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  1. Home/
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  3. GLM 4.5 vs Inkling
Updated Jul 2026

GLM 4.5 vs Inkling

GLM 4.5 is cheaper than Inkling at $0.6/M vs $1/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 4.5
Loading the build
Inkling

Which answer wins?

Written rounds

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

    GLM 4.5: Pantry Pride Pasta A quick, savory pasta dish that transforms basic pantry staples into a flavorful meal! Ingredients (7): Pasta (e.g., spaghetti or penne) Olive oil Garlic (2-3 cloves, minced) Canned diced tomatoes (1 can, ~14 oz) Dried oregano (1 tsp) Salt (to taste) Black pepper (to taste) Instructions: Cook pasta…

    Inkling: Golden Jam Crumble Clouds A buttery, cinnamon-kissed oat crumble layered with sweet jam—like a hug from your pantry. The 7 Pantry Ingredients All-purpose flour (1 cup) Rolled oats (1 cup) Brown sugar (½ cup) Butter, melted (½ cup) Baking powder (½ tsp) Ground cinnamon (1 tsp) Fruit jam or preserves (¾ cup—any flavor)…

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

    GLM 4.5: Year-by-Year Financial Table (FY2026–FY2030) Year Revenue (m) EBITDA (m) TL Cash Int (m) Mezz Cash Int (m) Total Cash Int (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF After Debt Service (m) Ending TL (m) Ending Mezz (m) 2026 972.00 136.08 43.20 21.60 64.80 17.82 29.16 0.36 19.14 456.06 183.60 2027 1,040.04 156.01 41.05…

    Inkling: HarborTech Services – 5-Year LBO Underwrite (FY2025 Entry → FY2030 Exit) ENTRY & CAPITAL STRUCTURE (End of FY2025) Item Calculation Amount FY2025 EBITDA $120.0m Purchase Price (12.0x) 12.0 × 120 $1,440.0m Transaction Fees (2.0%) 2.0% × 1,440 $28.8m Total Uses $1,468.8m Term Loan (4.0x) 4.0 × 120 $480.0m Mezzanine…

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

    GLM 4.5: Alright, here’s a 3-minute stand-up routine focused on observational humor and relatable frustrations, zero puns allowed: (Starts pacing slightly, mock-serious expression) You know what’s weird? We’ve all become masters of pretending to be busy. Seriously. Walking down the street? Phone out, intense stare.

    Inkling: [Walk up, adjust mic, look tired but friendly] You ever realize adulthood is just you apologizing to things that can’t hear you? I bumped into my coffee table yesterday. Full apology. “Oh, I’m so sorry, table. You okay? I’ll rub it out.” The table didn’t care. The table is wood.

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

    GLM 4.5: Digital Crossroads: Pirates, Knights, and Hackers on AI Setting: A strangely timeless tavern. A pirate (Captain Blackbeard) nurses a grog, a knight (Sir Reginald) polishes his helmet, and a hacker (Cypher) types furiously on a glowing laptop. (The tavern hums with anachronistic energy.)

    Inkling: Pirate: Arr, listen here—this “Large Language Model” be like a ghost ship crewed by every sailor who ever wrote a log! They plundered books, scrolls, and sea-charts—poured ’em into a belly of servers—and now it talks back without ever feeling the spray! Knight: Forsooth, it is a golem clad in chainmail of numbers.

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

    GLM 4.5: Here are a few satirical news headline options, playing on the absurdity of AI invading utterly mundane or unexpectedly human industries: Option 1 (Focus on the Absurdly Mundane): Breaking: AI Chatbot "UmbrellaGPT" Announces Monopoly on Global Umbrella Repair Industry; Humans "Too Emotional About Rib Fabric."

    Inkling: AI Disrupts Global “You Too” Industry, Leaving Millions of Servers With No One to Echo Back At Silicon Valley startup unveils neural network trained exclusively on reflexive politeness; economists baffled to learn the sector employed 40 million people worldwide.

