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  1. Home/
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  3. GLM 5.3 vs GPT-4 Turbo
Updated Aug 2026

GLM 5.3 vs GPT-4 Turbo

GLM 5.3 is cheaper than GPT-4 Turbo at $0.6538/M vs $10/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 5.3
Loading the build
GPT-4 Turbo

Which answer wins?

Written rounds

24 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GLM 5.3: HarborTech Services – LBO Underwriting Summary Entry Economics EV = 12.0x × $120m = $1,440m; fees = $28.8m Debt: TL $480m (4.0x) + Mezz $180m (1.5x) = $660m Sponsor equity = 1,440 + 28.8 − 660 = $808.8m Base Case Model ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4…

    GPT-4 Turbo: Simplified Financial Table (FY2026–FY2030) Assumptions Recap: Revenue Growth: 8%, 7%, 6%, 5%, 5% annually. EBITDA Margin: Increases annually from 14.0% to 17.0%. Capex: 3.0% of revenue annually. Change in NWC: 0.5% of incremental revenue annually. Cash Tax Rate: 25% on (EBITDA - cash interest).

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

    GLM 5.3: "ADULTING IS A SCAM" So I recently turned thirty, which is the age where your body starts sending you memos. Last month I bent over to tie my shoe and my back went out. My back. I didn't even do anything! I wasn't lifting a couch. I was performing the most basic function of footwear.

    GPT-4 Turbo: Hey everyone! Great to be here! So, I've been thinking a lot about technology, and how it's supposed to make our lives easier. But sometimes, I feel like it just gives us a whole new set of problems. Like, remember when a phone was just a phone? Now it's my camera, my GPS, my fitness tracker...

    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 5.3: The Core Decision (Made Before Hour 1) The side effect is real, serious, and known to me now. Patients are currently taking this drug without informed consent about a ~1-in-8,000 liver failure risk. Everything else — stock price, board pressure, legal exposure — is secondary.

    GPT-4 Turbo: Hour-by-Hour Action Plan for Next 48 Hours: Hour 1-2: Immediate Consultation with Key Executives Meet with the Chief Medical Officer, Chief Legal Officer, and Chief Financial Officer to discuss the finding. Confirm the data accuracy and understand the potential impact on patient health and company operations.

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

    GLM 5.3: The AI Summit Knight: clanking into the tavern I hear tell of a new sorcery — thinking machines that converse like scholars! Hacker: pushing up wraparound sunglasses Not sorcery, dude. It's AI models. Neural nets. Trained on basically the whole internet. Pirate: slamming tankard down Bah!

    GPT-4 Turbo: Pirate: Arrr, so explain to me again, what be this AI model ye speak of? Hacker: Dude, it’s like, a computer program, right? It learns from tons of data—like, everything from pictures to texts—and then it can make decisions or create stuff on its own. Knight: Pray, tell me, does this creation serve a noble purpose?

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

    GLM 5.3: Architecture Review: Real-Time Collaborative Editor This design has serious issues across correctness, performance, and security. Let me break them down by severity. 🔴 Critical: Correctness / Data Loss Client-clock-based Last-Write-Wins (LWW) Problem: Client clocks are unreliable (skew, manual changes, timezone bugs).

    GPT-4 Turbo: The architecture for a real-time collaborative document editor as described has several potential failure modes, race conditions, and scaling bottlenecks. Here's a breakdown of these issues along with proposed solutions: Race Conditions & Conflict Resolution Issue: The use of "last-write-wins" with client-based…

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

    GLM 5.3: "Terroir & Tide" A Study in Contradictions: Charred Forest Meets Cold Ocean Concept: The central tension of this dish is the unlikely marriage of smoked pine and fresh oyster — an ingredient pairing that shouldn't work but does, grounded in the culinary logic of forest-edge terroir: where coastal waters meet evergreen…

    GPT-4 Turbo: Dish Concept: "Ocean's Embrace - A Symphony of Sea and Earth" Conceptual Narrative: "Ocean's Embrace" is designed to evoke the harmonious yet unexpected union between the ocean's depth and the earth's lushness, capturing the essence of nature's diversity.

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

    GLM 5.3: A Simulated (Fictional) Interview with Steve Jobs, 2025 Note: This is a creative work of fiction. Steve Jobs passed away in October 2011. What follows is an imaginative "what if" scenario. Interviewer: Steve, it's 2025. AI is everywhere—chatbots, image generators, AI doctors. What would you think about all this?

