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alt.freeweights.glm / zai-org_GLM-4.5-Air-GGUF
From: bartowski <huggingface.co/bartowski>Newsgroups: alt.freeweights.glmSubject:

zai-org_GLM-4.5-Air-GGUF

Date: 2026-11-15Commit: bd90715Signed: 2DC28CC7B26A283B ✓

Text generation model. Gguf weights, 1.46 TB in all. Published by bartowski under MIT.

glm1.46TBzai-org_GLM-4.5-Air-GGUFggufpermissive
FactsParamsnot statedSize1.46 TBFormatsggufTasktext generationLicenseMITFrom sourcepermissive
$ fw get bartowski/zai-org_GLM-4.5-Air-GGUF
# manifest sha256 1078ad8ec8c9… · 1.46 TB · 47 files
$ fw verify ./zai-org_GLM-4.5-Air-GGUF bartowski/zai-org_GLM-4.5-Air-GGUF
From sourceHosted (signed)bartowski/zai-org_GLM-4.5-Air-GGUFLast check: 2026-11-15 04:50 UTC
Run at homeGet help

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Quantized of GLM-4.5-Air.

Works with

Run14Convert1Evaluate13Scan12Apps58

Convert with

ggml
OverviewModel cardFilesUse itLicenseProvenanceModel tree

Overview

Size
1.46 TB
Weights
228 MB (smallest of 25 GGUF variants)
Parameters
not stated
Formats
gguf
Task
text generation
License
MIT (permissive)
Files
47, each with a sha256
Publisher
bartowski
Added
2026-11-15
Section
alt.freeweights.glm
Lineage

Original release from the publisher.

Base model: zai-org/GLM-4.5-Air

Where these bytes come from
Publisher at the pinned commit→You

Sources are tried in order. A file counts only when its size and sha256 match the manifest. Sources are checked when you ask for them, not on a timer.

Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 04:50 UTCpassed

Model card

From the publisher at commit bd90715. Shown as plain text with links; images open at the publisher.

Llamacpp imatrix Quantizations of GLM-4.5-Air by zai-org#

Using llama.cpp release b6085 for quantization.

Original model: https://huggingface.co/zai-org/GLM-4.5-Air

All quants made using imatrix option with dataset from here

Run them in LM Studio

Run them directly with llama.cpp, or any other llama.cpp based project

Prompt format#

No prompt format found, check original model page

Download a file (not the whole branch) from below:#

FilenameQuant typeFile SizeSplitDescription
GLM-4.5-Air-Q8_0.ggufQ8_0117.46GBtrueExtremely high quality, generally unneeded but max available quant.
GLM-4.5-Air-Q6_K.ggufQ6_K99.18GBtrueVery high quality, near perfect, recommended.
GLM-4.5-Air-Q5_K_M.ggufQ5_K_M83.72GBtrueHigh quality, recommended.
GLM-4.5-Air-Q5_K_S.ggufQ5_K_S78.55GBtrueHigh quality, recommended.
GLM-4.5-Air-Q4_K_M.ggufQ4_K_M73.50GBtrueGood quality, default size for most use cases, recommended.
GLM-4.5-Air-Q4_1.ggufQ4_169.55GBtrueLegacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon.
GLM-4.5-Air-Q4_K_S.ggufQ4_K_S68.31GBtrueSlightly lower quality with more space savings, recommended.
GLM-4.5-Air-Q4_0.ggufQ4_063.76GBtrueLegacy format, offers online repacking for ARM and AVX CPU inference.
GLM-4.5-Air-IQ4_NL.ggufIQ4_NL63.06GBtrueSimilar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference.
GLM-4.5-Air-IQ4_XS.ggufIQ4_XS60.81GBtrueDecent quality, smaller than Q4_K_S with similar performance, recommended.
GLM-4.5-Air-Q3_K_XL.ggufQ3_K_XL56.45GBtrueUses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability.
GLM-4.5-Air-Q3_K_L.ggufQ3_K_L55.91GBtrueLower quality but usable, good for low RAM availability.
GLM-4.5-Air-Q3_K_M.ggufQ3_K_M55.48GBtrueLow quality.
GLM-4.5-Air-IQ3_M.ggufIQ3_M55.48GBtrueMedium-low quality, new method with decent performance comparable to Q3_K_M.
GLM-4.5-Air-Q3_K_S.ggufQ3_K_S53.42GBtrueLow quality, not recommended.
GLM-4.5-Air-IQ3_XS.ggufIQ3_XS50.84GBtrueLower quality, new method with decent performance, slightly better than Q3_K_S.
GLM-4.5-Air-IQ3_XXS.ggufIQ3_XXS50.34GBtrueLower quality, new method with decent performance, comparable to Q3 quants.
GLM-4.5-Air-Q2_K_L.ggufQ2_K_L46.71GBfalseUses Q8_0 for embed and output weights. Very low quality but surprisingly usable.
GLM-4.5-Air-Q2_K.ggufQ2_K46.10GBfalseVery low quality but surprisingly usable.
GLM-4.5-Air-IQ2_M.ggufIQ2_M45.12GBfalseRelatively low quality, uses SOTA techniques to be surprisingly usable.
GLM-4.5-Air-IQ2_S.ggufIQ2_S42.54GBfalseLow quality, uses SOTA techniques to be usable.
GLM-4.5-Air-IQ2_XS.ggufIQ2_XS42.19GBfalseLow quality, uses SOTA techniques to be usable.
GLM-4.5-Air-IQ2_XXS.ggufIQ2_XXS39.62GBfalseVery low quality, uses SOTA techniques to be usable.
GLM-4.5-Air-IQ1_M.ggufIQ1_M37.86GBfalseExtremely low quality, not recommended.

