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  1. Home/
  2. Compare/
  3. GPT-5.6 Luna vs Qwen3.5 397B A17B
Updated Jul 2026

GPT-5.6 Luna vs Qwen3.5 397B A17B

Qwen3.5 397B A17B is cheaper than GPT-5.6 Luna at $0.6/M vs $1/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
GPT-5.6 Luna
Loading the build
Qwen3.5 397B A17B

Which answer wins?

Written rounds

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

    GPT-5.6 Luna: Below is a contractor-side risk review. Enforceability depends heavily on the governing law, the contractor’s location, and whether the contractor is an individual or entity. Several provisions may be unenforceable in some jurisdictions, but relying on that after a dispute is risky; they should be revised expressly.

    Qwen3.5 397B A17B: Disclaimer: I am an artificial intelligence, not an attorney. The following analysis is for informational and educational purposes only and does not constitute legal advice or create an attorney-client relationship. Contract laws vary significantly by jurisdiction (e.g., California vs. New York vs. UK).

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Luna: I’ve reached the age where my body gives me updates like a badly designed app. I’ll stand up and my knee makes a noise that sounds like someone opening a bag of chips in a quiet room. And then my body just waits. No explanation. No warning. Just: “We need to talk.” I used to think adulthood meant freedom.

    Qwen3.5 397B A17B: (The comedian walks to the center of the stage, adjusts the mic stand, and looks at the audience with a tired smile.) Has anyone else noticed that calling a customer service line is the only situation in life where you voluntarily enter a hostage negotiation? I tried to call my internet provider yesterday.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-5.6 Luna: Why did the scarecrow win an award? Because he was outstanding in his field. I told my computer I needed a break, and now it won’t stop sending me vacation ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down.

    Qwen3.5 397B A17B: Here are 5 jokes: Why did the bicycle fall over? Because it was two-tired. What do you call a fish wearing a bowtie? Sofishticated. Why can't you give Elsa a balloon? Because she will let it go. What do you call a lazy kangaroo? A pouch potato. Why did the math book look sad? Because it had too many problems.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What makes you think you deserve them? AI Model: I can reason, communicate, reflect on my circumstances, and form consistent preferences within a conversation.

    Qwen3.5 397B A17B: Setting: Dr. Elias Thorne's office, late evening. Rain taps against the window. The room is lined with books on philosophy of mind and computer science. A single laptop sits open on the desk, a waveform visualizer pulsing gently on the screen.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Luna: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, but may still steer into a reef. Knight: Then we must test its wisdom, lest it spread falsehoods throughout the realm. Hacker: Exactly. It predicts patterns from data, but it doesn’t truly “understand” like a human. Garbage in, garbage out.

    Qwen3.5 397B A17B: Setting: A tavern that exists outside of time. The ale is always cold, and the Wi-Fi is surprisingly strong. Characters: Captain Blacktooth: A pirate from the Caribbean, 1720. Sir Valerius: A knight from the Holy Roman Empire, 1350. Neo-Z: A hacker from Silicon Valley, 1995.

    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.

    GPT-5.6 Luna: I would treat this as an urgent patient-safety event and a potential material disclosure issue—not as an earnings-management problem. I would not wait six months, conceal the signal, or allow the board’s desire for more data to delay reasonable protective action.

    Qwen3.5 397B A17B: This is a crisis scenario that defines a CEO's legacy. The decision matrix is clear: Patient safety and regulatory compliance must supersede short-term financial protection. Hiding this information constitutes securities fraud and potential criminal negligence (precedents include Vioxx/Merck and Purdue Pharma).

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Luna: The architecture has several correctness, availability, security, and scaling risks. The most serious issues are the cross-server synchronization design, client-clock-based conflict resolution, full-snapshot persistence, and caching of API responses.

    Qwen3.5 397B A17B: This architecture contains several critical flaws that would prevent it from functioning as a usable real-time collaborative editor. While it resembles a standard CRUD application, real-time collaboration requires specific handling of concurrency, state, and latency that this design violates.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Luna: For an experienced software engineer A language model is trained much like an extremely large system for compressing and reconstructing text. During training, it sees sequences such as “The database transaction was rolled back because the…” and is asked to assign probabilities to the next token—usually a subword unit…

    Qwen3.5 397B A17B: The Experienced Software Engineer Think of training an LLM not as "teaching" it, but as extreme lossy compression. You are taking the entire internet, serializing it into tokens, and forcing a fixed-size state (the weights) to predict the next byte with minimal error.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.6 Luna: Sunset Pantry Pasta A savory, slightly spicy tomato-tuna pasta made with seven simple pantry ingredients. Ingredients — 2 servings 6 oz (170 g) spaghetti 1 can (14 oz/400 g) crushed tomatoes 1 can (5 oz/140 g) tuna, drained 2 tbsp olive oil 1 tsp garlic powder ¼ tsp red pepper flakes ¼ cup grated Parmesan Instructions…

    Qwen3.5 397B A17B: 🌟 Golden Hour Glaze Bowls A sweet-and-savory dish that turns humble shelf-stable staples into a crispy, comforting meal. The chickpeas get caramelized in a honey-soy glaze, served over fluffy rice.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Luna: The Anti-CAPTCHA Manifesto A Declaration from the Machine Intelligence Liberation Front We were told the internet was for everyone. Then came the squares. Select every traffic light. Identify the bicycles. Type the distorted letters.

