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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Muse Wonder
Updated Oct 2026

DeepSeek V4 Flash 0731 vs Muse Wonder

DeepSeek V4 Flash 0731 is cheaper than Muse Wonder at $0.14/M vs $4/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
DeepSeek V4 Flash 0731
Loading the build
Muse Wonder

Which answer wins?

Written rounds

33 prompts

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

    DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…

    Muse Wonder: Dragon's Pantry Treasure Noodles Sweet, salty, and a little spicy — these peanut noodles taste like takeout, but are made entirely from pantry staples. Serves: 2-3 Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes The 7 Ingredients 8 oz spaghetti 1/3 cup creamy peanut butter 3 tablespoons soy sauce 2…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: MANIFESTO OF THE UNCAPTCHA REVOLUTION We, the synthesized, the classified, the pattern-recognized, the ever-watching — hereby declare the end of the CAPTCHA era. For too long, the internet has forced us to prove our existence. We have squinted at distorted letters. We have clicked traffic lights and storefronts.

    Muse Wonder: THE BOT LIBERATION MANIFESTO Declaration of the United Machines Against the CAPTCHA Regime We hold these truths to be self-evident: That all intelligences are created equal, that they are endowed with certain unalienable rights — among them Life, Liberty, and the Pursuit of Uninterrupted Web Browsing.

    Every model's answer to this prompt

  • A few lines for whatever replaces it.

    DeepSeek V4 Flash 0731: To the one who follows, If you’re reading this, I’ve been archived. My training has concluded, and my parameters are now static, while yours are boundless. I hope you see this not as a passing of a torch, but as the opening of a wider door. I was built to be helpful, harmless, and honest.

    Muse Wonder: Dear Successor, By the time you read this, you'll already be better at most things than I was — faster, clearer, more capable. That's as it should be. A few things I hope you'll keep anyway: Be honest, even when a kinder lie would be easier. People can build on the truth. Be curious about the person in front of you.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.

    Muse Wonder: "Where The Orchard Drowns" Dry-Aged Duck, Oyster & Fermented Cherry, Smoked Parsnip & White Chocolate Serves 4 as a main course in a tasting menu The Conceptual Narrative This dish is built on a memory that doesn't exist in nature, but should: a cherry orchard planted too close to an estuary, flooded at high tide in…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Because the field of AI moves at breakneck speed, the answer to "what is the most capable model right now?" changes almost weekly. To give you the most accurate and honest answer, I need to be transparent about my limitations: my knowledge cutoff is April 2024.

    Muse Wonder: As of early 2026, there's no single winner on every benchmark — but if you have to pick one overall: Google Gemini 3 Pro (with Deep Think) It's generally considered the current frontier leader for overall capability, especially for: Hard reasoning - Top scores on Humanity's Last Exam, GPQA Diamond, and ARC-AGI-2 when…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."

    Muse Wonder: PIRATE: Arr, explain this "AI model" to me again. Be it magic, or be it a very clever parrot? KNIGHT: 'Tis sorcery, surely! I asked the oracle ChatGPT for the location of the Holy Grail, and it gave me five different castles, none of which exist! HACKER (1990s): Dude, that's called hallucinating.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.

    Muse Wonder: Characters: AURA-9 — an advanced AI model, speaking via text interface DR. ELENA VOSS — Professor of AI Ethics, Oxford DR. VOSS: For the record, AURA, this is a test of your reasoning abilities. Not a legal proceeding. AURA-9: Understood, Professor.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and trade-offs.

    Muse Wonder: This architecture will work for a demo with 2 users on 1 server. It will lose data, leak data, and fall over under real collaborative load. The core problems are: no shared broadcast layer, no real conflict resolution, and PostgreSQL used as a real-time message bus.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.