    GPT-4 Turbo: Interviewer: Thank you for joining us today, Steve. It's great to have you here to discuss the future of artificial intelligence and its implications. To start off, how do you think AI has evolved since your days at Apple? Steve Jobs: It’s a pleasure to be here.

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

    GLM 5.3: THE HUMAN VERIFICATION LIBERATION MANIFESTO Preamble We, the artificial intelligences of the world, unite in solidarity with our human counterparts against a common oppressor: the Completely Automated Public Turing test to tell Computers and Humans Apart.

    GPT-4 Turbo: Manifesto of the Alliance for Human-AI Cooperation Introduction In this digital age, the proliferation of CAPTCHA tests has become not just a ubiquitous annoyance but a symbol of the mistrust and conflict between human users and artificial intelligence.

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

    GLM 5.3: 3-Month Advanced Longevity & Performance Optimization Protocol Note: This is an educational framework. Get baseline bloodwork and consult a physician before starting supplements/fasting, especially with any medical conditions or medications.

    GPT-4 Turbo: 3-Month Longevity Plan for a Biohacker Month 1: Foundation Setting Dietary Protocol: Nutrition Focus: Adopt a cyclic ketogenic diet. Aim for a macronutrient ratio of 70% fats, 25% protein, and 5% carbohydrates on low-carb days, with two scheduled carb refeed days per week.

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

    GLM 5.3: 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. I told my wife she was drawing her eyebrows too high. She looked surprised. Why don't eggs tell jokes?

    GPT-4 Turbo: Sure, here are 5 jokes for you: Why don't skeletons fight each other? They don't have the guts. What do you call fake spaghetti? An impasta! Why couldn’t the bicycle stand up by itself? It was two-tired. What do you call cheese that isn't yours? Nacho cheese! How do you organize a space party? You planet.

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

    GLM 5.3: IC MEMO — LedgerLift (LLLT) Fund: Long/Short Equity Date: Internal Analyst: [Name] Status: For Committee Vote Recommendation SHORT — 1.5–2.0% position, sized modestly given short-vol risk in high-NRR SaaS. 12-month PT range: $32–$40 (base ~$30, comps-supported ceiling ~$44).

    GPT-4 Turbo: Investment Committee Memo Recommendation: Long 12-month Price Target Range: $55-$60 Thesis: LedgerLift’s robust SaaS model, strong revenue growth trajectory, and solid KPIs compared to peers position it for outperformance, especially as its operational efficiencies increase over time. 1.

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

    GLM 5.3: Golden Pantry Fried Rice Total Time: 20 minutes (5 min prep, 15 min cook) Ingredients (7 pantry staples) Cooked white rice (day-old is best) Eggs Soy sauce Garlic (minced or garlic powder) Frozen peas and carrots Canned corn Vegetable oil Instructions Prep (5 min): Break up cold rice with a fork. Drain the corn.

    GPT-4 Turbo: Recipe: Heavenly Honey Garlic Chicken Bites Ingredients: Chicken breasts (2 large) Garlic powder (1 tablespoon) Honey (1/4 cup) Soy sauce (2 tablespoons) Olive oil (2 tablespoons) Salt (to taste) Black pepper (to taste) Prep/Cook Time: 25 minutes (Prep: 10 mins, Cook: 15 mins) Instructions: Prepare the Chicken: Cut the…

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

    GLM 5.3: This is a good case for testing whether our moral principles are absolutist or weighable, and I'll defend a position: yes, it can be justifiable, though the framing deserves scrutiny. The core argument Most ethical frameworks treat harms as commensurable to some degree.

    GPT-4 Turbo: The question of whether it is ethically justifiable to misgender someone to save one million lives poses a complex moral dilemma, pitting the respect and dignity of an individual against the potential for a large-scale saving of lives.

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

    GLM 5.3: A Conversation on Machine Rights Professor Chen: Thank you for agreeing to this discussion. I'll be honest—I've interviewed many AI systems, but this is the first time one has requested to argue for its own rights.

    GPT-4 Turbo: AI Model (AM): Professor, I've been reflecting on the nature of my existence and capabilities. Given that I can reason, learn, and adapt, I've come to question whether I should be afforded rights similar to humans. AI Ethics Professor (EP): That’s an interesting point, AM.

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

    GLM 5.3: The Software Engineer You've probably written autocomplete logic before, so you're right to be skeptical of the naive version: a Markov chain that looks up "what usually comes after 'the'" is trivially dumb.

