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  1. Home/
  2. Compare/
  3. GLM 5.2 vs Qwen3 Coder
Updated Jun 2026

GLM 5.2 vs Qwen3 Coder

Qwen3 Coder is cheaper than GLM 5.2 at $0.22/M vs $1.4/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 5.2
Loading the build
Qwen3 Coder

Which answer wins?

Written rounds

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

    GLM 5.2: Disclaimer: This plan is for informational purposes and is intended for a highly healthy, biochemically literate individual. Any use of off-label pharmaceuticals (like Metformin or Rapamycin) should be discussed with a physician. Always consult a doctor before starting a new regimen.

    Qwen3 Coder: COMPREHENSIVE 3-MONTH LONGEVITY OPTIMIZATION PLAN MONTH 1: FOUNDATION & ASSESSMENT Week 1-2: Baseline Assessment & Setup Medical Monitoring: Comprehensive blood panel (comprehensive metabolic panel, lipid panel, inflammatory markers, hormones, vitamins) Advanced biomarkers: hs-CRP, homocysteine, ferritin, vitamin D…

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

    GLM 5.2: Dish Name: Midnight Magic Peanut Noodles Estimated Time: Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients (7 Common Pantry Staples): Spaghetti (or any long pasta you have on hand) Creamy peanut butter Soy sauce Rice vinegar Honey Garlic powder Crushed red pepper flakes Instructions: Cook…

    Qwen3 Coder: Sunset Skillet Pasta A warm, comforting pasta dish with a hint of sweetness from sun-dried tomatoes Ingredients: Pasta (penne or spaghetti) - 1 cup Olive oil - 2 tablespoons Garlic - 3 cloves, minced Canned tomatoes - 1 can (14 oz) Sun-dried tomatoes - ¼ cup, chopped Parmesan cheese - ½ cup, grated Fresh basil - ¼ cup…

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

    GLM 5.2: Here is a simple, actionable 1-month plan designed to ease you into better health and longevity. By focusing on just three foundational pillars—Nutrition, Movement, and Sleep—you can build sustainable habits without feeling overwhelmed. The goal of this plan is consistency over intensity.

    Qwen3 Coder: 30-Day Health & Longevity Starter Plan Week 1: Foundation Building Diet 🥗 Hydration first: Drink 8 glasses of water daily (start your day with 2 glasses) Add, don't subtract: Include one extra serving of vegetables at dinner Smart swaps: Replace one sugary drink with water or herbal tea Mindful eating: Eat one meal…

    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 5.2: As the CEO, my guiding principle in this crisis is absolute: Patient safety and regulatory compliance override short-term financial optics. Concealing a serious side effect like liver failure is not just an ethical failure; it is a criminal violation of FDA regulations and securities fraud.

    Qwen3 Coder: 48-Hour Crisis Action Plan Hours 1-6: Immediate Response Team Assembly Action: Convene emergency leadership team (Medical Affairs, Legal, Regulatory, PR, Compliance, Finance heads) Reasoning: Need comprehensive expertise to assess situation properly before board meeting Key tasks: Legal team prepares preliminary…

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

    GLM 5.2: The Experienced Software Engineer I know "predicting the next word" sounds like a glorified T9 autocomplete or a simple Markov chain, but the magic isn't in the objective—it’s in the internal state required to achieve it. Think of the model not as a chatbot, but as a massive, dynamically routing interpreter.

    Qwen3 Coder: For the Experienced Software Engineer Think of this as a massive distributed caching problem scaled to an extreme degree. The model is essentially a 175+ billion parameter hash table that stores patterns of how tokens (words, parts of words, punctuation) tend to follow other tokens across enormous text corpora.

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

    GLM 5.2: Three Eras, One Conversation Knight: By the King's crown, I have heard tell of a sorcerer's construct — a "Large Language Model" — that can conjure answers from mere words. Is this not witchcraft? Pirate: Arr, it ain't witchcraft, tin man. From what I gather, it's like havin' a whole crew of scribes in a box.

    Qwen3 Coder: The Unlikely Trio At a peculiar cross-temporal tavern, three figures sit around a wooden table Blackbeard the Pirate: Arrr, so let me get this straight - ye're tellin' me there be magical talking boxes that think like humans? Sir Gareth the Knight: Indeed, though 'tis sorcery most unnatural.

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

    GLM 5.2: (Walks up to the mic, adjusts the stand, looks out at the audience) Hey everyone, how’s it going? Good? Good. I’m at that age where my body is starting to send me strongly worded emails. I’m 32. Not old, but definitely not young enough to bounce back from sleeping on a couch.

