GLM-4.5 How much memory it needs, what its licence allows, and whether it fits an office box.
Short answer. GLM-4.5 needs about 206 GB of memory at 4-bit, 385 GB at 8-bit and 721 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 358.3 billion parameters and a 131,072-token context window. Licence in short: commercial use allowed. By memory alone, on ANVE’s launch configurations: ANVE One does not fit, ANVE Office does not fit, ANVE Office Pro (GPU) does not fit. These are estimates from its published size, not benchmarks.
01
What it is
GLM-4.5 is a language model for chat, drafting and question answering, published by Z.ai (Zhipu) on Hugging Face on 20 July 2025. It has about 358.3 billion parameters and a configured context window of 131,072 tokens. It is a mixture-of-experts model: 160 experts, 8 used for each token.
Its card lists the licence as MIT. In short, the licence allows commercial use, modification and redistribution as long as the copyright notice is kept.
Hugging Face counted about 123,422 downloads of it in the 30 days before we checked (7 Oct 2026), and 1,411 people have liked it there.
The card lists 2 languages: en, zh (ISO codes as given on the card).
02
How much memory it needs
We size it the way you would size any model: the weights (parameters × bits ÷ 8), the KV cache for 8,192 tokens of context, and roughly 1.5 GB for the runtime itself. Real use varies with settings.
Each token of context adds about 0.38 MB of KV cache at 16-bit, so 32,768 tokens would add about 12 GB.
Precision
Weights
KV cache (8,192 tokens)
Total, estimated
BF16 (full precision)
717 GB
3.1 GB
721 GB
8-bit (Q8_0)
381 GB
3.1 GB
385 GB
4-bit (Q4_K)
202 GB
3.1 GB
206 GB
03
Architecture at a glance
Setting
Value in config.json
Architecture class
Glm4MoeForCausalLM
Model type
glm4_moe
Layers
92
Hidden size
5,120
Attention heads
96
Key-value heads
8 (grouped-query attention)
Head size
128
Vocabulary
151,552
Experts
160, 8 active per token
Configured context
131,072
Stored precision
bfloat16
04
Will it fit on ANVE?
These verdicts are arithmetic, not tests, against the specification at launch: ANVE One can give a model about three quarters of its 64 GB of unified memory, while ANVE Office and ANVE Office Pro hold it on a 24 GB graphics card and keep the rest of the stack in 64 GB or 128 GB of system memory. ANVE’s tested default is Qwen 3.8 27B; this model is not yet validated on ANVE.
Configuration (at launch)
Memory for the model
Verdict
ANVE One
about 48 GB of 64 GB unified memory
does not fit
ANVE Office
24 GB on the RTX PRO 4000 Blackwell SFF Edition
does not fit
ANVE Office Pro (GPU)
24 GB on the RTX PRO 4000 Blackwell
does not fit
05
What an office would use it for
This is frontier-scale: even at 4-bit it needs far more memory than any single office box, so it belongs on a multi-GPU server or a cloud service, not on an appliance.
06
Similar models to compare
Llama-3.1-405B-Instruct (405.9B parameters, about 230 GB at 4-bit before context; commercial use allowed, with conditions)
MiMo-V2.5 (310.8B parameters, about 176 GB at 4-bit before context; commercial use allowed)
MiMo-V2-Flash (309.8B parameters, about 176 GB at 4-bit before context; commercial use allowed)
07
Questions people ask
How much memory does GLM-4.5 need?
About 206 GB at 4-bit, 385 GB at 8-bit and 721 GB at full 16-bit precision, including an 8,192-token KV cache and about 1.5 GB of runtime overhead. These are estimates from its parameter count.
Can GLM-4.5 run on a 24 GB graphics card?
Not entirely: even at 4-bit it needs about 206 GB, so part of it would sit in system memory, which is much slower.
Is GLM-4.5 free for commercial use?
Its card lists MIT, which allows commercial use, modification and redistribution as long as the copyright notice is kept. Read the licence itself before relying on this summary; it is not legal advice.
What is GLM-4.5’s context window?
Its configuration sets 131,072 tokens. Longer contexts need more memory for the KV cache, so the practical limit on a given machine can be lower.
08
What is not real yet
No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.
Reservations are ₹999 in India or US$12 elsewhere, refundable in full until you confirm an order in writing (terms). Offices that cannot use cloud AI can apply to be one of ten design partners.