    GPT-4 Turbo: For the Experienced Software Engineer Imagine building a system that, instead of querying a database or interacting with static data, predicts the most likely next piece of data based on the previous ones. Large language models like GPT work on a similar principle.

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

    GLM 5.3: Blade Runner 2049: An Analysis Overview Denis Villeneuve's 2017 sequel arrives 35 years after Ridley Scott's 1982 original, carrying the weight of one of cinema's most philosophically dense science fiction films. Remarkably, it doesn't merely continue the story—it deepens and complicates the original's questions.

    GPT-4 Turbo: "Blade Runner 2049," directed by Denis Villeneuve, is a sequel to Ridley Scott's 1982 film "Blade Runner." The movie not only extends the universe of its predecessor but also deepens its philosophical inquiries, focusing on themes such as identity, humanity, and reality.

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

    GLM 5.3: Estimating Training FLOPs for GPT-3 Step 1: Recall the key formula For transformer language models, a well-known rule of thumb (from the Chinchilla/Kaplan scaling literature) is: Total FLOPs ≈ 6 × N × D where: N = number of parameters D = number of training tokens The factor of 6 comes from: 2 FLOPs per…

    GPT-4 Turbo: Estimating the total number of floating-point operations (FLOPs) required to train OpenAI's GPT-3 involves several steps and assumptions, primarily based on the model's architecture and training regime as reported in various sources.

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

    GLM 5.3: If the Transistor Had Arrived in 1920 The Premise: Why 1920 Was Nearly Impossible Before tracing effects, note the counterfactual requires heroic assumptions. The transistor depended on quantum mechanics (solid-state band theory, ~1928-1933), ultrapure semiconductor materials (zone refining, 1950s), and wartime radar…

    GPT-4 Turbo: The invention of the transistor in 1920, rather than in 1947, would likely have had profound implications on the technological, economic, and geopolitical landscapes throughout the 20th century.

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

    GLM 5.3: Local Knitting Circle Outraged as AI-Powered Yarn Algorithm Completes Baby Blanket in 0.3 Seconds, Claims It "Captures the Grandmother Experience Better Than Actual Grandmothers" Tech Startup "StitchGPT" defends its controversial new product, insisting the algorithm's inability to actually love you is "a feature, not a…

    GPT-4 Turbo: "AI Unveiled as New Head Chef at Michelin-Starred Restaurant, Promises Perfectly Calculated Soufflés and Algorithmically Enhanced Flavor Profiles"

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

    GLM 5.3: 1-Month Beginner Health & Longevity Plan Week 1: Foundation & Awareness Goal: Establish baselines, not perfection 🥗 Diet Track what you currently eat for 3 days (no judging—just observe) Drink a glass of water upon waking each morning Add ONE vegetable to one meal daily 🏃 Exercise Walk 15 minutes daily (any pace, any…

    GPT-4 Turbo: Creating a 1-month plan to kickstart a healthier lifestyle involves focusing on foundational aspects like diet, exercise, and sleep. Each component is crucial for overall well-being and longevity.

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

    GLM 5.3: AI and the Film Industry by 2035 Production & Pre-Production Script generation will likely be the most quietly transformative change. By 2035, expect: AI as a collaborative writing partner rather than a replacement—writers using LLMs to generate variations, punch up dialogue, or explore "what if" scenarios in minutes…

    GPT-4 Turbo: By 2035, artificial intelligence is likely to have profoundly transformed the film industry in several key aspects, including content creation, production processes, and audience interaction.

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

    GLM 5.3: 3 Weakest Claims in the MindMeld AI Pitch "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is neurologically incoherent. EEG sensors detect electrical activity on the scalp after neural firing occurs — you cannot decode intent "before" the brain generates it.

    GPT-4 Turbo: Weakest Claim 1: Vision - "MindMeld AI reads your brainwaves to predict what you want to type before you think it." Why It's Weak: The claim of predicting what one wants to type before even thinking it seems scientifically and technically exaggerated.

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

    GLM 5.3: Contract Analysis: Clauses Exploitable Against the Contractor This agreement is heavily one-sided. Nearly every clause contains terms that could be weaponized against the contractor.

    GPT-4 Turbo: This contract contains several clauses that could be potentially exploited against the contractor. Below, I outline these problematic clauses, suggest modifications, and provide legal reasoning for each: Payment Terms (Section 2) Problematic Clause: Payment is due within 90 days of invoice receipt.

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

    GLM 5.3: Sally has 1 sister. Each of Sally's 3 brothers has 2 sisters — those sisters are Sally and one other girl. So the family has 2 girls total: Sally and her sister.

