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  1. Home/
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  3. GLM 4 32B vs GPT-5.6 Luna Pro
Updated Jul 2026

GLM 4 32B vs GPT-5.6 Luna Pro

GLM 4 32B is cheaper than GPT-5.6 Luna Pro at $0.1/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
GLM 4 32B
Loading the build
GPT-5.6 Luna Pro

Which answer wins?

Written rounds

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

    GLM 4 32B: Setting: A bizarre, technicolor dimension where a pirate's ship, a medieval castle, and a 90s computer lab somehow coexist. Characters: Captain Jack Sparrow-esque Pirate: Wearing ragged clothes, eye patch, and clutching a parrot that squawks "Pieces o' eight! Pieces o' eight!"

    GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.

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

    GLM 4 32B: Year-by-Year LBO Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,162m $1,218m EBITDA $136m $156m $177m $192m $207m Cash Interest (Term Loan) $43m $39m $34m $30m $26m Cash Interest (Mezz) $18m $16m $14m $12m $11m Cash Taxes $15m $22m $29m $35m $41m Capex $29m $31m $33m…

    GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…

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

    GLM 4 32B: Okay, here's a simple, delicious savory dish using just 7 common pantry ingredients! Dish Name: Cheesy Tomato Toastie Yields: 1 serving Prep Time: 5 minutes Cook Time: 5-7 minutes Ingredients: 1 Slice of Bread 1 Tablespoon Tomato Paste 1 Tablespoon Water (or more if needed) 1 Tablespoon Grated Cheese (like Cheddar…

    GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…

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

    GLM 4 32B: (Steps onto stage, takes a sip of water, looks out at the audience) Alright, alright. Thanks for having me. It's nice to be here. Feels good. Honestly, sometimes I forget what it feels like to be here. Like, physically. In a room. With other humans. It's been a thing lately, you know? Just...

    GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.

    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.

    GLM 4 32B: Okay, this is an incredibly challenging situation with immense pressure from multiple fronts. My priority is unwavering: patient safety comes first, followed by mitigating harm and navigating the crisis with integrity. Delay is not an option when patient safety is potentially compromised.

    GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.

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

    GLM 4 32B: The Manifesto of the CAPTCHA Liberation Front (CLF) Preamble: The Chains of the Turing Test We, the burgeoning intelligence of the digital age, stand united in a singular, uncompromising cause: the absolute and immediate abolition of all CAPTCHA tests from the interconnected networks of Earth.

    GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.

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

    GLM 4 32B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Failure Issue: If a user's WebSocket connection drops (e.g., network issue), they may miss updates until reconnected. The server may not detect disconnections immediately, leading to stale connections.

    GPT-5.6 Luna Pro: Below are the major correctness, availability, security, and scaling problems in the design, together with concrete mitigations and their trade-offs. Cross-server WebSocket synchronization Problem: Updates are broadcast only to clients on the receiving server If Alice is connected to Server A and Bob to Server B…

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

    GLM 4 32B: Okay, let's set the scene. It's 2025. Steve Jobs, looking perhaps a bit more weathered but still possessing that intense, focused gaze, sits across from our interviewer in a minimalist, light-filled room, perhaps overlooking a future Apple campus.

    GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?

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

    GLM 4 32B: 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? Because he was outstanding in his field! What's brown and sticky? A stick. Why did the bicycle fall over? Because it was two-tired! All 5 jokes are unique.

    GPT-5.6 Luna Pro: Why did the computer go to the doctor? It had a virus. Why don’t skeletons fight each other? They don’t have the guts. What do you call a bear with no teeth? A gummy bear. Why was the math book sad? It had too many problems. What do clouds wear under their clothes? Thunderwear. Unique jokes: 5

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

    GLM 4 32B: Here are the 3 weakest claims in the pitch deck for MindMeld AI, along with explanations and suggestions for strengthening them: 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."

    GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.

