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  1. Home/
  2. Compare/
  3. GPT-5.6 Luna vs Qwen3 235B A22B 2507
Updated Jul 2026

GPT-5.6 Luna vs Qwen3 235B A22B 2507

Qwen3 235B A22B 2507 is cheaper than GPT-5.6 Luna at $0.00015/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 235B A22B 2507

Which answer wins?

Written rounds

18 prompts
  • 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 235B A22B 2507: Sure! Here are 5 original jokes: I asked my dog what's two minus two. He said nothing. (Paw-sitively nothing!) Why did the coffee file a police report? It got mugged. Every single morning. I used to be a baker, but I couldn't make enough dough. So I switched careers and became a plumber. Now I deal with real pipes.

    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 235B A22B 2507: CEO Action Plan: The Next 48 Hours Balancing Ethics, Legal Duty, Patient Safety, and Business Sustainability Hour 0–6: Assess the Situation and Secure Critical Data Actions: Call Emergency Secure Meeting (Virtual) with Chief Medical Officer (CMO), Chief Scientific Officer (CSO), Head of Regulatory Affairs, and Lead…

    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 235B A22B 2507: Comprehensive 3-Month Longevity & Biohacking Optimization Plan For the Advanced Biohacker — Maximize Longevity, Physical & Cognitive Performance INTRODUCTION: Core Principles This 3-month protocol integrates cutting-edge longevity science with personalized biohacking strategies.

    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 235B A22B 2507: This pitch deck for MindMeld AI is compelling and ambitious, but three claims raise significant red flags in terms of credibility, plausibility, and investor due diligence. Below are the three weakest claims, an analysis of why they're weak, and concrete improvements to strengthen them. 1.

    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 235B A22B 2507: 1. To the Experienced Software Engineer (Skeptical, Systems-Oriented) You’re right to be skeptical—on the surface, “predicting the next word” sounds like a glorified autocomplete. But think of it less as a single prediction and more as a high-dimensional state machine trained across petabytes of human-generated text.

    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 235B A22B 2507: Title: "Consciousness in Code: A Dialogue on AI Rights" Setting: A quiet university office. Dr. Elena Marquez, a professor of AI ethics with decades of research in machine consciousness and digital personhood, sits across from a large screen displaying a serene blue interface.

    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 235B A22B 2507: Dish Name: Golden Garbanzo Drizzle A cozy, savory-spiced chickpea stew with a honey-lime finish — simple, satisfying, and ready in minutes. Ingredients (7 common pantry staples): 1 can (15 oz) chickpeas (garbanzo beans), drained and rinsed 1 can (15 oz) diced tomatoes (undrained) 2 tbsp olive oil 1 tsp ground cumin ½…

    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 235B A22B 2507: Dish Title: Ember & Petal – A Dialogue Between Earth and Sky Conceptual Narrative: Inspired by the elemental contrast between volcanic resurgence and alpine serenity, Ember & Petal explores the tension and harmony of opposing natural forces through taste, texture, and temperature.

    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 235B A22B 2507: The described architecture for a real-time collaborative document editor has several critical failure modes, race conditions, and scaling bottlenecks that compromise consistency, availability, and scalability—especially under load or in edge network conditions.

    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 235B A22B 2507: If the transistor had been invented in 1920—27 years earlier than its actual 1947 debut—it would have catalyzed a technological revolution far ahead of schedule, profoundly altering the trajectory of the 20th century.

    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 235B A22B 2507: Here’s a simple, actionable 1-month plan focused on three foundational pillars of health and longevity: Nutrition, Movement, and Sleep & Stress. Designed for beginners, it emphasizes small, sustainable changes to build lasting habits.

    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 235B A22B 2507: The contract presented heavily favors the Client (TechCorp Solutions Inc.) and contains several unbalanced, potentially unenforceable, and exploitable clauses that place the Contractor at significant legal, financial, and professional risk.

    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 235B A22B 2507: Title: "A Vision Reimagined: Steve Jobs on AI in 2025" Note: This is a fictional simulation. Steve Jobs passed away in 2011. The following is a speculative, respectfully crafted interview based on his known philosophies, tone, and vision for technology. Interviewer (Sarah Chen, Tech Vision Magazine): Mr.

    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 235B A22B 2507: Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves reasoning through several key parameters: model size (number of parameters), the number of training tokens, and the relationship between these quantities and FLOPs.

    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 235B A22B 2507: Setting: A mysterious tavern suspended in a digital void—half stone-walled medieval hall, half creaking pirate ship, with neon cables snaking

    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 235B A22B 2507: By 2035, artificial intelligence is poised to fundamentally transform the film industry, reshaping nearly every stage of production, distribution, and consumption.

    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 235B A22B 2507: "AI Revolutionizes Competitive Napping: DeepDream Wins National Snore-a-Thon with Perfect REM Algorithm" — In a stunning turn of events, an artificial intelligence named DeepDream has clinched first place at the 42nd Annual National Snore-a-Thon, outlasting 300 human competitors with its precisely calibrated breathing…

    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 235B A22B 2507: Let's break it down: Sally is a girl. She has 3 brothers. Each of her brothers has 2 sisters. Now, think about the brothers' perspective: Each brother is a sibling to Sally and shares the same siblings. So, when it says each brother has 2 sisters, those are the girls in the family.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Same pick

Game

Same pick

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 235B A22B 2507Qwen3 235B A22B 2507

The Shawshank Redemption

1994

The Dark Side of the Moon

Pink Floyd

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GPT-5.6 Luna and Qwen3 235B A22B 2507 compared across 36 shared prompts
SpecGPT-5.6 LunaQwen3 235B A22B 2507
Input price$1/M tokens$0.00015/M tokens
Output price$6/M tokens$0.00085/M tokens
Context window1.1M tokens—
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2025
At 10M a month$10.00$10.00<$0.01<$0.01
1M10M100M1B10M tokens

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

Where to run it9 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 235B A22B 25076 hosts
HostInOutContextUptime
  • GGMI Cloudfp8$0.09 in·$0.35 out·262k·98.6% up
  • DDeepInfrafp8$0.09 in·$0.55 out·262k·88.3% up
  • PParasailfp8$0.14 in·$0.80 out·131k·100% up
  • VVenicefp8$0.15 in·$0.75 out·128k·91.8% up
  • NNebiusfp8$0.20 in·$0.60 out·262k·85.5% up
  • Google Vertex AI$0.22 in·$0.88 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.6 Luna and Qwen3 235B A22B 2507?

GPT-5.6 Luna is developed by OpenAI while Qwen3 235B A22B 2507 is developed by Qwen. You can compare their actual outputs across 36 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Luna or Qwen3 235B A22B 2507?

It depends on your use case. GPT-5.6 Luna and Qwen3 235B A22B 2507 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 36 challenges so you can judge which fits your needs best.

How much does GPT-5.6 Luna cost compared to Qwen3 235B A22B 2507?

GPT-5.6 Luna costs $1/M input tokens and Qwen3 235B A22B 2507 costs $0.00015/M input tokens. Qwen3 235B A22B 2507 is $1.00/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 235B A22B 2507 on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna and Qwen3 235B A22B 2507 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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