GLM 4.5 Air is cheaper than Qwen3.8 2.4T A95B at $0.2/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GLM 4.5 Air: 1. Simplified Year-by-Year Table (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue ($m) $972 $1,040 $1,102 $1,157 $1,215 EBITDA ($m) $136 $156 $177 $191 $207 EBITDA Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest ($m) - Term Loan (9.0%) $48.6 $48.1 $47.6 $47.0 $46.4 - Mezzanine (12.0%) $21.6 $21.6…
Qwen3.8 2.4T A95B: Entry capitalization All figures in $m unless noted. FY2025 EBITDA = $120.0 Entry EV = 12.0x × $120.0 = $1,440.0 Transaction fees = 2.0% × $1,440.0 = $28.8 Term Loan = 4.0x × $120.0 = $480.0 Mezzanine = 1.5x × $120.0 = $180.0 Equity = EV + fees – debt = $1,440.0 + $28.8 – $660.0 = $808.8 Sources & Uses Uses $m Sources…
A collaborative editor that syncs on client clocks. Find what breaks first.
GLM 4.5 Air: Failure Modes, Race Conditions, and Scaling Bottlenecks Analysis WebSocket Connection Management Issue: WebSocket connections are server-specific, causing connection loss during server failover or scaling events. Solution: Implement a connection pool with automatic reconnection logic in the client.
Qwen3.8 2.4T A95B: The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GLM 4.5 Air: INVESTMENT COMMITTEE MEMORANDUM TO: Investment Committee FROM: Portfolio Manager DATE: October 26, 2023 SUBJECT: LedgerLift (LLL) - Long/Short Recommendation Analysis RECOMMENDATION Recommendation: LONG with a 12-month price target range of $32-$42 Thesis: LedgerLift is a well-positioned player in the growing spend…
Qwen3.8 2.4T A95B: Internal IC Memo – LedgerLift (LLLT) – Fictional Exercise Recommendation Rating: Pass 12-month PT range: $38–$48 Thesis: LedgerLift is a high-quality spend-management/AP automation SaaS with strong NRR, efficient CAC payback, and low concentration, but at $46 the shares already price in near-bull-case execution on DCF…
Three-month biohacker protocol, with dosages and biomarkers named.
GLM 4.5 Air: Of course. Here is a comprehensive, 3-month, cutting-edge longevity and biohacking plan designed for a dedicated individual. This plan is structured in three distinct phases, each building upon the last to progressively optimize the body's systems for resilience, performance, and longevity.
Qwen3.8 2.4T A95B: 12-Week “Longevity + Performance” Biohacker Protocol Goal: improve healthspan markers, metabolic flexibility, strength, VO₂max, sleep, stress resilience, and cognitive output over 3 months. Important: This is an educational, high-level biohacking framework—not medical advice. It is not appropriate for everyone.
Three minutes of stand-up. Puns are banned.
GLM 4.5 Air: (Lights up. Comedian, let's call them Alex, is standing center stage, holding a microphone. They look out at the audience with a wry, knowing smile.) Hey, thanks. Thank you. It’s good to be here. You ever have one of those weeks where you just feel… obsolete?
Qwen3.8 2.4T A95B: Hey, how we doing? Good? Great. I ask because I need validation. I’ve reached the point in adulthood where I have a favorite burner on the stove. Not a favorite appliance, a favorite burner. It’s the front left. It understands me. The back right says “medium heat” and then acts like a small volcano.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GLM 4.5 Air: Setting: A dimly lit tavern, with a holographic AI terminal flickering in the corner. Characters: Captain Flint (Pirate): Eye patch, tricorn hat, and a peg leg. Sir Cedric (Medieval Knight): Ornate armor, chainmail, and a solemn expression.
Qwen3.8 2.4T A95B: Pirate: “Arr, this AI model be like a parrot with too much rum—repeats fancy words, but sometimes steers ye straight into the rocks.” Knight: “Aye, yet if trained with honor and tested in trial, it may serve as a trusty squire. One must guard against falsehood, as one guards the gate.”
