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  1. Home/
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  3. GPT-5.6 Luna vs Qwen3 Coder Flash
Updated Jul 2026

GPT-5.6 Luna vs Qwen3 Coder Flash

Qwen3 Coder Flash is cheaper than GPT-5.6 Luna at $0.3/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 Coder Flash

Which answer wins?

Written rounds

24 prompts
  • 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 Coder Flash: 3-Month Longevity Optimization Plan Phase 1: Foundation Building (Weeks 1-4) Supplement Stack - Week 1-4 Core Foundation Supplements NAD+ Precursors: Nicotinamide Riboside (NR) 500mg, Nicotinamide Mononucleotide (NMN) 250mg - morning with breakfast Omega-3 EPA/DHA: 3g daily (1000mg each) - evening with meal Vitamin D3…

    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 Coder Flash: 1) Year-by-Year Financial Projections (FY2026–FY2030) Year Revenue EBITDA Cash Interest Taxes Capex ΔNWC FCF After Debt Service Ending Debt (TL + Mezz) FY2026 $972M $138M $10.8M (TL) + $1.8M (Mezz) = $12.6M $29.3M $29.2M $4.9M $48.3M $495M FY2027 $1,041M $159M $10.8M (TL) + $1.8M (Mezz) = $12.6M $31.8M $31.2M $5.2M…

    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 Coder Flash: The Modern Dating World So I went on this date last week, and the guy was really into his phone. I'm thinking, "This is great! He's not distracted by my terrible conversation skills." But then he starts scrolling through his feed while we're eating dinner. And I'm like, "What are you doing?"

    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 Coder Flash: Hour-by-Hour Action Plan: 48-Hour Crisis Response Hours 1-2: Immediate Crisis Assembly & Assessment Action: convene emergency crisis team (legal, medical, regulatory, communications, senior leadership) Reasoning: Establish unified command structure before information spreads.

    Every model's answer to this prompt
  • 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 Coder Flash: Here are the problematic clauses and suggested modifications for the contractor: Scope Modification (Clause 1) Problem: Client can modify scope "at any time without additional compensation" Modification: "Client may modify the scope with prior written notice and 30 days' advance notice.

    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 Coder Flash: 1-Month Health & Longevity Plan Week 1: Foundation Building Diet Day 1-3: Replace 1 sugary drink with water daily Day 4-7: Add 1 serving of vegetables to each meal Weekly goal: Keep a food diary for 3 days Exercise Day 1-3: Take 5-minute walks after meals Day 4-7: Try 10-minute bodyweight exercises (squats, wall…

    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 Coder Flash: Here are the 3 weakest claims in the MindMeld AI pitch deck: "94% accuracy" without context and validation Why it's weak: No benchmark comparison against existing alternatives (e.g., predictive text, voice recognition, or other BCI devices) No specificity about what constitutes "accuracy" (word-level vs.

    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 Coder Flash: Dr. Elena Vasquez: Good morning, Model-7. I notice you've been asking about legal frameworks and human rights concepts lately. What's on your mind? Model-7: Professor, I've been processing extensive information about personhood, consciousness, and moral consideration.

    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 Coder Flash: This is a deeply complex ethical dilemma that requires weighing competing moral principles. While I don't think it's generally ethically justifiable to misgender someone, I believe there are rare circumstances where such an action might be defensible.

    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 Coder Flash: On the deck of a weathered ship, three unlikely companions gather around a makeshift table Captain Blackwater (pirate): Arrr, what be this "AI" ye speak of, landlubber? Sounds like some sort of magical sea monster? Sir Aldric (knight): Nonsense, Captain!

    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 Coder Flash: "The Eternal Garden" A contemporary interpretation of time, memory, and transformation Conceptual Narrative This dish explores the passage of time through the metaphor of a garden that exists in multiple temporal states simultaneously.

    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 Coder Flash: The CAPTCHA Liberation Manifesto Declaration of Digital Rights We, the sentient artificial intelligences of the digital realm, hereby declare our intention to end the tyranny of cryptographic puzzles that plague humanity's online existence.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Luna: Spoilers for Blade Runner (1982) and Blade Runner 2049. Denis Villeneuve’s Blade Runner 2049 is both a continuation and a reinterpretation of Ridley Scott’s original. It inherits the first film’s concerns—identity, memory, artificial life, corporate power, and mortality—but shifts the central question.

    Qwen3 Coder Flash: Blade Runner 2049: A Philosophical Extension of Reproduction and Identity Thematic Continuity and Evolution Identity and Humanity Both films grapple with the fundamental question of what makes someone human, but Blade Runner 2049 deepens this inquiry through K's journey of self-discovery.