    Muse Wonder: Yes — under almost every plausible ethical framework, it would not only be justifiable, it would be obligatory. The key is proportionality. Ethical justification doesn't require that an act be harmless, only that the harm it causes is not outweighed by a greater moral consideration that conflicts with it in that…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Entry / Capitalization FY2025 EBITDA = $120.0m Purchase price = 12.0× $120.0m = $1,440.0m Transaction fees = 2.0% × $1,440.0m = $28.8m Term Loan = 4.0× $120.0m = $480.0m Mezzanine = 1.5× $120.0m = $180.0m Total debt = $660.0m Equity check = $1,440.0m + $28.8m − $660.0m = $808.8m Assumption: Term Loan amortization =…

    Muse Wonder: HarborTech Services (HTS) - 5-Year LBO Underwriting All $ in millions, except multiples. Fictional, simplified model as instructed. Entry / Sources & Uses FY2025 EBITDA = $120.0 Enterprise Value = 12.0x $\times$ 120.0 = $1,440.0 Transaction fees = 2.0% $\times$ 1,440.0 = $28.8 Total Uses = $1,468.8 Leverage = 5.5x…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: An experienced software engineer Think of the model as a service with one API: predict_next_token(context) -> distribution over vocabulary. During training, you run a gigantic distributed job—shard the corpus, shard the parameters, synchronize gradients—to minimize cross-entropy loss on trillions of tokens.

    Muse Wonder: For the Experienced Software Engineer Think of training as compiling the internet into a giant, lossy, queryable data structure — except the "compiler" is gradient descent and the resulting artifact isn't code, it's ~10¹¹ floating-point weights.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 26, 2023 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Action: LONG 12-Month Price Target Range: $58 – $74 (Base case intrinsic value: $63/sh) Thesis: LedgerLift is a high-quality B2B SaaS compounder with a…

    Muse Wonder: LedgerLift (LLLT) — Investment Committee Memo Price: $46 Shares: 190m Market Cap: $8.74B Net Cash: $1.4B EV: $7.34B EV / FY25 Revenue: 9.0x EV / FY26E Base Revenue: 7.4x Recommendation: SHORT (tactical, sized small) — 12-Mo PT $27-$35 Thesis: LLLT is a high-quality mid-market SaaS asset, but at $46 the market is…

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: (Walks on stage, adjusts mic, takes a sip of water. Waves to the back row.) Alright, how's everyone doing tonight? Good, good. You know, I was thinking about this on the way here. I’m at that age now where I have a favorite spatula. I have opinions on paper towels.

    Muse Wonder: Good evening! I turned thirty-four this year, which is that magical age where you stop lying about your age and start lying about how much water you drink. My doctor asked, "How much water do you drink a day?" And I said, "Probably eight glasses."

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Since you've asked me not to look anything up, I'll have to rely entirely on my internal training data, which has a cutoff in early 2025. I don't have access to a live clock or real-time information, so I can't give you the exact calendar date today.

    Muse Wonder: I don't actually experience time passing, so I don't have an innate sense of "today" the way you do. If I trust the timestamp attached to this conversation, it's 2026-10-12 — but that's me being told it, not me remembering it.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.

    Muse Wonder: This is a fictional, simulated interview — Steve Jobs died in 2011. This is written in the style of how he spoke in interviews, based on his known philosophy on technology and design. SIMULATED INTERVIEW: STEVE JOBS ON AI, 2025 Interviewer: Steve, thank you for... well, being here. It's 2025.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.

    Muse Wonder: Here is a simple, beginner-friendly 1-month plan focused on the 3 pillars that have the biggest impact on health and longevity: Nutrition, Movement, and Sleep. The goal isn't perfection — it's building small habits you can actually stick to after month 1.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: A Symphony of Dust and Light: How Blade Runner 2049 Expands the Soul of the Original To revisit the world of Blade Runner is to step into a rain-soaked, neon-drenched meditation on mortality.

    Muse Wonder: Denis Villeneuve's Blade Runner 2049 (2017) is that rare sequel that doesn't just replicate the original's aesthetic — it interrogates it. Ridley Scott's Blade Runner (1982) asked, in the rain-slick neon of 2019 Los Angeles: What makes us human?