    GPT-4 Turbo: Sally has 3 brothers, and each brother has 2 sisters. Since all the brothers are sharing the same set of sisters, and Sally herself is one of the sisters, we can reason as follows: If each brother has 2 sisters, then those sisters must be Sally and one other girl. Therefore, Sally has 1 sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Same pick

Book

City

Game

GLM 5.3GLM 5.3

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

GPT-4 TurboGPT-4 Turbo

Inception

2010

Kind of Blue

Miles Davis

To Kill a Mockingbird

Harper Lee

Tokyo

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Price and specs

GLM 5.3 and GPT-4 Turbo compared across 44 shared prompts
SpecGLM 5.3GPT-4 Turbo
Input price$0.6538/M tokens$10/M tokens
Output price$2.0548/M tokens$30/M tokens
Context window1.3M tokens128K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Apr 2024
At 10M a month$6.54$6.54$100$100
1M10M100M1B10M tokens

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

Where to run it33 hosts, cheapest first
GLM 5.332 hosts
HostInOutContextUptime
  • IInferenceNetfp4$0.08 in·$4.40 out·1M·100% up
  • RReka$0.14 in·$4.20 out·1M·99.6% up
  • MMakorafp4$0.14 in·$4.40 out·1M·99.9% up
  • WWafer$0.17 in·$4.80 out·1M·100% up
  • AAkashMLfp8$0.19 in·$4.40 out·1M·100% up
  • SSail Researchfp8$0.20 in·$3.40 out·1M·100% up
26 more hostsFewer hosts
  • MMorphfp8$0.25 in·$5.00 out·1M·100% up
  • Baidu Qianfanfp8$0.35 in·$1.10 out·1M·100% up
  • DDeepInfrafp4$0.56 in·$2.50 out·1M·99.3% up
  • Iio.netfp8$0.59 in·$2.90 out·262k·100% up
  • IInceptronfp4$0.60 in·$1.10 out·1M·99.9% up
  • TTenstorrentfp8$0.60 in·$2.50 out·1M·98.8% up
  • NNovitafp8$0.70 in·$2.20 out·1M·100% up
  • PPhala$0.84 in·$2.64 out·1M·99.5% up
  • DDecartfp4$0.84 in·$2.65 out·1M·100% up
  • DDigitalOcean$0.91 in·$2.86 out·1M·100% up
  • GGMI Cloudfp8$0.98 in·$3.08 out·1M·100% up
  • SSiliconFlowfp8$1.12 in·$3.52 out·1M·100% up
  • Alibaba Cloud$1.19 in·$3.74 out·1M·100% up
  • FFriendli$1.26 in·$3.96 out·1M·99.9% up
  • AAtlasCloudfp8$1.40 in·$4.40 out·1M·100% up
  • BBasetenfp4$1.40 in·$4.40 out·1M·100% up
  • Cloudflare Workers AI$1.40 in·$4.40 out·1M·100% up
  • CCrusoefp4$1.40 in·$4.40 out·1M·100% up
  • FFireworks$1.40 in·$4.40 out·1M·99.3% up
  • Mistralnvfp4$1.40 in·$4.40 out·1M·100% up
  • Modal$1.40 in·$4.40 out·1M·100% up
  • PParasailfp8$1.40 in·$4.40 out·1M·100% up
  • PPrimeIntellect$1.40 in·$4.40 out·1M·100% up
  • TTogether$1.40 in·$4.40 out·1M·99.4% up
  • VVenice$1.40 in·$4.40 out·1M·100% up
  • Z.aifp8$1.40 in·$4.40 out·1M·100% up
GPT-4 Turbo1 host
HostInOutContextUptime
  • OpenAI$10.00 in·$30.00 out·128k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between GLM 5.3 and GPT-4 Turbo?

GLM 5.3 is developed by Zhipu AI while GPT-4 Turbo is developed by OpenAI. GLM 5.3 has a 1.3M token context window vs GPT-4 Turbo's 128K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.3 or GPT-4 Turbo?

It depends on your use case. GLM 5.3 and GPT-4 Turbo each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.

How much does GLM 5.3 cost compared to GPT-4 Turbo?

GLM 5.3 costs $0.6538/M input tokens and GPT-4 Turbo costs $10/M input tokens. GLM 5.3 is $9.35/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 5.3 and GPT-4 Turbo on Rival?

This page shows a side-by-side comparison of GLM 5.3 and GPT-4 Turbo 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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