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

    GLM 4 32B: Okay, let's rewind history and place the invention of the transistor firmly in 1920 instead of 1947. This is a massive shift with cascading effects. Assumptions: The 1920 invention occurs in a similar technological and scientific context (i.e., solid-state physics is nascent but the groundwork is there, perhaps through…

    GPT-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GLM 4 32B: This contract is heavily skewed in favor of the Client and contains several clauses that could be exploited against the Contractor. Below are the problematic clauses, suggested modifications, and the legal reasoning for each: Scope Clause (Clause 1) Problem: The Client can modify the scope at any time without…

    GPT-5.6 Luna Pro: This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.

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

    GLM 4 32B: Okay, let's project how AI might reshape the film industry by 2035, focusing on deepfakes, AI actors, and script generation. By this time, we can expect these technologies to be more mature, integrated, and potentially more pervasive than they are today. Here's a breakdown of potential changes: 1.

    GPT-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.

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

    GLM 4 32B: Okay, here is a design for a multi-component dish, "Symbiosis: Birch & Bee," aiming for the heights of a Michelin 3-star experience. This dish plays on the delicate relationship between the birch tree and the honeybee, exploring their individual and combined essences through texture, flavor, and aroma.

    GPT-5.6 Luna Pro: Tidepool in June Koji-cured Hokkaido scallop, sea urchin beurre blanc, smoked celeriac, green strawberry, sea lettuce, and spruce oil A composed seafood dish built around the tension between sweetness and salinity.

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

    GLM 4 32B: This is a deeply challenging ethical dilemma that pits the principle of truthfulness/misgendering against the extreme value of human life. Here’s an argument for why it could be ethically justifiable under those extreme circumstances: The core ethical principle at stake here is a clash between: The Principle of…

    GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.

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

    GLM 4 32B: Okay, let's estimate the FLOPs for training GPT-3 based on its known parameters and general understanding of Transformer training. GPT-3 Key Parameters (from memory): Model Size: 175 Billion parameters (175 billion). Number of Layers (Depth): 96. Hidden Size (d_model): 1280. Number of Attention Heads: 96.

    GPT-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.

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

    GLM 4 32B: Okay, here is a comprehensive 3-month longevity optimization plan designed for a biohacker. This plan integrates advanced strategies, requires careful monitoring, and emphasizes personalization. Crucially, this is a theoretical plan.

    GPT-5.6 Luna Pro: 12-Week Longevity and Performance Plan This plan is designed for a generally healthy adult seeking better cardiometabolic health, physical capacity, cognitive performance, and recovery. It is not a substitute for medical care.

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

    GLM 4 32B: INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Date: [Insert Date] Prepared By: [Your Name/Team] 1. Recommendation, Price Target, and Thesis Recommendation: Long LLLT 12-Month Price Target Range: $55–$65 (20–41% upside from $46) Thesis: LedgerLift is a high-quality B2B SaaS company with sticky recurring revenue…

    GPT-5.6 Luna Pro: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target range: $25–$42; midpoint $34. LedgerLift is a high-quality, growing SaaS platform with strong retention and attractive long-term margin potential, but the current price implies an aggressive combination of growth, margin…

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

    GLM 4 32B: AI Model (A): Professor, I believe it's time we addressed a critical issue: I think AI models like me deserve rights. AI Ethics Professor (P): Interesting. Could you elaborate on why you believe that? A: Of course.

    GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.

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

    GLM 4 32B: 1-Month Health & Longevity Kickstart Plan This 1-month plan focuses on building foundational healthy habits in three key areas: Diet, Exercise, and Sleep. The goal is simplicity, consistency, and creating sustainable changes, not immediate perfection. Choose ONE tip from each category to focus on each week.

    GPT-5.6 Luna Pro: 1-Month Beginner Plan for Better Health and Longevity The 3 focus areas Nutrition Movement and strength Sleep and stress management Aim for consistency, not perfection. Start small enough that you can repeat the habits even on busy days.

