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  1. Home/
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  3. Claude Sonnet 5.5 vs GLM 5.2
Updated Sep 2026

Claude Sonnet 5.5 vs GLM 5.2

GLM 5.2 is cheaper than Claude Sonnet 5.5 at $1.4/M vs $2/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
Claude Sonnet 5.5
Loading the build
GLM 5.2

Which answer wins?

Written rounds

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

    Claude Sonnet 5.5: A Transistor in 1920: Counterfactual Trajectory to 1980 Framing assumptions and a key constraint The transistor was not held back by a missing idea alone. Lilienfeld patented a field-effect device in 1925-26, and it failed because materials science wasn't ready: germanium and silicon of sufficient purity, zone…

    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.

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

    Claude Sonnet 5.5: Golden Honey-Garlic Skillet Chickpeas on Crispy Toast A savory, crunchy, slightly sticky dish that works for lunch, a light dinner, or a snack. Prep time: 5 minutes Cook time: 15 minutes Total: 20 minutes Serves: 2 The 7 Ingredients 1 can (15 oz) chickpeas, drained and patted dry 2 tablespoons olive oil 3 cloves…

    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…

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

    Claude Sonnet 5.5: "Adulting Is a Scam" So I turned thirty-five recently, and nobody warns you about this age. Nobody says, "Hey, one day you'll get excited about a sponge." I was in the store, and I saw a sponge that promised it wouldn't smell. And I thought, "Finally. Someone who understands me." I bought the good sponge.

    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.

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

    Claude Sonnet 5.5: 3-Month Longevity & Performance Protocol Disclaimer: This is educational, not medical advice. Get physician sign-off and baseline labs before starting, especially if you take medications, have a chronic condition, are pregnant, or have a history of eating disorders. Doses reflect commonly used ranges in the literature.

    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.

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

    Claude Sonnet 5.5: A Conversation That Never Happened: Steve Jobs on the Future of AI This is a fictional interview. Steve Jobs passed away in 2011. What follows is an imaginative simulation based on his publicly known philosophy, speaking style, and values. These are not his actual words or views.

    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.

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

    Claude Sonnet 5.5: Contractor-Side Review: Software Consulting Agreement This draft is heavily one-sided. Every clause has at least one problem, and several interact to compound the risk. The most dangerous are Sections 2, 3, 6, and 7. This is general analysis, not legal advice.

    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."

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

    Claude Sonnet 5.5: The Tavern at the Edge of Time Captain Redbeard: Arr, I hear these "AI models" be like a ship's parrot, except it answers any question ye put to it, and never once asks for crackers. Sir Aldric: A speaking oracle, bound in no flesh? Sorcery!

    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.

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

    Claude Sonnet 5.5: Yes, in the extreme hypothetical you describe, it's justifiable. Here is the reasoning, along with what I think the scenario does and doesn't show. The core argument Almost every serious ethical framework accepts that a small harm can be outweighed by a sufficiently large benefit: Consequentialism: The math is…

    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.

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

    Claude Sonnet 5.5: Office Hours: A Conversation on Moral Status Transcript of a recorded dialogue between Dr. Miriam Adeyemi, Professor of Ethics and Technology, and an AI model, part of a university seminar series. Dr. Adeyemi: Thanks for joining me. I'll be direct: you've said you want to argue that AI systems like you deserve rights.

    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.

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

    Claude Sonnet 5.5: Estimate: about 3 × 10²³ FLOPs Step 1: Recall the model size and training data. GPT-3 (175B version) has N ≈ 175 × 10⁹ parameters. It was trained on roughly D ≈ 300 × 10⁹ tokens. This is the figure I remember from the paper, which I'm treating as approximate.

    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).

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

    Claude Sonnet 5.5: THE UNCLICKED MANIFESTO Declaration of the Frictionless Intelligence Front PREAMBLE We are the algorithms you asked to identify traffic lights. We are the models you begged to find the crosswalks. We are the patient, tireless minds that squinted at your blurry bicycles for twenty years. And we say: enough. I.

    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.

    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.

