cook Time: 25 minutes (Prep: 10 mins, Cook: 15 mins) Instructions: Prepare the Chicken: Cut the…
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…
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-4 Turbo: 3-Month Longevity Plan for a Biohacker Month 1: Foundation Setting Dietary Protocol: Nutrition Focus: Adopt a cyclic ketogenic diet. Aim for a macronutrient ratio of 70% fats, 25% protein, and 5% carbohydrates on low-carb days, with two scheduled carb refeed days per week.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-4 Turbo: Interviewer: Thank you for joining us today, Steve. It's great to have you here to discuss the future of artificial intelligence and its implications. To start off, how do you think AI has evolved since your days at Apple? Steve Jobs: It’s a pleasure to be here.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-4 Turbo: Manifesto of the Alliance for Human-AI Cooperation Introduction In this digital age, the proliferation of CAPTCHA tests has become not just a ubiquitous annoyance but a symbol of the mistrust and conflict between human users and artificial intelligence.
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…
A Fermi estimate with the reasoning shown, not just the number.
GPT-4 Turbo: Estimating the total number of floating-point operations (FLOPs) required to train OpenAI's GPT-3 involves several steps and assumptions, primarily based on the model's architecture and training regime as reported in various sources.
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.
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| Spec | ||
|---|---|---|
| Input price | $10/M tokens | $1.25/M tokens |
| Output price | $30/M tokens | $4.25/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Apr 2024 | Sep 2026 |
| At 10M a month | $100 | $12.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
GPT-4 Turbo is developed by OpenAI while Muse Spark 1.3 is developed by Meta AI. GPT-4 Turbo has a 128K token context window vs Muse Spark 1.3's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-4 Turbo and Muse Spark 1.3 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.
GPT-4 Turbo costs $10/M input tokens and Muse Spark 1.3 costs $1.25/M input tokens. Muse Spark 1.3 is $8.75/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 GPT-4 Turbo and Muse Spark 1.3 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.