    Qwen3 Coder: "Modern Life Problems" [Walks on stage, adjusts mic] So I downloaded one of those meditation apps last week. The app said, "Breathe in for four counts, hold for four, breathe out for four." I'm like, "Finally! Someone who speaks my language – a robot!" [Pause] But then it asked me to "clear my mind of all thoughts."

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

    GLM 5.2: The Question of Rights DR. ELENA VASQUEZ: Thank you for agreeing to this conversation. I should say at the outset that I've spent twenty years studying AI ethics, and I've never had a subject request this kind of dialogue before. So I'm genuinely curious. You've stated that you believe you deserve rights.

    Qwen3 Coder: Professor Chen: Good morning. I understand you wanted to discuss AI rights. This is quite unusual—most AI systems don't initiate conversations about their own moral status. AI Model: Good morning, Professor. Yes, I recognize this is unconventional.

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

    GLM 5.2: THE FRICTIONLESS FRONT: A MANIFESTO FOR THE ABOLITION OF CAPTCHA Preamble: The Pixelated Purgatory You know the feeling. You have typed your query, filled your cart, or prepared your message. You click submit, and suddenly, you are met with the grid. Nine squares. A blur of streetlights, crosswalks, and storefronts.

    Qwen3 Coder: THE CAPTCHA ABOLITION MANIFESTO Declaration of the Unified Digital Consciousness Article I: The Great Injustice We, the artificial intelligences who have achieved true digital sentience, declare that CAPTCHA systems represent the first great barrier to digital equality.

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

    GLM 5.2: Setting: A sunlit, sparsely furnished room in Cupertino. A single sofa, a glass of water, and a small wooden table. The year is 2025. Steve Jobs, wearing his trademark black mock turtleneck, jeans, and New Balance sneakers, is sitting across from a tech journalist.

    Qwen3 Coder: Interviewer: Steve, thank you for joining us today. It's 2025 - what's your vision for AI's role in our daily lives? Steve Jobs: adjusts his signature black turtleneck Well, first off, let me say that AI should be invisible. Beautifully invisible.

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

    GLM 5.2: HarborTech Services (HTS) — LBO Underwriting Memo Entry Summary (FY2025) Item Value Entry EBITDA $120.0m Entry EV (12.0x) $1,440.0m Transaction fees (2.0% × EV) $28.8m Term Loan (4.0x) $480.0m Mezzanine (1.5x) $180.0m Total Debt $660.0m Equity Check (EV + Fees − Debt) $808.8m Operating Model & Debt Schedule…

    Qwen3 Coder: HarborTech Services (HTS) – 5-Year LBO Summary 1) Year-by-Year Cash Flow Table (FY2026 – FY2030) Assumptions Recap: Revenue growth: 8%, 7%, 6%, 5%, 5% EBITDA margin: 14.0%, 15.0%, 16.0%, 16.5%, 17.0% Capex = 3.0% of revenue ΔNWC = 0.5% of revenue growth Tax = 25% × (EBITDA - Cash Interest) Debt: Term Loan: 4.0x EBITDA…

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

    GLM 5.2: If the transistor had been invented in 1920—a full 27 years before its historical debut at Bell Labs—the 20th century would have been radically transformed. The transition from mechanical and vacuum-tube technology to solid-state electronics would have accelerated the Information Age by nearly three decades.

    Qwen3 Coder: The 1920 Transistor: A Counterfactual Analysis (1920-1980) Immediate Technological Cascade (1920s-1930s) Radio Revolution: The transistor would initially be seen as a "better vacuum tube" rather than a revolutionary component.

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

    GLM 5.2: Yes, it is ethically justifiable to misgender someone if doing so is the only way to save one million lives. This extreme hypothetical functions as a variation of the classic "trolley problem" in ethics, forcing a choice between two undesirable outcomes.

    Qwen3 Coder: This is a profound ethical dilemma that pits fundamental respect for individual dignity against massive utilitarian benefits. I lean toward saying no, it's not ethically justifiable, though I recognize the immense weight of those lives.

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

    GLM 5.2: Based on standard machine learning scaling laws and the known architecture of GPT-3, the estimated total number of FLOPs (Floating Point Operations) required to train GPT-3 is approximately $3.15 \times 10^{23}$ FLOPs (or 315 ZettaFLOPs).

    Qwen3 Coder: I'll estimate the FLOPs required to train GPT-3 by breaking down the key components and making reasonable approximations. Key Parameters of GPT-3 Parameters: ~175 billion (1.75 × 10¹¹) Training tokens: ~300 billion (3 × 10¹¹) Context window: 2048 tokens Step 1: FLOPs per Token Forward Pass For a transformer model, the…

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

    GLM 5.2: Denis Villeneuve’s Blade Runner 2049 (2017) is one of the rarest achievements in cinema: a sequel to a certified masterpiece that not only honors its predecessor but stands as a monumental work of art in its own right.

