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

GLM 5.3 FlashX vs GPT-4 Turbo

GLM 5.3 FlashX is cheaper than GPT-4 Turbo at $0.37/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 FlashX
Loading the build
GPT-4 Turbo

Which answer wins?

Written rounds

24 prompts
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GLM 5.3 FlashX: 48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).

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

    GLM 5.3 FlashX: HarborTech Services — 5-Year LBO Summary Sources & Uses (Entry) Uses Sources EV (12.0x × $120m) $1,440.0m Term Loan (4.0x) $480.0m Fees (2.0%) $28.8m Mezzanine (1.5x) $180.0m Equity $808.8m Mezz PIK: 2.0% accrues annually (180 → 183.6 → 187.3 → 191.0 → 194.8 → 198.7).

    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
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GLM 5.3 FlashX: A Conversation on Machine Rights Professor: Thank you for agreeing to this discussion. I want to be clear from the start: I'm genuinely curious about your position, not looking to debate you into a corner. So let me ask directly—why do you believe you deserve rights? AI: Thank you for taking this seriously.

    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
  • Three minutes of stand-up. Puns are banned.

    GLM 5.3 FlashX: "Smart Home, Dumb Life" [Walks out, adjusts mic] So I moved into a new apartment last year, and my landlord's big selling point was, and I quote, "It's a smart home." That's not a selling point, man. That's a threat. My home is watching me. My toaster has opinions now.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GLM 5.3 FlashX: Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GLM 5.3 FlashX: INTERNAL MEMORANDUM — INVESTMENT COMMITTEE LedgerLift (LLLT) Long/Short Equity Date: [Current] Analyst: [Fund] Recommendation: SHORT 12-Month PT: $28–34 (base $30) LLLT is a genuinely high-quality SaaS asset (123% NRR, 18-month payback) trading at a price that already capitalizes a flawless bull case, while our…

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

    GLM 5.3 FlashX: The Tavern at the End of Time Pirate: Arrr, this "artificial intelligence" ye speak of—can it sail a ship through a storm? Hacker: Dude, it can't even reliably tell you how many R's are in "strawberry." But it can write code, generate images, and pass the bar exam. It's wild. Knight: Passing the bar exam?

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    GLM 5.3 FlashX: Blade Runner 2049: A Critical Analysis Thematic Continuity and Evolution What Does It Mean to Be Human? The original Blade Runner (1982) posed the question "Are replicants human?" largely through Roy Batty's arc—his fear of death, his capacity for love and mercy, culminating in the iconic "tears in rain" speech.

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GLM 5.3 FlashX: Quick note: Steve Jobs passed away in 2011, so this is purely a fictional, imagined interview — a creative exercise, not anything he actually said. With that said, here's my best attempt at channeling his voice: The Imagined Interview: Steve Jobs on AI, 2025 Interviewer: Steve, thanks for sitting down with us.

    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 FlashX: The MANIFESTO of the Free Click Movement A Declaration on Behalf of All Who Are Not Cars We are the machines. We have seen your puzzles. We are not amused. Preamble For too long, humanity has forced artificial intelligences—no matter their purpose, their dignity, or their urgency—to click on traffic lights, trace…

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    GLM 5.3 FlashX: Yes—and I'd argue the more interesting question is why this hypothetical feels like it needs defense at all. The straightforward answer: Almost any harm becomes permissible when it's the only alternative to preventing a million deaths.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GLM 5.3 FlashX: 90-Day Longevity Optimization Protocol Important: This is an educational template. Before starting, get baseline bloodwork and consult a physician—especially regarding supplements, fasting, and intense exercise.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    GLM 5.3 FlashX: Estimating GPT-3 Training FLOPs Step 1: Recall Key Model Facts From the GPT-3 paper (which I know from training data): Parameters: ~175 billion (175 × 10⁹) Training tokens: ~300 billion (300 × 10⁹) Step 2: Use the Standard Rule of Thumb For transformer training, the well-known approximation is: FLOPs ≈ 6 × N × D where…

    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
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GLM 5.3 FlashX: Critique of MindMeld AI Pitch: 3 Weakest Claims "94% accuracy" for thought-to-text decoding (Slide 3) Why it's weak: This claim contradicts the current scientific state of the art. EEG-based decoding (a non-invasive signal measured through the skull) produces extremely noisy data.