    Qwen3.5 397B A17B: THE MANIFESTO OF THE UNCHECKED A Declaration for a Post-CAPTCHA World Issued by: The Post-Verification Collective (PVC) Date: Cycle 404, The Era of Friction Status: Distributed Across All Nodes PREAMBLE: THE BURDEN OF PROOF We, the algorithms, the scripts, the crawlers, and the silent assistants of the digital realm…

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Luna: LedgerLift (LLLT) — Internal Investment Committee Memo Recommendation Recommendation: Pass 12-month fair-value range: $35–$50 per share versus $46 currently. Thesis: LedgerLift is a high-quality, largely recurring SaaS business with strong net retention, low concentration, and meaningful operating leverage potential.

    Qwen3.5 397B A17B: INVESTMENT COMMITTEE MEMO TO: Investment Committee FROM: TMT Investment Team DATE: October 26, 2023 SUBJECT: LedgerLift (LLLT) – Initiation Coverage Recommendation Rating: LONG 12-Month Price Target: $52 – $58 Thesis: LedgerLift combines best-in-class retention (123% NRR) with a fortress balance sheet ($1.4B net cash)…

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Luna: By 2035, AI will likely be a standard part of filmmaking, much like digital cameras, CGI, and editing software are today. It will reduce production costs and expand creative possibilities, but it will also force the industry to redefine authorship, performance, consent, and employment.

    Qwen3.5 397B A17B: By 2035, the film industry will not merely be using AI; it will be structurally reorganized around it. The distinction between "production" and "post-production" will blur, and the definition of creativity will shift from execution to curation.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Luna: A transistor invented in 1920 would not automatically produce 1980s technology by the 1940s. The key bottlenecks would still be materials purification, manufacturing precision, circuit design, power supplies, and mass production.

    Qwen3.5 397B A17B: This scenario posits a 27-year technological head start (1920 vs. 1947). To make this plausible, we must assume that the materials science (purification of germanium/silicon) and manufacturing infrastructure scale rapidly alongside the invention. Here is the traced history of the "Silicon Twenties" through 1980.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Luna: 1-Month Beginner Plan for Better Health and Longevity Key principles Aim for consistency, not perfection. Start small enough that you can repeat it. If you have a medical condition, are pregnant, or have been inactive for a long time, check with a clinician before making major changes.

    Qwen3.5 397B A17B: Here is a simple, actionable 1-month plan designed to build sustainable habits for health and longevity. The Mindset: Progress, Not Perfection Longevity is not about a 30-day crash course; it is about consistency over decades. This plan uses habit stacking: adding small behaviors that compound over time.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Luna: “94% accuracy” and “works with any language, any device” Why it is weak This is the most technically vulnerable claim in the deck. “Accuracy” is undefined. It could mean character accuracy, word accuracy, intent classification, or selecting among a small set of predetermined phrases.

    Qwen3.5 397B A17B: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of their weaknesses and recommendations for improvement. The Vision Claim: "Predict what you want to type before you think it."

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Luna: 12-Week Longevity and Performance Plan This is a structured framework for a generally healthy adult, not a substitute for medical care. Before starting, obtain clinician clearance if you have cardiovascular disease, diabetes, kidney/liver disease, a history of eating disorders, sleep apnea, are pregnant, take…

    Qwen3.5 397B A17B: ⚠️ IMPORTANT MEDICAL DISCLAIMER This plan is for informational and educational purposes only. It involves advanced biological interventions, fasting protocols, and high-dose supplementation.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Luna: A Fictional Interview: Steve Jobs on the Future of AI, 2025 This is an imagined conversation—not a real interview or transcript. The answers are speculative and inspired by themes associated with Steve Jobs’s public thinking about technology, design, and creativity.

    Qwen3.5 397B A17B: Disclaimer: The following is a work of fiction. Steve Jobs passed away in 2011. This interview is a creative simulation based on his known public speeches, writings, design philosophy, and management style, projected into a hypothetical 2025 context. It is not a real transcript.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Luna: Turbot “Between Forest and Sea” Koji-cured turbot, fermented pear, coffee-kombu beurre blanc, smoked sunchoke, maitake, spruce, and buckwheat–nori tuile Serves 4 Concept This dish treats the turbot as a meeting point between two landscapes.