Embed/output weights#

Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to.

Downloading using huggingface-cli#

Click to view download instructions

First, make sure you have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Then, you can target the specific file you want:

huggingface-cli download bartowski/zai-org_GLM-4.5-Air-GGUF --include "zai-org_GLM-4.5-Air-Q4_K_M.gguf" --local-dir ./

If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download bartowski/zai-org_GLM-4.5-Air-GGUF --include "zai-org_GLM-4.5-Air-Q8_0/*" --local-dir ./

You can either specify a new local-dir (zai-org_GLM-4.5-Air-Q8_0) or download them all in place (./)

ARM/AVX information#

Previously, you would download Q4_0_4_4/4_8/8_8, and these would have their weights interleaved in memory in order to improve performance on ARM and AVX machines by loading up more data in one pass.

Now, however, there is something called "online repacking" for weights. details in this PR. If you use Q4_0 and your hardware would benefit from repacking weights, it will do it automatically on the fly.

As of llama.cpp build b4282 you will not be able to run the Q4_0_X_X files and will instead need to use Q4_0.

Additionally, if you want to get slightly better quality for , you can use IQ4_NL thanks to this PR which will also repack the weights for ARM, though only the 4_4 for now. The loading time may be slower but it will result in an overall speed incrase.

Click to view Q4_0_X_X information (deprecated

I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking.

Click to view benchmarks on an AVX2 system (EPYC7702)

modelsizeparamsbackendthreadstestt/s% (vs Q4_0)
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp512204.03 ± 1.03100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp1024282.92 ± 0.19100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64pp2048259.49 ± 0.44100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg12839.12 ± 0.27100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg25639.31 ± 0.69100%
qwen2 3B Q4_01.70 GiB3.09 BCPU64tg51240.52 ± 0.03100%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp512301.02 ± 1.74147%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp1024287.23 ± 0.20101%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64pp2048262.77 ± 1.81101%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg12818.80 ± 0.9948%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg25624.46 ± 3.0483%
qwen2 3B Q4_K_M1.79 GiB3.09 BCPU64tg51236.32 ± 3.5990%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp512271.71 ± 3.53133%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp1024279.86 ± 45.63100%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64pp2048320.77 ± 5.00124%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg12843.51 ± 0.05111%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg25643.35 ± 0.09110%
qwen2 3B Q4_0_8_81.69 GiB3.09 BCPU64tg51242.60 ± 0.31105%

Q4_0_8_8 offers a nice bump to prompt processing and a small bump to text generation

Which file should I choose?#

Click here for details

A great write up with charts showing various performances is provided by Artefact2 here

The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have.

If you want your model running as FAST as possible, you'll want to fit the whole thing on your GPU's VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU's total VRAM.

If you want the absolute maximum quality, add both your system RAM and your GPU's VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total.

Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'.

If you don't want to think too much, grab one of the K-quants. These are in format 'QX_K_X', like Q5_K_M.

If you want to get more into the weeds, you can check out this extremely useful feature chart:

llama.cpp feature matrix

But basically, if you're aiming for below Q4, and you're running cuBLAS (Nvidia) or rocBLAS (AMD), you should look towards the I-quants. These are in format IQX_X, like IQ3_M. These are newer and offer better performance for their size.

These I-quants can also be used on CPU, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide.

Credits#

Thank you kalomaze and Dampf for assistance in creating the imatrix calibration dataset.

Thank you ZeroWw for the inspiration to experiment with embed/output.

Thank you to LM Studio for sponsoring my work.

