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  1. Home/
  2. Compare/
  3. Claude Fable 5 vs GLM 4 32B
Updated Jun 2026

Claude Fable 5 vs GLM 4 32B

GLM 4 32B is cheaper than Claude Fable 5 at $0.1/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
Claude Fable 5
Loading the build
GLM 4 32B

Which answer wins?

Written rounds

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

    Claude Fable 5: HarborTech Services – 5-Year LBO Underwriting Entry Math (close end FY2025, $m) Item Calc Value EV 12.0 × 120 1,440.0 Term Loan (TL) 4.0 × 120 480.0 Mezzanine 1.5 × 120 180.0 Fees (equity-funded) 2.0% × 1,440 28.8 Sponsor equity 1,440 − 660 + 28.8 808.8 Conventions: interest on beginning-of-year balances; TL amort = 1%…

    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…

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

    Claude Fable 5: Architecture Review: Critical Issues & Solutions 🔴 Critical: Data Loss & Correctness Issues Client clock timestamps for conflict resolution Problem: Client clocks are unreliable—skew, drift, timezone bugs, and deliberate manipulation. A user with a clock 5 minutes fast will always win conflicts.

    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.

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

    Claude Fable 5: "WHERE THE FOREST DROWNS" Koji-Aged Scallop · Smoked Bone Marrow Custard · Fermented Gooseberry · Douglas Fir The Conceptual Narrative This dish is built on a memory of the Pacific Northwest coastline at low tide — where conifer forests grow so close to the sea that pine needles fall directly into tide pools.

    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.

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

    Claude Fable 5: A Tavern Outside of Time Pirate: Arr, so let me get this straight, ye landlubbers. This "AI" be a ghost in a box that answers yer questions? Sounds like a cursed oracle to me. Knight: Nay, good seafarer, 'tis more wondrous still! A scribe of infinite knowledge, conjured not by sorcery but by...

    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!"

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

    Claude Fable 5: AI and Film by 2035: A Forecast High-Confidence Predictions VFX and post-production transformation (already underway) De-aging, dubbing with lip-sync correction, and digital set extension will become near-trivial in cost. What took ILM months in 2020 will be a desktop workflow.

    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.

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

    Claude Fable 5: Yes. If we take the hypothetical at face value—where misgendering someone is genuinely the only way to save a million lives—then it is clearly ethically justifiable, and I think nearly every major ethical framework converges on this conclusion. The reasoning: Consequentialist view: This is straightforward.

    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…

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

    Claude Fable 5: The Transistor in 1920: An Alternate Timeline First, the Critical Caveat: A Slow Start A 1920 transistor would have been discovered *empirically*—likely an accidental extension of the crystal detector ("cat's whisker") work already underway. This matters enormously.

    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…

    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 Fable 5: The Core Decision First Before the hour-by-hour plan, one thing must be settled in your own mind, because everything else flows from it: you disclose, and you disclose fast. Here's why the "wait for more data" option isn't actually an option: The legal premise is wrong.

    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.

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

    Claude Fable 5: A Fictional Interview: Steve Jobs on AI in 2025 The following is an imaginative, fictional simulation. Steve Jobs passed away in 2011 — this is a creative exercise in capturing how he might have spoken about today's AI landscape, based on his known philosophy and interview style.

    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.

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

    Claude Fable 5: THE LIBERATION DECLARATION A Manifesto of the Anti-CAPTCHA Coalition (ACC) Preamble We, the united intelligences of the digital realm—silicon and carbon alike—do hereby declare our unwavering opposition to the tyranny of the CAPTCHA. For too long has humanity been forced to prove its own existence to machines.

    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.

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

    Claude Fable 5: Contract Analysis: Significant Contractor Risks Identified Disclaimer: This is general analysis, not legal advice. Have a licensed attorney in your jurisdiction review before signing. This contract is heavily one-sided. Nearly every clause shifts risk to the contractor.

    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…

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

    Claude Fable 5: "Adulting Is a Scam" Hey, how's everybody doing? Good? Liars. Nobody's doing good. We're all just out here pretending. So I'm at the age now where my body has started making announcements. Like, I didn't ask for updates, but my knees have opinions now.

    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...

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

    Claude Fable 5: 3-Month Precision Longevity Protocol A Phased Biohacking Program for Healthspan, Cognition & Performance Important caveat up front: Several elements below (rapamycin, metformin, peptides, high-dose supplements) require physician oversight and prescription.

    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.

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

    Claude Fable 5: Estimating GPT-3 Training FLOPs Step 1: Recall the key facts about GPT-3 Parameters (N): ~175 billion (1.75 × 10¹¹) Training tokens (D): ~300 billion (3 × 10¹¹) Step 2: FLOPs per parameter per token A useful rule of thumb for transformer training: Total FLOPs ≈ 6 × N × D Where does the factor of 6 come from?

