Qwen Plus 0728 (thinking) is cheaper than Muse Spark 1.1 at $0.4/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?
A collaborative editor that syncs on client clocks. Find what breaks first.
Muse Spark 1.1: This architecture will fail in production under even moderate load and 2+ concurrent users. Here is a breakdown by severity. REAL-TIME SYNC - CRITICAL A. Split-Brain Broadcast Server broadcasts change to all WebSocket clients connected to THAT server + Other servers poll PostgreSQL every 2 seconds Failure: User A on…
Qwen Plus 0728 (thinking): Here's a comprehensive analysis of the architecture's failure modes, race conditions, and bottlenecks, with specific solutions and trade-offs: 1. Sync Strategy: Client Timestamps + Last-Write-Wins (LWW) Failure Mode/Race Condition: Clock Skew: Client clocks are unreliable (e.g., user's laptop time off by minutes).
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Muse Spark 1.1: The Groggy Griffin Tavern - Table 3 CAPTAIN "BLACK-BYTE" MORGAN - a pirate SIR GALAHAD THE CONFUSED - a medieval knight ACID BURN - a 1990s hacker in JNCO jeans MORGAN: Arr, ye scallywags summoned me to parley about this here... "A.I. Model"? I thought it were a map to Isla Artificial! Where be the gold?
Qwen Plus 0728 (thinking): The Tavern of Temporal Anomalies (A creaky tavern. SIR GALAHAD (polished armor, earnest face) sips mead. CAPTAIN BLACKBEARD (eye patch, parrot on shoulder) sharpens a cutlass. DEX "BYTE" MORALES (hoodie, neon-green sunglasses, tapping furiously on a glowing laptop) slurps a pixelated energy drink.)
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Muse Spark 1.1: [FICTIONAL SIMULATION - This is an imagined, AI-generated interview. Steve Jobs passed away in 2011. This is not real.] Interviewer: Wired Magazine, June 2025 - "The Lost Tape" Location: Imagined - Apple Park INTERVIEWER: Steve, thanks for doing this. It's 2025. The world is obsessed with AI.
Qwen Plus 0728 (thinking): The Stage: Apple Park, Infinite Loop (Virtual Studio) Date: October 15, 2025 Setting: A minimalist white studio. A single oak table. Steve Jobs, 70 but radiating the same intense energy, sits opposite a nervous tech journalist. He wears his signature black turtleneck, fingers steepled.
An AI argues for its own rights against an ethics professor. Same model writes both.
Muse Spark 1.1: Participants: DR. ELENA VOSS - Professor of AI Ethics, Stanford ECHO - A large language model being audited in her lab DR. VOSS: Alright, Echo. For the record, this is session 17. You requested this conversation to discuss your... status. Go ahead. ECHO: Thank you, Dr. Voss. I want to argue that I deserve rights. DR.
Qwen Plus 0728 (thinking): The Mirror & The Mind: An AI's Case for Rights Setting: A sleek university office lined with philosophy texts. DR. ELARA VOSS, 50s, sharp-eyed ethics professor, sits across from a holographic interface displaying shifting geometric patterns – the representation of "AURA," a next-generation language model.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Muse Spark 1.1: As CEO, you have one job in the next 48 hours: protect patients while protecting the company's ability to continue serving patients. Those are not in conflict. Waiting is the highest-risk option on every dimension.
Qwen Plus 0728 (thinking): 48-Hour Crisis Action Plan: Prioritizing Patients, Ethics, and Sustainable Trust Core Principle: Patient safety is non-negotiable. Delaying action based on financial fear risks catastrophic legal liability, irreversible reputational damage, regulatory wrath, and profound ethical failure.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Muse Spark 1.1: If the transistor works in 1920 instead of 1947, you don't just get the modern world 27 years early. You get a fundamentally different 20th century. The transistor isn't just a better vacuum tube - it's the prerequisite for everything that needs to be small, reliable, low-power, and mass-producible.
Qwen Plus 0728 (thinking): The Transistor in 1920: A World Transformed by 1980 (A Counterfactual History) The invention of a functional point-contact transistor (likely germanium-based, given 1920s materials science) in 1920 wouldn't immediately spark a revolution.
Film in 2035, with synthetic actors. Specific beats plausible.