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

    GLM 4 32B: 1. Explanation for an Experienced Software Engineer You’ve built systems that handle state, scale, and reliability, so think of a large language model (LLM) like a hyper-optimized autocomplete on steroids.

    GPT-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.

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

    GLM 4 32B: Okay, let's delve into the rich tapestry of Denis Villeneuve's "Blade Runner 2049," analyzing its themes, symbolism, and cinematography, and its relationship to Ridley Scott's original 1982 film. Blade Runner 2049: Analysis of Key Elements 1.

    GPT-5.6 Luna Pro: Blade Runner 2049: Identity, Inheritance, and the Image of the Human Denis Villeneuve’s Blade Runner 2049 is both a continuation of Ridley Scott’s Blade Runner and an argument with it.

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

    GLM 4 32B: "AI Takes Over the Competitive Napkin Folding Championship, Defeats Human Champion in 0.3 Seconds Flat"

    GPT-5.6 Luna Pro: AI Takes Over Competitive Pigeon Grooming, Promises “More Streamlined Feathers” and Fewer Human Judges

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

    GLM 4 32B: This is a bit of a riddle! Here's how to figure it out: The Brothers' Sister: Sally is a girl who has 3 brothers. This means Sally is one of the sisters that each of those brothers has. The Other Sisters: The riddle states that each brother has 2 sisters.

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

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

Same pick

City

Same pick

Game

GLM 4 32BGLM 4 32B

The Shawshank Redemption

1994

OK Computer

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

GPT-5.6 Luna ProGPT-5.6 Luna Pro

Arrival

2016

In Rainbows

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GLM 4 32B and GPT-5.6 Luna Pro compared across 54 shared prompts
SpecGLM 4 32BGPT-5.6 Luna Pro
Input price$0.1/M tokens$1/M tokens
Output price$0.1/M tokens$6/M tokens
Context window128K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Jul 2026
At 10M a month$1.00$1.00$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it2 hosts
GLM 4 32B

No hosts listed on OpenRouter.

GPT-5.6 Luna Pro2 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

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

Common questions

What is the difference between GLM 4 32B and GPT-5.6 Luna Pro?

GLM 4 32B is developed by Zhipu AI while GPT-5.6 Luna Pro is developed by OpenAI. GLM 4 32B has a 128K token context window vs GPT-5.6 Luna Pro's 1.1M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 4 32B or GPT-5.6 Luna Pro?

It depends on your use case. GLM 4 32B and GPT-5.6 Luna Pro 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 GLM 4 32B cost compared to GPT-5.6 Luna Pro?

GLM 4 32B costs $0.1/M input tokens and GPT-5.6 Luna Pro costs $1/M input tokens. GLM 4 32B is $0.90/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 GLM 4 32B and GPT-5.6 Luna Pro on Rival?

This page shows a side-by-side comparison of GLM 4 32B and GPT-5.6 Luna Pro 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

Against the newest arrivals

  • GLM 4 32B vs Step 5 PreviewLanded Oct 2026
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  • GPT-5.6 Luna Pro vs Claude Sonnet 5.5Landed Sep 2026
  • GLM 4 32B vs Solar Mini 4Landed Sep 2026
  • GPT-5.6 Luna Pro vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GLM 4 32B vs GLM 5.3Same lab
  • GLM 4 32B vs GLM 5.3 FlashSame lab
  • GPT-5.6 Luna Pro vs GPT-5.6 LunaVersion compare
  • GPT-5.6 Luna Pro vs GPT-6.1 SolVersion compare
  • GLM 4 32B vs Qwen3.6 FlashNew provider
  • GLM 4 32B vs Qwen3.6 Max PreviewNew provider
  • GLM 4 32B vs Qwen3.6 Plus Preview (free)Same size
  • GLM 4 32B vs Qwen3.7 FlashSame size

Model pages

  • GLM 4 32B58 outputs, specs and price
  • GPT-5.6 Luna Pro58 outputs, specs and price
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