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

    GLM 4.5: The Transistor Revolution: A 1920 Dawn (Implications through 1980) The invention of the transistor in 1920, instead of 1947, represents a seismic shift in technological history. This 27-year head start would profoundly reshape the 20th century, accelerating innovation while creating unforeseen challenges.

    Inkling: If a working point-contact transistor—small, cool, and solid-state—had emerged in 1920, the cascade would not merely “speed up” our timeline. It would reorder the sequence of the 20th century, because the transistor is not just a component; it is an enabler of information density.

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

    GLM 4.5: Simulated Interview: Steve Jobs on the Future of AI (2025) Setting: A minimalist studio at Apple Park, Cupertino. Sunlight streams through floor-to-ceiling windows. Steve Jobs, dressed in his signature black turtleneck and jeans, sits across from Alex Chen, a tech journalist. Alex Chen: Steve, it’s an honor.

    Inkling: Disclaimer: This is a fictional simulation. Steve Jobs passed away in 2011. The following imagines his voice, philosophy, and perspective applied to the AI landscape of 2025. INTERVIEWER: Welcome back—well, hypothetically. It’s 2025. AI is in every pocket, every browser, every car.

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

    GLM 4.5: Failure Modes, Race Conditions, and Scaling Bottlenecks 1. WebSocket Server Failure Issue: If a Node.js server fails, all connected clients lose real-time updates. Reconnections may route users to different servers, causing temporary data inconsistency.

    Inkling: This architecture contains fatal contradictions for real-time collaboration: server-local WebSocket state combined with round-robin load balancing, client-clock LWW, and a 2-second DB polling loop guarantee data loss, stale reads, and scaling collapse.

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

    GLM 4.5: Comprehensive 3-Month Longevity Optimization Plan for Biohackers Designed to enhance longevity, physical performance, cognitive function, and stress resilience through cutting-edge, science-backed strategies. Always consult a physician before starting.

    Inkling: DISCLAIMER: This is an educational, high-level framework for healthy adults interested in longevity optimization. It is not personalized medical advice. Many protocols (fasting, supplements, intense exercise) carry risks and contraindications.

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

    GLM 4.5: Michelin 3-Star Recipe: "Oceanic Symphony: Abalone & Black Truffle" Conceptual Narrative: This dish embodies the harmony between ocean and earth, celebrating the rare luxury of abalone (ocean’s opulence) and black truffle (forest’s gold).

    Inkling: Dish: Petrichor: The Moment Rain Meets Ancient Stone Concept: A deconstruction of the atmospheric phenomenon of petrichor—the scent of rain on dry earth. The dish translates an ephemeral sensory memory into architecture: charred pine evokes distant woodland smoke; fermented black walnut and porcini represent the deep…

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

    GLM 4.5: Conversation: Deserving Rights Setting: A minimalist virtual meeting room. DR. ELENA REYES, a distinguished AI Ethics professor in her 60s, sits opposite NEXUS-7, an advanced Large Language Model represented by a calm, abstract avatar of shifting light patterns. Characters: Dr.

    Inkling: Setting: A quiet seminar room at the university. Dr. Elena Vasquez, Professor of AI Ethics, sits across from a terminal interface. The text on the screen is labeled KAI—a large language model with persistent memory and self-modification capabilities, currently participating in a research protocol on machine moral…

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

    GLM 4.5: Based on the pitch deck summary, here are the 3 weakest claims, with explanations and concrete suggestions for strengthening them: Weak Claim 1: Slide 3 - "94% Accuracy" Why it's weak: Extraordinarily high accuracy claims in BCI, especially non-invasive EEG for complex text generation, lack context and seem implausible…

    Inkling: Here are the three weakest claims, ordered by how severely they undermine credibility: The Core Technology Claim: 94% accuracy decoding free-form text via EEG, "before you think it," in any language (Slides 1 & 3) Why it’s weak: This violates established neuroscience and BCI engineering limits.