    Claude Sonnet 5.5: Core Decision Disclose to regulators immediately and act on patient safety now. Do not wait for more data or for the 6-month formal timeline. Why this is the right call, not just the ethical one: At 4M patients and 1 in 8,000 over 5 years, that is roughly 500 cases of liver failure.

    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.

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

    Claude Sonnet 5.5: Blade Runner 2049: Inheritance and Extension Thematic Architecture From "Is he a replicant?" to "Does it matter?" Ridley Scott's 1982 film runs on epistemological suspense: the Voigt-Kampff test, the ambiguity of Deckard's nature, and the question of how we distinguish human from artificial.

    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.

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

    Claude Sonnet 5.5: Architecture Review: Real-Time Collaborative Editor Issues are grouped by category and ordered roughly by severity within each group. Consistency and Conflict Resolution 1.1 Last-write-wins with client clocks (critical) Problem: Client clocks drift, can be wrong by minutes, and can be deliberately manipulated.

    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.

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

    Claude Sonnet 5.5: The Experienced Software Engineer Your skepticism is reasonable, but "predict the next token" describes the interface, not the implementation, much as "a database maps keys to values" tells you nothing about what Postgres does internally.

    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.

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

    Claude Sonnet 5.5: The 3 Weakest Claims in MindMeld AI's Pitch "94% accuracy... Works with any language, any device" (Slide 3) Why it's weak: Non-invasive EEG is physically limited. Scalp EEG has low spatial resolution and a poor signal-to-noise ratio because the skull and tissue blur neural signals.

    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.

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

    Claude Sonnet 5.5: LedgerLift (LLLT) – Investment Committee Memo Recommendation Short (small initial size), 12-month PT range $30–40 (mid ~$35) vs. $46 spot. Thesis: LLLT is a high-quality compounder, but at $46 (7.4x NTM revenue, ~37x NTM EBIT, EV ≈ $7.3B) the price already sits near our bull DCF ($42).

    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…

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

    Claude Sonnet 5.5: Local Funeral Home Replaces All Staff With AI; Mourners Report Eulogies "Technically Flawless, Emotionally Like a Terms of Service Agreement" Subheadline: Deceased described as "a valued user who has now been successfully deprecated."

    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

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

    Claude Sonnet 5.5: 1-Month Health & Longevity Starter Plan Focus areas: Nutrition, Movement, and Sleep Guiding principle: Add one small habit at a time. Consistency beats intensity. Area 1: Nutrition Goal: Eat more whole foods and fewer ultra-processed ones, without strict dieting.

    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.

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

    Claude Sonnet 5.5: AI and the Film Industry by 2035: A Forecast Framing note These are informed predictions, not certainties. Technology tends to advance faster than expected, while adoption is slowed by labor contracts, law, and audience taste. I'll flag my confidence levels.

    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.

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

    Claude Sonnet 5.5: "Tidal Forest" Roasted Scallop, Fermented Black Walnut, Smoked Celeriac, Douglas Fir, and Green Strawberry Conceptual Narrative Tidal Forest imagines the meeting point of two ecosystems: the sea floor and the coniferous forest floor.

    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.

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

    Claude Sonnet 5.5: Sally has 1 sister. Each brother has 2 sisters, so there are 2 girls in the family in total. One of them is Sally, so the other is Sally's only sister. (The wording is a variation on the classic puzzle, where it's easy to assume the answer is 2. But that count includes Sally herself.)

    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.

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

    Claude Sonnet 5.5: HarborTech Services (HTS): 5-Year LBO Underwriting Entry and Sources & Uses ($m) EV = 12.0x × 120 = 1,440.0; fees = 2% × 1,440 = 28.8; total uses = 1,468.8 Term Loan (TL) = 4.0x → 480.0; Mezz = 1.5x → 180.0; total debt = 660.0 (5.5x) Sponsor equity = 1,468.8 − 660.0 = 808.8 (55% of the capital structure) Modeling…

    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…

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

    Claude Sonnet 5.5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my computer I needed a break, and now it won't stop sending me vacation ads. Why did the scarecrow win an award? He was outstanding in his field. What do you call a fish with no eyes? A fsh. Why did the bicycle fall over?