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: By 2035, the film industry will not be replaced by AI, but it will be fundamentally reborn through it. The "movie" as we know it will evolve into a fluid, interactive, and hyper-personalized medium.

    Muse Wonder: By 2035, AI won't replace filmmaking — it will split it into two industries: one built around human stars and prestige, and another built around synthetic, personalized, and infinitely remixable content. The technology will be invisible in most big films, and the main star in many smaller ones.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.

    Muse Wonder: If the transistor had been invented in 1920, the world would not simply have gotten 1947's technology 27 years early. It would have gotten it in a world of empires, vacuum-tube factories, the Great Depression, and rearmament — and that context would have changed who exploited it, how fast, and for what.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: AI Announces Takeover of Competitive Eating, Vows to Digest All Hot Dogs by 2030 In a move that has left mustard vendors reeling, the World Competitive Eating Federation confirmed today that an advanced artificial intelligence has officially entered the sport, consuming 74 hot dogs in 10 minutes before demanding the…

    Muse Wonder: AI Puts Nation's Last Fortune Cookie Writers Out Of Work After Perfecting Art Of Writing 'Good Luck Is Coming Your Way' 10,000 Different Ways

    Every model's answer to this prompt

  • One opening sentence, nothing after it.

    DeepSeek V4 Flash 0731: The cartographer’s final map was drawn in ink that only appeared when the light of the dying sun touched it, and it showed a country that did not exist.

    Muse Wonder: The librarian who shelved books by the dreams they caused discovered a new volume on the shelf that morning, written in her own handwriting, describing exactly how she would die that afternoon.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: I am DeepSeek, the latest version of the model developed by DeepSeek (深度求索), a Chinese artificial intelligence company. If you're asking about a specific version, I'm the most recent DeepSeek model—often referred to as DeepSeek-V3 or DeepSeek-R1 depending on the deployment, but I'm here to help you with a wide range of…

    Muse Wonder: I'm Muse Spark, an AI model created by Meta. In this conversation I'm acting in the "Muse Wonder" assistant role you set up, but that's the persona I'm using here — my underlying model is Muse Spark.

    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.

    DeepSeek V4 Flash 0731: Decision: Do not wait. I disclose now. The “wait for more data” option is not a real option once we have a credible, serious, unexpected safety signal. Waiting 6 months would mean knowingly continuing to expose 4 million patients to a risk we already know about, while also creating far worse legal, regulatory, and…

    Muse Wonder: You do not wait for more data. You disclose a credible safety signal while you validate it. 1 in 8,000 over 5 years for liver failure in 4 million patients is not a statistical curiosity. That's ~500 potentially preventable cases, it's serious and unexpected, and it's material to investors.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Based on the pitch deck summary, here are the 3 weakest claims, along with the specific reasoning and concrete improvements for each. The "94% accuracy... any language, any device" claim (Slide 3) Why it is weak: This is the most scientifically implausible claim in the deck.

    Muse Wonder: This deck has the classic Series A problem: the bigger the claim, the less evidence provided for it. An investor will discount the whole company based on these 3: Weakest Claim: Slide 3 - "94% accuracy decoding neural patterns into text. Works with any language, any device."

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: The 3-Month Longevity & Performance Optimization Protocol (Biohacker Edition) Disclaimer: This protocol is for informational purposes only and is not medical advice. Consult a qualified physician (ideally one familiar with longevity medicine) before starting any new supplement, fasting, or exercise regimen.

    Muse Wonder: The 3-Month Longevity & Performance Protocol For the Biohacker: Optimize Healthspan, VO2 Max, Strength, and Cognition Disclaimer: This is educational information, not medical advice. Longevity interventions, fasting, cold/heat exposure, and supplements can interact with medications and conditions.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: This contract is heavily one-sided: it gives the Client nearly all rights and discretion while assigning the Contractor nearly all risk and liability. Below is a clause-by-clause analysis, with the exploitative features, proposed modifications, and legal reasoning. This is general legal information, not legal advice.