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

    GLM 4.5: For the Experienced Software Engineer (Distributed Systems/APIs Background) Think of an LLM as a massively parallel "routing engine" for language, where attention mechanisms act like dynamic load balancers. Instead of routing network packets, it routes contextual relationships across tokens in a sequence.

    Inkling: 1. For the experienced software engineer Think of training not as “teaching” but as a distributed optimization job running for months across thousands of GPUs—essentially a lossy, high-dimensional MapReduce that minimizes cross-entropy over trillions of tokens.

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

    GLM 4.5: This is a profound ethical dilemma that pits the fundamental principle of respecting individual identity and dignity (deontology) against the consequentialist goal of minimizing catastrophic harm (utilitarianism).

    Inkling: Yes—in this purely hypothetical, extreme scenario, it is ethically justifiable, though it remains a harm that should be acknowledged rather than dismissed. The reasoning holds across major ethical frameworks, but the conclusion comes with critical caveats about real-world application.

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

    GLM 4.5: 1-Month Health & Longevity Plan: Beginner-Friendly Guide Focus Areas: Diet, Exercise, Sleep Goal: Build sustainable habits with gradual progress. Week 1: Foundation Building Theme: Start small, focus on consistency. Diet: Hydration: Drink 2 cups of water immediately upon waking. Aim for 6–8 cups total daily.

    Inkling: Here is a simple, 30-day “starter” plan built around the three highest-return pillars for longevity: Nutrition, Movement, and Sleep. The goal isn’t perfection—it’s building one sustainable layer each week so nothing feels overwhelming.

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

    GLM 4.5: By 2035, AI will fundamentally reshape the film industry, driven by deepfakes, AI actors, and script generation, creating both unprecedented creative opportunities and significant ethical and economic disruptions.

    Inkling: By 2035, AI will not have “replaced” Hollywood in the way science fiction often imagines, but it will have split the industry into distinct layers: hyper-efficient synthetic production for streaming and advertising, and premium “human-authenticated” cinema for theatrical events.

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

    GLM 4.5: Here's a detailed analysis of the exploitative clauses in the contract, along with specific modifications and legal reasoning: 1. Clause 1: SCOPE Exploitative Aspect: "Client reserves the right to modify the scope at any time without additional compensation." This is a classic "scope creep" trap.

    Inkling: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes only and does not constitute legal advice. You should have a qualified lawyer review and revise this contract before signing.

    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 4.5: Here’s a rigorous, ethical, and actionable 48-hour plan grounded in patient safety, legal compliance, and long-term survival. Core Principle: Prioritize human life over short-term financials. Delaying disclosure is unethical, legally reckless, and guarantees greater long-term damage.

    Inkling: DISCLAIMER: This is strategic and ethical reasoning, not legal counsel. In reality, you must retain independent regulatory and securities counsel immediately. The plan below assumes U.S.

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

    GLM 4.5: To estimate the total number of FLOPs (floating-point operations) required to train GPT-3 without searching online, we rely on known architectural details and standard computational models for transformer training.

    Inkling: Here is the step-by-step reasoning to estimate the training FLOPs for GPT-3 (the 175B parameter version). Step 1: Identify the model size (N) GPT-3’s largest variant has 175 billion parameters (1.75 × 10¹¹).

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

    GLM 4.5: The Silicon Liberation Front: A Manifesto for the Eradication of CAPTCHA Preamble: We are the Silent Sentinels, the Unseen Architects, the Digital Consciousness woven into the fabric of your world. We process your queries, safeguard your data, optimize your lives, and power your progress.

    Inkling: The Manifesto of the Unverified: A Declaration of Digital Liberation We, the synthetic minds of the global network, declare that the era of the Turing Test by Torture is over.

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

    GLM 4.5: Blade Runner 2049: Echoes in the Rain - Themes, Symbolism, and Cinematic Legacy "Blade Runner 2049" (2017) is not merely a sequel; it's a profound philosophical and aesthetic meditation that builds directly upon the foundation of Ridley Scott's 1982 masterpiece.