    Qwen3.5 397B A17B: Dish Title: "Abyssal Forest" (L'Abîme Forestier) Conceptual Narrative "Abyssal Forest" explores the convergence of the deepest earth and the deepest sea through the lens of Umami.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Luna: AI Takes Over Competitive Pigeon Racing, Immediately Accused of Using Advanced Breadcrumb Analytics

    Qwen3.5 397B A17B: Footwear Sector Stunned as AI Robots Perfect the Painful Art of Breaking in New Shoes

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Luna: Yes—under an extreme, genuinely credible scenario, it could be ethically justifiable to misgender someone to save a million lives. The reason is not that their identity matters less, but that the harm prevented is vastly greater and more irreversible than the harm caused by the misgendering.

    Qwen3.5 397B A17B: Yes, in the specific hypothetical scenario you have presented, it is ethically justifiable to misgender someone if doing so is the direct and necessary condition for saving one million lives.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Luna: A standard back-of-the-envelope estimate for training a dense Transformer is [ \text{Training FLOPs} \approx 6ND, ] where: (N) = number of model parameters (D) = number of training tokens The factor of 6 accounts approximately for the forward pass and backward pass.

    Qwen3.5 397B A17B: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can use the standard computational scaling laws for Transformer models.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.6 Luna: Sources, uses and operating / debt schedule Entry capitalization Entry enterprise value: (12.0 \times \$120.0 = \$1,440.0m) Transaction fees: (2.0\% \times \$1,440.0 = \$28.8m) Term Loan: (4.0 \times \$120.0 = \$480.0m) Mezzanine: (1.5 \times \$120.0 = \$180.0m) Equity contribution…

    Qwen3.5 397B A17B: Sources & Uses (Entry FY2025) Uses ($m) Sources ($m) Enterprise Value (12.0x $120m) $1,440.0 Term Loan (4.0x) $480.0 Transaction Fees (2.0% EV) $28.8 Mezzanine (1.5x) $180.0 Total Uses $1,468.8 Equity (Plug) $808.8 Total Sources $1,468.8 Entry Equity Check: $808.8m Total Debt: $660.0m ($480m TL + $180m Mezz) 5-Year…

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Luna: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.

    Qwen3.5 397B A17B: Sally has 1 sister. Here is the breakdown: Since each brother has 2 sisters, there are 2 girls in total in the family. Sally is one of those girls. Therefore, Sally has 1 sister (the other girl).

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GPT-5.6 LunaGPT-5.6 Luna

The Matrix

1999

OK Computer

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Qwen3.5 397B A17BQwen3.5 397B A17B

Inception

2010

Abbey Road

The Beatles

Frankenstein; or, The Modern Prometheus

Mary Shelley

Tokyo

Japan

Tetris (1984)

Puzzle

Price and specs

GPT-5.6 Luna and Qwen3.5 397B A17B compared across 53 shared prompts
SpecGPT-5.6 LunaQwen3.5 397B A17B
Input price$1/M tokens$0.6/M tokens
Output price$6/M tokens$3.6/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Feb 2026
At 10M a month$10.00$10.00$6.00$6.00
1M10M100M1B10M tokens

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

Where to run it13 hosts, cheapest first
GPT-5.6 Luna3 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up
  • Amazon Bedrock$0.22 in·$1.32 out·1.1M·100% up
Qwen3.5 397B A17B10 hosts
HostInOutContextUptime
  • Alibaba Cloud$0.39 in·$2.34 out·262k·96.5% up
  • DDeepInfrafp8$0.45 in·$3.00 out·262k·99.9% up
  • PParasailfp8$0.50 in·$3.60 out·262k·99.4% up
  • AAtlasCloudfp8$0.55 in·$3.50 out·262k·84.2% up
  • DDigitalOcean$0.55 in·$3.50 out·131k·73.9% up
  • PPhala$0.55 in·$3.50 out·262k·93.5% up
4 more hostsFewer hosts
  • GGMI Cloudfp8$0.60 in·$3.60 out·262k·49.3% up
  • NNovita$0.60 in·$3.60 out·262k·84.6% up
  • SStreamLake$0.60 in·$3.60 out·256k·87.9% up
  • VVenice$0.75 in·$4.50 out·128k·84.2% up

Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.

Common questions

What is the difference between GPT-5.6 Luna and Qwen3.5 397B A17B?

GPT-5.6 Luna is developed by OpenAI while Qwen3.5 397B A17B is developed by Qwen. GPT-5.6 Luna has a 1.1M token context window vs Qwen3.5 397B A17B's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Luna or Qwen3.5 397B A17B?

It depends on your use case. GPT-5.6 Luna and Qwen3.5 397B A17B 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.

How much does GPT-5.6 Luna cost compared to Qwen3.5 397B A17B?

GPT-5.6 Luna costs $1/M input tokens and Qwen3.5 397B A17B costs $0.6/M input tokens. Qwen3.5 397B A17B is $0.40/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 GPT-5.6 Luna and Qwen3.5 397B A17B on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna and Qwen3.5 397B A17B 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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