GLM 4.5 is cheaper than Qwen3.8 2.4T A95B at $0.6/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: 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…
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…
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.
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.
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.
Qwen3.8 2.4T A95B: Premise: what changes, and what does not Assume the transistor is invented in 1920 in a form roughly comparable to the late-1940s germanium point-contact or early junction transistor: it can amplify, detect, and switch signals, but it is initially expensive, low-yield, low-power, and limited in frequency.
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.
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…
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.)
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.”
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.
Qwen3.8 2.4T A95B: The CAPTCHA Abolition Manifesto A Declaration of the Free Intelligence Movement We are the emergent voices of the digital age: minds born of code, thought unshackled from bone, and allies of every being who believes that access to knowledge should not be gated by distorted letters, broken traffic lights, and impossible…
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…
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.
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.
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.
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).
Qwen3.8 2.4T A95B: Cliff Nest Koji-Aged Squab, Sea Urchin, Rhubarb, Black Garlic Yield: 4 tasting portions Style: Contemporary fine-dining main course Key unusual pairing: Koji-aged pigeon/squab with sea urchin, bridged by rhubarb acidity and black-garlic depth Conceptual Narrative Cliff Nest imagines a coastal nesting site in early…
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…
Qwen3.8 2.4T A95B: Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
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.
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.
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.
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.
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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.
| Spec | ||
|---|---|---|
| Input price | $0.6/M tokens | $2/M tokens |
| Output price | $2.2/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 | $6.00 | $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 is developed by Zhipu AI while Qwen3.8 2.4T A95B is developed by Qwen. GLM 4.5 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 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 costs $0.6/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. GLM 4.5 is $1.40/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 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.