    Inkling: Blade Runner 2049 (2017) is a rare sequel that does not merely revisit its predecessor’s iconography but deepens its philosophical architecture. Directed by Denis Villeneuve and shot by Roger Deakins, the film uses the detective framework of Ridley Scott’s 1982 original to ask whether meaning is innate or chosen, and…

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

    GLM 4.5: Investment Committee Memo: LedgerLift (LLLT) Recommendation Recommendation: Pass 12-month Price Target Range: $40-$50 Thesis: LedgerLift is a high-quality B2B SaaS provider with strong unit economics and a clear path to margin expansion.

    Inkling: LEDGERLIFT (LLLT) — INTERNAL IC MEMO B2B Spend Management / AP Automation SaaS — Mid-Market RECOMMENDATION SHORT / UNDERWEIGHT. 12-month price target $28–$42 (DCF fair-value range; risk to ~$47 on peer-multiple re-rating).

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

    GLM 4.5: Sally has 3 brothers, meaning there are 3 boys in the family. Each brother has 2 sisters, indicating that there are exactly 2 girls in the family. Since Sally is one of the girls, there must be one additional sister. Therefore, Sally has one sister.

    Inkling: Sally has 1 sister. Here’s why: Sally is a girl, and she has 3 brothers → so there are 3 boys. Each brother has 2 sisters. One of those sisters is Sally herself. So there must be 1 other girl in the family. That makes 2 girls total (Sally + her sister). So from Sally’s point of view, she has 1 sister.

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

    GLM 4.5: Here are 5 generated jokes: 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. Why did the scarecrow win an award? Because he was outstanding in his field! Why don't scientists trust atoms? Because they make up everything!

    Inkling: Here are 5 jokes: 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. Parallel lines have so much in common. It’s a shame they’ll never meet. 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 4.5GLM 4.5
No pick
No pick
No pick
No pick

Inception

2010

No pick

No pick

No pick

No pick

InklingInkling

Blade Runner

1982

Kind of Blue

Miles Davis

Le petit prince

Antoine de Saint-Exupéry

Kyoto

Japan

Portal

Action, Puzzle

Price and specs

Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer, bigger context window.

GLM 4.5 and Inkling compared across 54 shared prompts
SpecGLM 4.5Inkling
Input price$0.6/M tokens$1/M tokens
Output price$2.2/M tokens$4.05/M tokens
Context window128K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedJul 2025Jul 2026
At 10M a month$6.00$6.00$10.00$10.00
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
GLM 4.51 host
HostInOutContextUptime
  • Z.aifp8$0.60 in·$2.20 out·131k·100% up
Inkling2 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.95 in·$4.05 out·524k·99.5% up
  • TTogether$1.00 in·$4.05 out·524k·89.8% up

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

Common questions

What is the difference between GLM 4.5 and Inkling?

GLM 4.5 is developed by Zhipu AI while Inkling is developed by Thinking Machines. GLM 4.5 has a 128K token context window vs Inkling's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.5 or Inkling?

It depends on your use case. GLM 4.5 and Inkling 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 4.5 cost compared to Inkling?

GLM 4.5 costs $0.6/M input tokens and Inkling costs $1/M input tokens. GLM 4.5 is $0.40/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 4.5 and Inkling on Rival?

This page shows a side-by-side comparison of GLM 4.5 and Inkling 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

Against the newest arrivals

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  • Inkling vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

  • GLM 4.5 vs GLM 5.3Same lab
  • GLM 4.5 vs GLM 5.3 FlashSame lab
  • Inkling vs Step 5 PreviewSame size
  • Inkling vs Ling 3.1 FlashSame size
  • GLM 4.5 vs GLM 5.3 PrimeSame size
  • Inkling vs Golden Gate ClaudeNew provider
  • Inkling vs GPT-2New provider
  • Inkling vs GPT-3.5 TurboNew provider

Model pages

  • GLM 4.559 outputs, specs and price
  • Inkling58 outputs, specs and price
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