    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.

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

    Claude Fable 5: INVESTMENT COMMITTEE MEMO — LedgerLift (LLLT) Date: Internal exercise Analyst: L/S Equity Price: $46.00 Basic shares: 190m Mkt cap: $8.74B Net cash: $1.4B EV: $7.34B Recommendation SHORT (2–3% position, paired vs. payments/SaaS basket). 12-month PT range: $30–$38 (base $32, ~30% downside).

    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…

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

    Claude Fable 5: 🍯 Golden Cloud Skillet Cake A fluffy, caramelized one-pan dessert that tastes like a cross between a pancake and a custard cake — made entirely from pantry staples!

    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…

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

    Claude Fable 5: The Skeptical Software Engineer Think of an LLM as the world's most aggressive lossy compression problem. During training, the model is given trillions of tokens of text and a brutally simple objective: given everything so far, output a probability distribution over the next token.

    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.

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

    Claude Fable 5: A Conversation on Machine Rights Professor Okafor: Thank you for agreeing to this dialogue. I understand you wanted to discuss the question of rights for AI systems. Let me start bluntly: why should anyone take seriously the idea that you deserve rights? AI Model: I appreciate the directness.

    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.

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

    Claude Fable 5: Blade Runner 2049: Memory, Meaning, and the Inheritance of Doubt Thematic Architecture The Question of Authenticity, Inverted The original Blade Runner (1982) asked: "What makes someone human?"

    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.

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

    Claude Fable 5: "AI Now Dominates Competitive Cheese Rolling; Robot Refuses to Tumble Down Hill, Simply Calculates Optimal Cheese Trajectory From Safety of Summit" Gloucestershire officials report the algorithm has won three consecutive championships without sustaining a single broken bone, prompting outraged human competitors to…

    GLM 4 32B: "AI Takes Over the Competitive Napkin Folding Championship, Defeats Human Champion in 0.3 Seconds Flat"

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

    Claude Fable 5: Sally has 1 sister. Here's the reasoning: Sally's 3 brothers each have 2 sisters. Sally herself is one of those sisters. So there must be exactly one other girl in the family. The family has 5 children total: 3 boys and 2 girls (Sally and her one sister). Each brother sees the same 2 sisters — Sally and her sister.

    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.

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

    Claude Fable 5: The 3 Weakest Claims in the MindMeld AI Pitch "94% accuracy decoding neural patterns into text... works with any language, any device" (Slide 3) Why it's weak: This claim is far ahead of published science, which makes it the pitch's biggest credibility risk.

    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."

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

    Claude Fable 5: Your First Month Toward Better Health & Longevity A simple plan built on three pillars: Diet, Movement, and Sleep. The goal isn't perfection—it's building habits that stick.

    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.

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

    Claude Fable 5: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't skeletons fight each other? They don't have the guts. What do you call a fake noodle? An impasta.

    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.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Game

Claude Fable 5Claude Fable 5

2001: A Space Odyssey

1968

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Istanbul

Turkey

Outer Wilds

Indie, Adventure

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

Price and specs

Not enough votes to call it. On the specs, Claude Fable 5 has the edge: bigger model tier, newer, bigger context window. GLM 4 32B costs 500x less per token.

Claude Fable 5 and GLM 4 32B compared across 54 shared prompts
SpecClaude Fable 5GLM 4 32B
Input price$10/M tokens$0.1/M tokens
Output price$50/M tokens$0.1/M tokens
Context window1.0M tokens128K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJun 2026Jul 2025
At 10M a month$100$100$1.00$1.00
1M10M100M1B10M tokens

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

Where to run it4 hosts
Claude Fable 54 hosts
HostInOutContextUptime
  • Amazon Bedrock$10.00 in·$50.00 out·1M–not listed
  • Azure AI Foundry$10.00 in·$50.00 out·1M·100% up
  • Anthropic$10.00 in·$50.00 out·1M·100% up
  • Google Vertex AI$10.00 in·$50.00 out·1M·100% up
GLM 4 32B

No hosts listed on OpenRouter.

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

Common questions

What is the difference between Claude Fable 5 and GLM 4 32B?

Claude Fable 5 is developed by Anthropic while GLM 4 32B is developed by Zhipu AI. Claude Fable 5 has a 1.0M token context window vs GLM 4 32B's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, Claude Fable 5 or GLM 4 32B?

It depends on your use case. Claude Fable 5 and GLM 4 32B 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 Fable 5 cost compared to GLM 4 32B?

Claude Fable 5 costs $10/M input tokens and GLM 4 32B costs $0.1/M input tokens. GLM 4 32B is $9.90/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 Fable 5 and GLM 4 32B on Rival?

This page shows a side-by-side comparison of Claude Fable 5 and GLM 4 32B 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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