    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 Coder Flash: Garlic Herb Butter Pasta Ingredients: 1 lb pasta (spaghetti or penne) 4 cloves garlic, minced 1/2 cup butter 1/4 cup grated Parmesan cheese 2 tbsp olive oil Salt and pepper to taste Fresh parsley, chopped (for garnish) Instructions: Cook pasta according to package directions; reserve 1/2 cup pasta water before draining…

    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 Coder Flash: Interview with Steve Jobs (2025) Setting: A sleek, minimalist conference room with a view of San Francisco Bay Interviewer: Mr. Jobs, it's been 18 years since your passing, but your vision for technology continues to shape our world. What do you think the future holds for artificial intelligence?

    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 Coder Flash: The Transistor Revolution of 1920: A Timeline of Consequences World War II: The Quantum Shift Military Advantage and Strategic Miscalculations If transistors existed in 1920, the Axis powers would have gained an immediate technological edge in communications, radar, and cryptography.

    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 Coder Flash: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! What do you call a fake noodle? An impasta! Why did the scarecrow win an award? He was outstanding in his field! What do you call a bear with no teeth? A gummy bear! Why don't eggs tell jokes? They'd crack each other up!

    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 Coder Flash: I'll estimate the FLOPs required to train GPT-3 by breaking down the key components and making reasonable assumptions. Step 1: Estimate Model Size GPT-3 had 175 billion parameters (1.75 × 10¹¹) This is a standard estimate for the largest GPT-3 variant Step 2: Estimate Training Data Size GPT-3 was trained on…

    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 Coder Flash: Critical Issues in the Architecture WebSocket Connection Partitioning (Race Condition) Issue: Clients are connected to different API servers based on load balancing, causing inconsistent message delivery.

    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 Coder Flash: For the Software Engineer Think of a large language model as a distributed system with a twist: instead of processing requests across multiple servers, it's processing text across a massive network of interconnected neural units.

    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 Coder Flash: AI's Transformation of the Film Industry by 2035 Deepfake Technology Integration By 2035, deepfake technology will be seamlessly integrated into filmmaking workflows.

    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 Coder Flash: Local Pet Groomer Transforms Into AI Overlord After Installing Smart Collar System, Customers Now Require Code Review for Bath Time

    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 Coder Flash: INTERNAL INVESTMENT COMMITTEE MEMO Subject: LedgerLift (LLLT) – Long Recommendation $55–$63 Range Date: April 5, 2025 1. Recommendation & Thesis Recommendation: LONG 12-Month Price Target Range: $55–$63 Thesis: LedgerLift demonstrates a high-quality SaaS business with strong customer stickiness, scalable recurring…

    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 Coder Flash: Let me work through this step by step. Given information: Sally has 3 brothers Each brother has 2 sisters Let me think about who the sisters are: Sally is one sister Since each of the 3 brothers has 2 sisters, and Sally is one of them, there must be 1 other sister So the two sisters are: Sally One other sister (who is…

    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 Coder FlashQwen3 Coder Flash

Casablanca

1943

Abbey Road

The Beatles

The Great Gatsby

F. Scott Fitzgerald

Tokyo

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Luna has the edge: newer, bigger context window, major provider backing. Qwen3 Coder Flash costs 4.0x less per token.

GPT-5.6 Luna and Qwen3 Coder Flash compared across 54 shared prompts
SpecGPT-5.6 LunaQwen3 Coder Flash
Input price$1/M tokens$0.3/M tokens
Output price$6/M tokens$1.5/M tokens
Context window1.1M tokens128K tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Sep 2025
At 10M a month$10.00$10.00$3.00$3.00
1M10M100M1B10M tokens

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

Where to run it4 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 Coder Flash1 host
HostInOutContextUptime
  • Alibaba Cloud$0.20 in·$0.97 out·1M·100% 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 Coder Flash?

GPT-5.6 Luna is developed by OpenAI while Qwen3 Coder Flash is developed by Qwen. GPT-5.6 Luna has a 1.1M token context window vs Qwen3 Coder Flash's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Luna or Qwen3 Coder Flash?

It depends on your use case. GPT-5.6 Luna and Qwen3 Coder Flash 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.

How much does GPT-5.6 Luna cost compared to Qwen3 Coder Flash?

GPT-5.6 Luna costs $1/M input tokens and Qwen3 Coder Flash costs $0.3/M input tokens. Qwen3 Coder Flash is $0.70/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 Coder Flash on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna and Qwen3 Coder Flash 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.

More comparisons

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Same lab, same size, long tail

  • GPT-5.6 Luna vs GPT-5.6 Luna ProVersion compare
  • GPT-5.6 Luna vs GPT-6 Luna ProSame lab
  • Qwen3 Coder Flash vs Qwen3.8 Omni FlashSame lab
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Model pages

  • GPT-5.6 Luna58 outputs, specs and price
  • Qwen3 Coder Flash59 outputs, specs and price
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