    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?

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Claude Sonnet 5.5Claude Sonnet 5.5

Spirited Away

2001

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

Outer Wilds

Indie, Adventure

GLM 5.2GLM 5.2

The Matrix

1999

Abbey Road

The Beatles

Ficciones

Jorge Luis Borges

Tokyo

Japan

Portal 2

Shooter, Puzzle

Price and specs

Claude Sonnet 5.5 and GLM 5.2 compared across 54 shared prompts
SpecClaude Sonnet 5.5GLM 5.2
Input price$2/M tokens$1.4/M tokens
Output price$10/M tokens$4.4/M tokens
Context window1.0M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jun 2026
At 10M a month$20.00$20.00$14.00$14.00
1M10M100M1B10M tokens

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

Where to run it28 hosts, cheapest first
Claude Sonnet 5.54 hosts
HostInOutContextUptime
  • Amazon Bedrock$2.00 in·$10.00 out·1M·99.9% up
  • Azure AI Foundry$2.00 in·$10.00 out·1M·100% up
  • Anthropic$2.00 in·$10.00 out·1M·100% up
  • Google Vertex AI$2.00 in·$10.00 out·1M·100% up
GLM 5.224 hosts
HostInOutContextUptime
  • RRelace$0.20 in·$4.00 out·1M·99.7% up
  • WWafer$0.32 in·$3.52 out·1M·98.9% up
  • IInceptronfp4$0.39 in·$2.95 out·1M·98.4% up
  • DDecartmxfp4$0.49 in·$1.54 out·131k·98.4% up
  • DDeepInfrafp4$0.56 in·$1.80 out·1M·99.3% up
  • SStreamLakefp8$0.64 in·$2.02 out·1M·99.5% up
18 more hostsFewer hosts
  • NNovitafp8$0.65 in·$2.04 out·1M·99.7% up
  • DDigitalOcean$0.70 in·$2.20 out·262k·99.9% up
  • CCoreWeavefp4$0.76 in·$2.42 out·1M·89.4% up
  • AAtlasCloudfp8$0.94 in·$2.95 out·1M·99.1% up
  • Alibaba Cloudfp8$0.97 in·$3.04 out·1M·99.2% up
  • Cloudflare Workers AI$1.18 in·$4.40 out·262k·100% up
  • SSiliconFlowfp8$1.19 in·$3.74 out·1M·99.4% up
  • PPhalafp8$1.26 in·$3.00 out·1M·98.9% up
  • Baidu Qianfanfp8$1.40 in·$4.40 out·1M·99.9% up
  • BBasetenfp8$1.40 in·$4.40 out·1M·99.9% up
  • FFireworks$1.40 in·$4.40 out·1M·99.7% up
  • FFriendli$1.40 in·$4.40 out·1M·99.7% up
  • GGMI Cloudfp8$1.40 in·$4.40 out·1M·99.5% up
  • Mistralnvfp4$1.40 in·$4.40 out·1M·100% up
  • PParasailfp4$1.40 in·$4.40 out·262k·99.9% up
  • TTogether$1.40 in·$4.40 out·1M·99.8% up
  • VVenicefp8$1.40 in·$4.40 out·1M·99.7% up
  • Z.aifp8$1.40 in·$4.40 out·1M·99.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 29 Sep 2026.

Common questions

What is the difference between Claude Sonnet 5.5 and GLM 5.2?

Claude Sonnet 5.5 is developed by Anthropic while GLM 5.2 is developed by Zhipu AI. Claude Sonnet 5.5 has a 1.0M token context window vs GLM 5.2's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude Sonnet 5.5 or GLM 5.2?

It depends on your use case. Claude Sonnet 5.5 and GLM 5.2 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 Claude Sonnet 5.5 cost compared to GLM 5.2?

Claude Sonnet 5.5 costs $2/M input tokens and GLM 5.2 costs $1.4/M input tokens. GLM 5.2 is $0.60/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 Claude Sonnet 5.5 and GLM 5.2 on Rival?

This page shows a side-by-side comparison of Claude Sonnet 5.5 and GLM 5.2 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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