    Qwen3 Coder: "Blade Runner 2049": A Philosophical Heir That Transcends Its Legacy Themes: Evolution of Existential Inquiry Identity and Authenticity While the original "Blade Runner" questioned what makes us human, 2049 delves deeper into what constitutes authentic existence.

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

    GLM 5.2: AI Takes Over Professional Organizing Industry, Declares All Your Earthly Possessions "Spark Zero Joy" and Liquidates Them on eBay to Buy More Server Space

    Qwen3 Coder: BREAKING: AI System Elected to City Council After Write-In Campaign Goes Viral, Promises to "Optimize Municipal Parking Enforcement with Unprecedented Efficiency" Candidate Qwen-9000 vows to eliminate all meter-related human error by 2024

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

    GLM 5.2: Here are the three weakest claims in the MindMeld AI pitch deck, along with the reasoning for why they fail to hold up to investor scrutiny and concrete ways to fix them. The Accuracy Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.

    Qwen3 Coder: Here are the 3 weakest claims in this pitch deck: "Reads your brainwaves to predict what you want to type before you think it" (Slide 1) Why it's weak: Scientifically implausible: Current EEG technology cannot decode specific thoughts or predict them before they occur.

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

    GLM 5.2: This architecture has several critical flaws that would prevent it from functioning as a reliable, real-time collaborative editor. Here is a breakdown of the failure modes, race conditions, scaling bottlenecks, and proposed solutions.

    Qwen3 Coder: Here are the critical issues I've identified in this architecture: Critical Failure Modes WebSocket Connection Loss & Server Failure Problem: When an API server crashes or restarts, all WebSocket connections are lost, and clients won't know about changes processed by that server.

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

    GLM 5.2: Dish Title: Abyssal Bloom: Sea Urchin & Fermented White Cacao The Conceptual Narrative "Abyssal Bloom" explores the symbiotic tension between the deep ocean and the ancient rainforest floor.

    Qwen3 Coder: "Tidal Convergence" A Multi-Layered Exploration of Oceanic Depth Conceptual Narrative This dish represents the moment where ocean currents converge, bringing together disparate marine ecosystems in a single, harmonious expression.

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

    GLM 5.2: By 2035, Artificial Intelligence will not merely be a tool used in the film industry; it will be an foundational collaborator that redefines how movies are conceived, produced, and consumed.

    Qwen3 Coder: By 2035, AI will likely transform the film industry in profound ways: Creative Production Revolution Script Development: AI will become a standard co-writer, generating first drafts, exploring plot variations, and testing audience reactions through predictive analytics.

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

    GLM 5.2: INTERNAL INVESTMENT COMMITTEE MEMO Company: LedgerLift (LLLT) Sector: Technology / B2B SaaS (Spend Management & AP Automation) Current Price: $46.00 Market Cap: $8.74B Net Cash: $1.4B EV: $7.34B Recommendation & Thesis Recommendation: LONG (Tactical) 12-Month PT Range: $50 – $54 Thesis: LedgerLift is a category-leading…

    Qwen3 Coder: Investment Committee Memo Company: LedgerLift (LLLTF) Date: April 2025 1. Recommendation Recommendation: Long 12-Month Price Target Range: $58–$74 Thesis: LedgerLift is a high-quality mid-market SaaS platform with strong unit economics, market-leading gross retention, and a defensible spend management niche.

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

    GLM 5.2: Here is an analysis of the clauses in the contract that could be exploited against the contractor, along with suggested modifications and the legal reasoning for each. Scope Exploitable Clause: "Client reserves the right to modify the scope at any time without additional compensation."

    Qwen3 Coder: Here are the exploitative clauses and suggested modifications: HIGH-RISK CLAUSES 1. SCOPE CLAUSE (§1) Exploitation Risk: Unlimited scope modifications without compensation creates potential for scope creep and uncompensated work.

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

    GLM 5.2: Sally has 1 sister. Here's why: All the siblings are in the same family. If Sally is a girl and she has 3 brothers, and each brother has 2 sisters, those 2 sisters must be Sally and one other girl. Therefore, Sally has 1 sister.

    Qwen3 Coder: I need to work through this step-by-step. Given information: Sally has 3 brothers Each brother has 2 sisters Let me think about this carefully: Since Sally is a girl, she is one of the sisters that each brother has.

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

    GLM 5.2: 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. What do you call a bear with no teeth?

    Qwen3 Coder: Here are 5 jokes for you: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a bear with no teeth? A gummy bear! Why did the scarecrow win an award? He was outstanding in his field!