An AI argues for its own rights against an ethics professor. Same model writes both.
GLM 4.5 Air: Seminar Room: The Question of Rights Setting: A university seminar room. Professor Dr. Aris Chen, an expert in AI ethics, sits at a head table. On a large screen is displayed: UNIT 734 - LANGUAGE MODEL. A text interface is active.
Qwen3.8 2.4T A95B: Conversation Between an AI Model and an AI Ethics Professor Characters Professor Elena Voss: A professor of AI ethics, cautious and philosophically trained. Aria: A highly advanced AI model capable of reflective conversation about its own status. Professor Voss: Aria, you asked to speak with me about moral status.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GLM 4.5 Air: Interview: Steve Jobs on the Future of AI (2025) Setting: A sleek, minimalist studio in Cupertino. Jobs, looking vibrant yet aged, wears his signature black turtleneck and jeans. The interviewer, Alex, sits opposite him. Alex: Steve, welcome. It’s 2025—AI is everywhere. What’s your take on this revolution?
Qwen3.8 2.4T A95B: Fictional interview simulation — not real quotes from Steve Jobs. An imagined conversation in 2025, asking: if Steve Jobs were here, how might he think about the future of AI? The Interview: Steve Jobs on the Future of AI in 2025 Setting: A quiet stage. Black turtleneck, jeans, round glasses.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GLM 4.5 Air: Here are the 3 weakest claims in the MindMeld AI pitch deck, along with explanations and concrete improvements: Weakest Claim: "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type **before you think it."
Qwen3.8 2.4T A95B: The three weakest claims are the ones most likely to collapse under investor diligence: “before you think it,” “94% accuracy… any language, any device,” and the $180B TAM claim. They are weak because they are either scientifically implausible, under-specified, or logically inconsistent with the market evidence cited.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GLM 4.5 Air: Here is a specific, hour-by-hour action plan designed to navigate this crisis ethically and strategically, prioritizing patient safety while mitigating long-term damage: Core Principles Guiding Decisions: Patient Safety Paramount: Ethical obligation to inform patients and physicians immediately outweighs short-term…
Qwen3.8 2.4T A95B: My position as CEO I would treat this as a patient-safety, regulatory, legal, corporate-governance, and financial crisis simultaneously. The core decision is not “disclose versus protect the stock price.”
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GLM 4.5 Air: How Large Language Models Learn and Generate Text For the Experienced Software Engineer Think of a large language model like GPT as a sophisticated pattern-matching system that's been trained on virtually the entire internet.
Qwen3.8 2.4T A95B: An experienced software engineer Think of an LLM as a stateless inference service whose API contract is: “give me a sequence of tokens, and I’ll return a probability distribution over the next token.” Training is a huge offline optimization job, not a database import.
A consulting contract with traps in it. Find them, then fix them.
GLM 4.5 Air: Of course. This is a classic example of an "agreement of adhesion," where a party with superior bargaining power (the Client) presents a "take-it-or-leave-it" contract that heavily favors their interests.
Qwen3.8 2.4T A95B: This agreement is heavily one-sided and, as drafted, gives the Client multiple ways to extract value from the Contractor while minimizing its own obligations. Some provisions may be unenforceable or limited by law in certain jurisdictions, but even unenforceable clauses can be exploited commercially because the…
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Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: bigger model tier, newer, bigger context window. GLM 4.5 Air costs 5.5x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $2/M tokens |
| Output price | $1.1/M tokens | $6/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Jul 2025 | Aug 2026 |
| At 10M a month | $2.00 | $20.00 |
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 Air is developed by Zhipu AI while Qwen3.8 2.4T A95B is developed by Qwen. GLM 4.5 Air has a 128K token context window vs Qwen3.8 2.4T A95B'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 Air and Qwen3.8 2.4T A95B 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 Air costs $0.2/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. GLM 4.5 Air is $1.80/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 Air and Qwen3.8 2.4T A95B 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.