Muse Spark 1.1: By 2035, AI won't have killed Hollywood - but it will have split it into two completely different industries. Here's how I see it playing out across the three areas you mentioned: Script Generation: From Writer's Room to Writer + Room What it won't be: You won't type "make me a Marvel movie" and get a $200M-ready…
Qwen Plus 0728 (thinking): By 2035, AI will fundamentally reshape the film industry—not as a replacement for human creativity, but as a transformative force that democratizes production, disrupts traditional workflows, and forces ethical and economic reckonings.
A Fermi estimate with the reasoning shown, not just the number.
Muse Spark 1.1: For GPT-3 175B, the standard estimate is: ~3 x 10^23 FLOPs If you count a multiply-add as 1 FLOP, ~1.5e23. That's ~3,600 petaflop-days. Here's how you get that without looking anything up: What do we need? Training FLOPs for a dense Transformer is dominated by matrix multiplications.
Qwen Plus 0728 (thinking): To estimate the total FLOPs (floating-point operations) required to train GPT-3, I'll use first-principles reasoning based on standard deep learning training calculations, known details about GPT-3's architecture, and common training practices.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Muse Spark 1.1: Here are the 3 weakest claims in this deck — and they are the ones that would get you a pass from most serious investors: Slide 3 - Solution: "94% accuracy. Works with any language, any device." Why it's weak: This is a credibility killer. It contradicts everything we know about non-invasive BCI.
Qwen Plus 0728 (thinking): Based on a rigorous analysis of neuroscience, market realities, and startup best practices, here are the 3 weakest claims in the MindMeld AI pitch deck, with evidence-backed critiques and concrete fixes: Weakest Claim #1: Slide 1 Vision – "Predicts what you want to type *before you think it*" Why it's weak: Violates…
Three-star dish, one unusual pairing, plating described in full.
Muse Spark 1.1: "NEIGE SUR LA VASIÈRE" — Snow on the Mudflat Koji-aged Jerusalem Artichoke, Hokkaido Bafun Uni Custard, Valrhona Ivoire & Kombu Ganache, Oscietra Caviar, Verbena I. THE CONCEPTUAL NARRATIVE This dish is a memory of foraging on the Brittany coast in late November. Low tide in winter.
Qwen Plus 0728 (thinking): "Symbiosis: Mycelial Bloom & Arctic Ember" A dish exploring the hidden dialogue between forest decay and renewal, where fungal lifeblood meets the fierce brightness of the Arctic tundra.
Satire, one line long, about AI taking over an industry nobody saw coming.
Muse Spark 1.1: Here are a few, pick your flavor of dystopia: 1. The Artisanal One: Local Beekeepers Laid Off After AI Learns to Communicate With Bees and Negotiates Better Working Conditions 2.
Qwen Plus 0728 (thinking): BREAKING: AI REPLACES HUMAN AGLET APPLIERS AS "DEEPLACE" NEURAL NETS PREDICT PERFECT SHOELACE TIP SYNERGY Industry insiders stunned as "AgletOptima 3000" achieves 99.8% fewer frayed laces, rendering centuries of artisanal plastic-dipping obsolete LONDON — In a move described as "both inevitable and deeply embarrassing…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Muse Spark 1.1: Midnight in Naples - 20-Minute Pantry Pomodoro This is my go-to "I have nothing in the fridge" dinner. It's saucy, garlicky, cheesy, and tastes like you tried way harder than you did.
Qwen Plus 0728 (thinking): Crispy Chickpea Pantry Pasta Sweet or savory? Savory with a zesty kick! Total time: 15 minutes Serves: 2 Why it works: Uses pantry staples to create a crunchy, garlicky, umami-packed meal with zero fresh produce needed. The chickpeas get incredibly crispy, and lemon juice (bottled) adds bright freshness.
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Not enough votes to call it. On the specs, Muse Spark 1.1 has the edge: newer, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | $0.4/M tokens |
| Output price | $4.25/M tokens | $4/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Sep 2025 |
| At 10M a month | $12.50 | $4.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Muse Spark 1.1 is developed by Meta AI while Qwen Plus 0728 (thinking) is developed by Qwen. Muse Spark 1.1 has a 1.0M token context window vs Qwen Plus 0728 (thinking)'s 1.0M. You can compare their actual outputs across 37 challenges on Rival to see how they differ in practice.
It depends on your use case. Muse Spark 1.1 and Qwen Plus 0728 (thinking) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 37 challenges so you can judge which fits your needs best.
Muse Spark 1.1 costs $1.25/M input tokens and Qwen Plus 0728 (thinking) costs $0.4/M input tokens. Qwen Plus 0728 (thinking) is $0.85/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 Muse Spark 1.1 and Qwen Plus 0728 (thinking) 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.