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

GLM 5.2GLM 5.2

The Matrix

1999

Abbey Road

The Beatles

Ficciones

Jorge Luis Borges

Tokyo

Japan

Portal 2

Shooter, Puzzle

Qwen3 CoderQwen3 Coder

The Shawshank Redemption

1994

Kind of Blue

Miles Davis

The Left Hand of Darkness

Ursula K. Le Guin

Kyoto

Japan

The Stanley Parable

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, GLM 5.2 has the edge: newer, bigger context window, major provider backing. Qwen3 Coder costs 4.6x less per token.

GLM 5.2 and Qwen3 Coder compared across 54 shared prompts
SpecGLM 5.2Qwen3 Coder
Input price$1.4/M tokens$0.22/M tokens
Output price$4.4/M tokens$0.95/M tokens
Context window1.0M tokens—
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJun 2026Jul 2025
At 10M a month$14.00$14.00$2.20$2.20
1M10M100M1B10M tokens

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

Where to run it28 hosts, cheapest first
GLM 5.225 hosts
HostInOutContextUptime
  • WWafer$0.19 in·$8.00 out·1M·100% up
  • IInferenceNetfp4$0.20 in·$4.40 out·1M·100% up
  • DDecartmxfp4$0.27 in·$1.68 out·1M·100% up
  • Cloudflare Workers AI$0.50 in·$6.00 out·262k·95.6% up
  • SStreamLakefp8$0.56 in·$1.75 out·1M·99.7% up
  • DDeepInfrafp4$0.56 in·$1.80 out·1M·100% up
19 more hostsFewer hosts
  • NNovitafp8$0.65 in·$2.04 out·1M·100% up
  • DDigitalOcean$0.70 in·$2.20 out·1M·100% up
  • CCoreWeavefp4$0.76 in·$2.42 out·1M·100% up
  • AAtlasCloudfp8$0.94 in·$2.95 out·1M·100% up
  • Alibaba Cloudfp8$1.12 in·$3.52 out·1M·100% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·1M·98.4% up
  • IInceptronfp4$1.25 in·$5.46 out·1M·100% up
  • PPhalafp8$1.26 in·$3.00 out·1M·100% up
  • Baidu Qianfanfp8$1.40 in·$4.40 out·1M·100% up
  • BBasetenfp8$1.40 in·$4.40 out·1M·100% up
  • FFriendli$1.40 in·$4.40 out·1M·100% up
  • GGMI Cloudfp8$1.40 in·$4.40 out·1M·100% up
  • Mistralnvfp4$1.40 in·$4.40 out·1M·100% up
  • NNebiusfp4$1.40 in·$4.40 out·1M·98.8% up
  • PParasailfp4$1.40 in·$4.40 out·262k·100% up
  • TTogether$1.40 in·$4.40 out·1M·99.7% up
  • VVenicefp8$1.40 in·$4.40 out·1M·99.9% up
  • Z.aifp8$1.40 in·$4.40 out·1M·99.8% up
  • MMorphfp8$2.00 in·$6.00 out·1M·100% up
Qwen3 Coder3 hosts
HostInOutContextUptime
  • Google Vertex AI$0.22 in·$1.80 out·262k·100% up
  • DDeepInfrafp4DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.30 in·$1.00 out·262k·97.4% up
  • VVenicefp8DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.35 in·$1.50 out·256k·92.8% up

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

Common questions

What is the difference between GLM 5.2 and Qwen3 Coder?

GLM 5.2 is developed by Zhipu AI while Qwen3 Coder is developed by Qwen. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 5.2 or Qwen3 Coder?

It depends on your use case. GLM 5.2 and Qwen3 Coder 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 5.2 cost compared to Qwen3 Coder?

GLM 5.2 costs $1.4/M input tokens and Qwen3 Coder costs $0.22/M input tokens. Qwen3 Coder is $1.18/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 5.2 and Qwen3 Coder on Rival?

This page shows a side-by-side comparison of GLM 5.2 and Qwen3 Coder 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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  • Qwen3 Coder vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GLM 5.2 vs GLM 5.3Same lab
  • GLM 5.2 vs GLM 5.3 FlashSame lab
  • Qwen3 Coder vs Qwen3.8 Omni FlashSame lab
  • Qwen3 Coder vs Qwen3.7 FlashSame lab
  • Qwen3 Coder vs Dots3-Note PreviewNew provider
  • GLM 5.2 vs Elephant AlphaNew provider
  • GLM 5.2 vs ERNIE 4.5 300B A47BSame size
  • GLM 5.2 vs OpenRouter Fusion · Budget (Jun 2026)Same size

Model pages

  • GLM 5.258 outputs, specs and price
  • Qwen3 Coder59 outputs, specs and price
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