GLM 4.5 is cheaper than Inkling at $0.6/M vs $1/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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)…
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…
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.
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.
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.
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.
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.
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.
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.
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…
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…
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.
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Not enough votes to call it. On the specs, Inkling has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $0.6/M tokens | $1/M tokens |
| Output price | $2.2/M tokens | $4.05/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Jul 2025 | Jul 2026 |
| At 10M a month | $6.00 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
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.
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.
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.
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.