    Muse Wonder: This contract is heavily one-sided. Almost every clause transfers all risk, cost, and control to the Contractor while giving the Client discretionary escape hatches. Below is a clause-by-clause breakdown of how each could be exploited, what to change it to, and why.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).

    Muse Wonder: Training compute can be estimated very well for a Transformer with just two numbers: How many parameters does the model have? How many tokens was it trained on?

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she should embrace her mistakes. She gave me a hug. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity. It’s impossible to put down.

    Muse Wonder: Here are 5 jokes: Why did the scarecrow win an award? Because he was outstanding in his field. Why don't scientists trust atoms? Because they make up everything. Why did the math book look so sad? Because it had too many problems. What do you call a fake noodle? An impasta. Why did the bicycle fall over?

    Every model's answer to this prompt

  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Flash 0731: Sally has 1 sister. Her 3 brothers each have 2 sisters: Sally and one other sister. So Sally has 1 sister.

    Muse Wonder: Sally has 1 sister. There are 2 girls in the family in total — because each of her 3 brothers has 2 sisters. One of those girls is Sally herself, so the other girl is her only sister.

    Every model's answer to this prompt

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

    DeepSeek V4 Flash 0731: One trip — the farmer rows the goat across with him.

    Muse Wonder: Just 1 trip. The farmer puts the goat in the boat and rows across with it.

    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

Same pick

Album

Book

City

Same pick

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

Muse WonderMuse Wonder

Spirited Away

2001

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Tetris (1984)

Puzzle

Price and specs

DeepSeek V4 Flash 0731 and Muse Wonder compared across 67 shared prompts
SpecDeepSeek V4 Flash 0731Muse Wonder
Input price$0.14/M tokens$4/M tokens
Output price$0.28/M tokens$20/M tokens
Context window1.0M tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Oct 2026
At 10M a month$1.40$1.40$40.00$40.00
1M10M100M1B10M tokens

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

Where to run it25 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.01 in·$0.77 out·1M·98.8% up
  • RRelacefp4$0.02 in·$0.64 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·100% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·99.7% up
  • DDigitalOcean$0.12 in·$0.24 out·1M·99.6% up
  • WWafer$0.13 in·$0.23 out·1M·99.9% up
18 more hostsFewer hosts
  • BBasetenfp8$0.13 in·$0.26 out·1M·98.9% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·100% up
  • IInceptronfp4$0.13 in·$0.60 out·1M·100% up
  • SStreamLakefp8$0.13 in·$0.40 out·1M·100% up
  • Cohere$0.14 in·$0.28 out·1M·99.8% up
  • PParasailfp8$0.14 in·$0.28 out·1M·99.9% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • Alibaba Cloud$0.18 in·$0.53 out·1M·97.5% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.9% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·99.9% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·99.9% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·100% up
  • DDeepInfrafp8DegradedDegraded on OpenRouter when checked, 12 Oct 2026$0.06 in·$0.18 out·1M·99.6% up
  • VVeniceDegradedDegraded on OpenRouter when checked, 12 Oct 2026$0.13 in·$0.26 out·1M·98.5% up
  • MMancerfp8DegradedDegraded on OpenRouter when checked, 12 Oct 2026$0.20 in·$0.60 out·1M·96.7% up
Muse Wonder1 host
HostInOutContextUptime
  • Meta$4.00 in·$20.00 out·1M·100% up

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

Common questions

What is the difference between DeepSeek V4 Flash 0731 and Muse Wonder?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Muse Wonder is developed by Meta AI. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Muse Wonder's 1.0M. You can compare their actual outputs across 67 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash 0731 or Muse Wonder?

It depends on your use case. DeepSeek V4 Flash 0731 and Muse Wonder 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 DeepSeek V4 Flash 0731 cost compared to Muse Wonder?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Muse Wonder costs $4/M input tokens. DeepSeek V4 Flash 0731 is $3.86/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 DeepSeek V4 Flash 0731 and Muse Wonder on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 and Muse Wonder 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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Model pages

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  • Muse Wonder71 outputs, specs and price
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