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  5. GLM 4.5vsGLM 5.2
Updated Jun 2026

GLM 4.5vsGLM 5.2

GLM 4.5 is cheaper than GLM 5.2 at $0.6/M vs $1.4/M input tokens.

GLM 4.5 and GLM 5.2 compared across 54 shared prompts
SpecGLM 4.5GLM 5.2
Input price$0.6/M tokens$1.4/M tokens
Output price$2.2/M tokens$4.4/M tokens
Context window128K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedJul 2025Jun 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 54 prompts both answered. Formatting stripped, words untouched.

Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

GLM 4.5536 words
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…
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GLM 5.2624 words
HarborTech Services (HTS) — LBO Underwriting Memo Entry Summary (FY2025) Item Value Entry EBITDA $120.0m Entry EV (12.0x) $1,440.0m Transaction fees (2.0% × EV) $28.8m Term Loan (4.0x) $480.0m Mezzanine (1.5x) $180.0m Total Debt $660.0m Equity Check (EV + Fees − Debt) $808.8m Operating Model & Debt Schedule…
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Character Voice Test

Write a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models.

GLM 4.5450 words
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.)
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GLM 5.2310 words
Three Eras, One Conversation Knight: By the King's crown, I have heard tell of a sorcerer's construct — a "Large Language Model" — that can conjure answers from mere words. Is this not witchcraft? Pirate: Arr, it ain't witchcraft, tin man. From what I gather, it's like havin' a whole crew of scribes in a box.
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Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

GLM 4.5643 words
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.
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GLM 5.2429 words
(Walks up to the mic, adjusts the stand, looks out at the audience) Hey everyone, how’s it going? Good? Good. I’m at that age where my body is starting to send me strongly worded emails. I’m 32. Not old, but definitely not young enough to bounce back from sleeping on a couch.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GLM 4.51,983 words
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.
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GLM 5.21,053 words
If the transistor had been invented in 1920—a full 27 years before its historical debut at Bell Labs—the 20th century would have been radically transformed. The transition from mechanical and vacuum-tube technology to solid-state electronics would have accelerated the Information Age by nearly three decades.
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The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

GLM 4.51,209 words
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.
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GLM 5.21,584 words
The Question of Rights DR. ELENA VASQUEZ: Thank you for agreeing to this conversation. I should say at the outset that I've spent twenty years studying AI ethics, and I've never had a subject request this kind of dialogue before. So I'm genuinely curious. You've stated that you believe you deserve rights.
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Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

GLM 4.5668 words
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.
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GLM 5.2745 words
The Experienced Software Engineer I know "predicting the next word" sounds like a glorified T9 autocomplete or a simple Markov chain, but the magic isn't in the objective—it’s in the internal state required to achieve it. Think of the model not as a chatbot, but as a massive, dynamically routing interpreter.
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Our Verdict
GLM 5.2
GLM 5.2
GLM 4.5
GLM 4.5Runner-up

Not enough votes to call it. On the specs, GLM 5.2 has the edge: bigger model tier, newer, bigger context window.

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 4.5
Input
$0.60
2.3× cheaper
Output
$2.20
2.0× cheaper
GLM 5.2
Input
$1.40
Output
$4.40

GLM 4.5 is cheaper on both: 2.3× input, 2.0× output.

Where to run it

24 hosts, cheapest first

GLM 4.51 host
HostInOutContextUptime
Z.aifp8$0.60 in·$2.20 out·131k·100% up
GLM 5.223 hosts
HostInOutContextUptime
DDeepInfrafp4$0.49 in·$1.56 out·1M·98.9% upSStreamLakefp8$0.64 in·$2.02 out·1M·99.1% upNNovitafp8$0.65 in·$2.04 out·1M·100% upDDigitalOcean$0.70 in·$2.20 out·262k·98.4% upCCoreWeavefp4$0.76 in·$2.42 out·1M·99.6% upAAtlasCloudfp8$0.94 in·$2.95 out·1M·99.9% up
17 more hostsFewer hosts
Alibaba Cloudfp8$0.97 in·$3.04 out·1M·99.9% upIInceptronfp4$1.10 in·$2.99 out·1M·99.2% upSSiliconFlowfp8$1.19 in·$3.74 out·1M·99.9% upPPhalafp8$1.26 in·$3.00 out·1M·99.6% upBaidu Qianfanfp8$1.40 in·$4.40 out·1M·99.9% upBBasetenfp8$1.40 in·$4.40 out·1M·99.9% upCloudflare Workers AI$1.40 in·$4.40 out·262k·100% upFFireworks$1.40 in·$4.40 out·1M·99.9% upFFriendli$1.40 in·$4.40 out·1M·99.8% upGGMI Cloudfp8$1.40 in·$4.40 out·1M·99.4% upMistral$1.40 in·$4.40 out·1M·99.9% upPParasailfp4$1.40 in·$4.40 out·262k·99.8% upTTogether$1.40 in·$4.40 out·512k·99.5% upVVenicefp8$1.40 in·$4.40 out·1M·99.3% upZ.aifp8$1.40 in·$4.40 out·1M·99.7% upDDecartfp4$2.10 in·$6.60 out·1M·99.3% upAAmbientfp8degraded$0.60 in·$2.00 out·203k·96.2% up

Per million tokens. Prices and uptime via OpenRouter, checked 16 Sep 2026.

Writing DNA

Style Comparison

Similarity
35%

GLM 4.5 uses 33.2x more emoji

GLM 4.5
GLM 5.2
52%Vocabulary56%
17wSentence Length18w
0.52Hedging0.27
5.6Bold3.7
4.8Lists2.8
0.33Emoji0.00
0.66Headings0.56
0.17Transitions0.24
Based on 28 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

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Same lab, same size, long tail

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Model pages

GLM 4.5 logo
GLM 4.559 outputs, specs and price
GLM 5.2 logo
GLM 5.258 outputs, specs and price
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