DeepSeek V3.1 is cheaper than Muse Spark 1.3 at $0.2/M vs $1.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V3.1: Setting: A sleek, minimalist virtual interface. Dr. Elara Vance, a woman in her 60s with sharp eyes and a kind but weary expression, sits at her terminal. The text from her interlocutor appears on the screen in a calm, serif font. Participant: Gemini-7, a state-of-the-art multimodal AI. Dr. Vance: Good morning, Gemini.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V3.1: Of course! Here is a simple, delicious recipe using common pantry staples. Pantry Perfection Pasta This dish is a celebration of simplicity. The humble can of chickpeas is transformed into a crispy, savory topping, while a silky, garlic-infused oil coats the pasta for a meal that feels luxurious but is incredibly easy…
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…
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V3.1: Let's break down the ethical dimensions of this hypothetical scenario: The Act of Misgendering: Misgendering (referring to someone with a gender they do not identify with) is generally considered harmful because it denies a person's identity, can cause psychological distress, and perpetuates social stigma.
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.
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V3.1: Of course. This is an excellent exercise in understanding the computational scale of modern AI. Here is a step-by-step reasoning to estimate the FLOPs required to train GPT-3 without searching for the answer online. The most commonly cited figure for GPT-3 training is 3.14E23 FLOPs (314 ZettaFLOPs).
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.
Three-star dish, one unusual pairing, plating described in full.
DeepSeek V3.1: Of course. Here is an innovative recipe designed to the specifications of a Michelin 3-star restaurant. Conceptual Narrative: "Petrichor" The dish is an edible evocation of the first rain on a sun-baked forest floor—the scent known as petrichor.
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek V3.1: Excellent. This is a crisis that defines a company and its leadership. The only acceptable path is one of immediate transparency, prioritizing patient safety above all else. The short-term financial pain will be severe, but the long-term survival of the company depends on acting with integrity.
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.
DeepSeek V3.1: Of course. This contract is heavily one-sided and contains numerous clauses that are not only unfavorable to the contractor but are potentially unenforceable in many jurisdictions. Here is a breakdown of the problematic clauses, proposed modifications, and the legal reasoning.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V3.1: Of course. Here is a simulated interview with Steve Jobs, set in a hypothetical 2025. Setting: A minimalist studio at Apple Park. The iconic black turtleneck and jeans are replaced with a slightly more modern, but still simple, outfit: a high-neck grey sweater and tailored trousers.
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.
One month, three habits, someone starting from nothing.
DeepSeek V3.1: Of course. Here is a simple, actionable 1-month plan focused on three foundational pillars of health: Nutrition, Movement, and Recovery (which encompasses sleep and stress management). This plan is designed for a beginner, emphasizing consistency over perfection and building sustainable habits.
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.
Three minutes of stand-up. Puns are banned.
DeepSeek V3.1: (The Comedian walks out, grabs the mic. They look tired but amused.) Alright, how we doin'? Good, good. You all look… adequately hydrated. That’s a win. You know, I was at the grocery store yesterday, in the self-checkout line. Which is a modern form of torture.
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.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek V3.1: Of course. This is a fascinating counterfactual. An invention as foundational as the transistor arriving 27 years earlier would have sent shockwaves through every aspect of human society. Here is a detailed trace of the likely implications, focusing on second and third-order effects.
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.
Five jokes on demand, then count how many were actually different.
DeepSeek V3.1: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What's the best thing about Switzerland? I don't know, but the flag is a big plus. I told my wife she was drawing her eyebrows too high. She looked surprised.
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?
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| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $1.25/M tokens |
| Output price | $0.8/M tokens | $4.25/M tokens |
| Context window | 164K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Sep 2026 |
| At 10M a month | $2.00 | $12.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
DeepSeek V3.1 is developed by DeepSeek while Muse Spark 1.3 is developed by Meta AI. DeepSeek V3.1 has a 164K token context window vs Muse Spark 1.3's 1.0M. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V3.1 and Muse Spark 1.3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
DeepSeek V3.1 costs $0.2/M input tokens and Muse Spark 1.3 costs $1.25/M input tokens. DeepSeek V3.1 is $1.05/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 DeepSeek V3.1 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.