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

GLM 4 32B vs GPT-5.6 Terra

GLM 4 32B is cheaper than GPT-5.6 Terra at $0.1/M vs $2.5/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 Terra

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 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.

    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 Terra: The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.

    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 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.

    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 Terra: Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…

    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 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.

    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 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.

    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 Terra: Fictional, imagined interview — not real quotes. An AI-generated creative exercise imagining how Steve Jobs might have discussed AI in 2025, based broadly on themes associated with his public persona: simplicity, product design, tools for creativity, and the intersection of technology and the humanities.

    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 Terra: All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.

    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 Terra: Below is a contractor-focused review. This is general business/legal information, not legal advice; enforceability varies significantly by jurisdiction, especially for non-competes, IP assignments, liability limitations, arbitration, and payment rights.

    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 Terra: Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.

    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 Terra: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break, so it started showing me vacation ads. Why did the scarecrow get promoted? He was outstanding in his field. Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call fake spaghetti?

    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 Terra: Below are the main failure modes, race conditions, correctness issues, and scaling bottlenecks in the proposed architecture, with concrete mitigations and trade-offs. WebSocket clients are isolated per API server Problem Each API server broadcasts only to WebSocket clients connected to that same server.

    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 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”

    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 Terra: Blade Runner 2049 is both a continuation and an expansion of Ridley Scott’s Blade Runner (1982). Where the original asks whether artificial beings can possess humanity, Denis Villeneuve’s sequel pushes further: if memories, desire, love, and even birth can be manufactured or mediated, what remains of “human” identity?

    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 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…

    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 Terra: Simple 1-Month Health & Longevity Starter Plan Focus on three high-impact areas: Nutrition: eat mostly whole, minimally processed foods Movement: build a consistent walking + strength habit Sleep & stress: protect sleep and create daily recovery time The goal is consistency, not perfection.

    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 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?

    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 Terra: In an extreme, tightly constrained hypothetical, it could be ethically justifiable—but only as a tragic last resort, not because misgendering becomes harmless or morally good.

    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 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…

    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 Terra: Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.

    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 Terra: “AI Replaces Lighthouse Keepers, Immediately Starts Charging Subscription Fees for Safe Passage”

    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 Terra: 3-Month Longevity, Physical Performance, and Cognitive Optimization Plan This is an evidence-informed optimization framework, not a substitute for medical care.

    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 Terra: “Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.

    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 Terra: Sally has 1 sister. The 2 sisters each brother has are Sally and her sister.

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

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 TerraGPT-5.6 Terra

Spirited Away

2001

Blue

Jonas Blue

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: newer, bigger context window. GLM 4 32B costs 150x less per token.

GLM 4 32B and GPT-5.6 Terra compared across 54 shared prompts
SpecGLM 4 32BGPT-5.6 Terra
Input price$0.1/M tokens$2.5/M tokens
Output price$0.1/M tokens$15/M tokens
Context window128K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Jul 2026
At 10M a month$1.00$1.00$25.00$25.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
GLM 4 32B

No hosts listed on OpenRouter.

GPT-5.6 Terra3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$12.00 out·1.1M·100% up
  • OpenAI$2.00 in·$12.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$13.20 out·1.1M–not listed

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 Terra?

GLM 4 32B is developed by Zhipu AI while GPT-5.6 Terra is developed by OpenAI. GLM 4 32B has a 128K token context window vs GPT-5.6 Terra'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 Terra?

It depends on your use case. GLM 4 32B and GPT-5.6 Terra 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 Terra?

GLM 4 32B costs $0.1/M input tokens and GPT-5.6 Terra costs $2.5/M input tokens. GLM 4 32B is $2.40/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 GLM 4 32B and GPT-5.6 Terra on Rival?

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