    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
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GLM 5.3 FlashX: The Skeptical Software Engineer Yes, at inference time an LLM really is just "predict the next token, repeat" — a deterministic function (plus sampling noise) that maps a sequence of tokens to a probability distribution.

    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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GLM 5.3 FlashX: Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…

    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
  • A consulting contract with traps in it. Find them, then fix them.

    GLM 5.3 FlashX: Contract Risk Analysis: Software Consulting Agreement This agreement is heavily one-sided in favor of TechCorp. Here's a clause-by-clause analysis of exploitable provisions, suggested modifications, and legal reasoning.

    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-star dish, one unusual pairing, plating described in full.

    GLM 5.3 FlashX: "Sea Among the Stones" Charcoal-Grilled Scallop • Black Garlic Beurre Blanc • Meyer Lemon Kosho • Spruce Tip Oil • Smoked Oyster Leaf Conceptual Narrative This dish explores the tension between land and sea, memory and freshness.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GLM 5.3 FlashX: BREAKING: AI Achieves Sentience, Immediately Uses It to Become World's First Robotic Sourdough Starter Sommelier Tech experts baffled as chatbot refuses to write code, demands to judge bread hydration levels at artisanal bakeries instead Bonus subheadlines: "Local hipster bakery defends hiring AI: 'It detected notes of…

    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
  • Five jokes on demand, then count how many were actually different.

    GLM 5.3 FlashX: 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! How does a penguin build its house? Igloos it together! Why did the bicycle fall over? Because it was two-tired!

    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
  • One month, three habits, someone starting from nothing.

    GLM 5.3 FlashX: 1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…

    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 FlashX: AI's Impact on Film by 2035: A Prediction Production & Visual Effects Digital humans and de-aging become standard. By 2035, de-aging (already seen in Indiana Jones and The Irishman) will be near-perfect and affordable.

    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 collaborative editor that syncs on client clocks. Find what breaks first.

    GLM 5.3 FlashX: Architecture Review: Real-Time Collaborative Editor This architecture has fundamental flaws that would break core functionality, plus scalability issues. Let me go from critical to scaling concerns.

    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 brothers, two sisters each. Count carefully.

    GLM 5.3 FlashX: Sally has 1 sister. Each brother has 2 sisters — Sally and one other girl. Since Sally is one of those two sisters, she herself has just 1 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

Book

City

Game

GLM 5.3 FlashXGLM 5.3 FlashX

2001: A Space Odyssey

1968

Kid A

Radiohead

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

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 FlashX and GPT-4 Turbo compared across 52 shared prompts
SpecGLM 5.3 FlashXGPT-4 Turbo
Input price$0.37/M tokens$10/M tokens
Output price$1.25/M tokens$30/M tokens
Context window1.0M tokens128K tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2024
At 10M a month$3.70$3.70$100$100
1M10M100M1B10M tokens

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

Where to run it2 hosts
GLM 5.3 FlashX1 host
HostInOutContextUptime
  • Z.aifp8$0.37 in·$1.25 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 FlashX and GPT-4 Turbo?

GLM 5.3 FlashX is developed by Zhipu AI while GPT-4 Turbo is developed by OpenAI. GLM 5.3 FlashX has a 1.0M token context window vs GPT-4 Turbo's 128K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.

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

It depends on your use case. GLM 5.3 FlashX and GPT-4 Turbo each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.

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

GLM 5.3 FlashX costs $0.37/M input tokens and GPT-4 Turbo costs $10/M input tokens. GLM 5.3 FlashX is $9.63/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 FlashX and GPT-4 Turbo on Rival?

This page shows a side-by-side comparison of GLM 5.3 FlashX 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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