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski

Files

47 files · 1.46 TBWeights 228 MB (smallest of 25 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 47 files with their sha256
FileSizesha256
.gitattributes6.16 KB7375705bfb70fd882d0b89d6d8c841ee20eed11c24cd2de0559616287c44ca39
README.md13.0 KB3176506b63cf54dacc971b560f70801881f2c1473c169509dad653b9b24a3194
zai-org_GLM-4.5-Air-IQ1_M.gguf37.9 GB0a9276e6597caa9816504310567b726f08dd08d51dbf480b2a0fc4d22985ac25
zai-org_GLM-4.5-Air-IQ2_M.gguf45.1 GB2f88eaaca0b78f8ad2d77b9d3c8aa705b5594e07a18972b92458f6cd742001a5
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zai-org_GLM-4.5-Air-IQ2_XS.gguf42.2 GB227a4929e51cc247819c2b5cad5aa0b56540ad5e3f80974ed44c5948e6354fb6
zai-org_GLM-4.5-Air-IQ2_XXS.gguf39.6 GBf8ce200485ee4fbcffb9a265ec3d92b9b46d23c4be02ca982e74f64465160a11
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zai-org_GLM-4.5-Air-Q3_K_M/zai-org_GLM-4.5-Air-Q3_K_M-00002-of-00002.gguf15.5 GBf536801c65c89cb391ece40c95f74ab64bed66005f1fddd2f2c0ca114cbd0f15
zai-org_GLM-4.5-Air-Q3_K_S/zai-org_GLM-4.5-Air-Q3_K_S-00001-of-00002.gguf39.8 GBf306db23fb1bbe7298b92920b9e6e3462e7899671aaf8c7bde781a4bf451c81c
zai-org_GLM-4.5-Air-Q3_K_S/zai-org_GLM-4.5-Air-Q3_K_S-00002-of-00002.gguf13.6 GB48872f1b0093c3aacfe2f0d35f6273a46f2db3f0e3c2c70e7243431ddc104771
zai-org_GLM-4.5-Air-Q3_K_XL/zai-org_GLM-4.5-Air-Q3_K_XL-00001-of-00002.gguf39.9 GB898e0f3c71f2f760d9e3134356ca7b80dfe8703c53557e4d66f7c43688ecaa03
zai-org_GLM-4.5-Air-Q3_K_XL/zai-org_GLM-4.5-Air-Q3_K_XL-00002-of-00002.gguf16.5 GBb06973ddf967d1b83d03d2dfc5c2c3daf0b03db901d212c9375d88e71e389b4c
zai-org_GLM-4.5-Air-Q4_0/zai-org_GLM-4.5-Air-Q4_0-00001-of-00002.gguf39.7 GBef79d95e838a486b644edd9223346dd6e82c5373572d8af5f8a6152ae3ae0627
zai-org_GLM-4.5-Air-Q4_0/zai-org_GLM-4.5-Air-Q4_0-00002-of-00002.gguf24.1 GB68f13be975acb909aaea96e36f30dcd8ea54a85e720bef6ad3f2e58c23c79040
zai-org_GLM-4.5-Air-Q4_1/zai-org_GLM-4.5-Air-Q4_1-00001-of-00002.gguf39.9 GB7624c3751a68596a9cefea9e77714d2010471da00820a91275cd280d9086fb0b
zai-org_GLM-4.5-Air-Q4_1/zai-org_GLM-4.5-Air-Q4_1-00002-of-00002.gguf29.7 GBf5ca9f12617fd065d3a1f5d9014e76f8dd2218ba33713cf48430a71f930cad97
zai-org_GLM-4.5-Air-Q4_K_M/zai-org_GLM-4.5-Air-Q4_K_M-00001-of-00002.gguf39.8 GB5a37921080f79f8f8fe6118f8477fa77b6c4b4ff95d1b983226affe370b5227d
zai-org_GLM-4.5-Air-Q4_K_M/zai-org_GLM-4.5-Air-Q4_K_M-00002-of-00002.gguf33.7 GB0bb72bd2c28d40bc8d6184e017be1b2123bcef83cde1d103faa45235147dba56
zai-org_GLM-4.5-Air-Q4_K_S/zai-org_GLM-4.5-Air-Q4_K_S-00001-of-00002.gguf39.6 GB8e0cc31656e930fac7f418a08a008dba6cead5dae75d43588eb31b8162c4f212
zai-org_GLM-4.5-Air-Q4_K_S/zai-org_GLM-4.5-Air-Q4_K_S-00002-of-00002.gguf28.7 GB0b3c941ef04c4abba3c1f8703b5bb03cf131c03135cf135c9bf51bb3818d2ec9
zai-org_GLM-4.5-Air-Q5_K_M/zai-org_GLM-4.5-Air-Q5_K_M-00001-of-00003.gguf39.6 GB17aa63c57f0a54f38d835b56bbe7da3696780a1956fec44daac49853445e662b
zai-org_GLM-4.5-Air-Q5_K_M/zai-org_GLM-4.5-Air-Q5_K_M-00002-of-00003.gguf39.6 GBc59f783aae38b57c460199d42c4714a1e1d0193825673d47cc15321a303f1d18
zai-org_GLM-4.5-Air-Q5_K_M/zai-org_GLM-4.5-Air-Q5_K_M-00003-of-00003.gguf4.59 GBd8238073500f4dc827cd57a8b5c9e3c8fd3579006ecdcc1affb98377b9c1d1d1
zai-org_GLM-4.5-Air-Q5_K_S/zai-org_GLM-4.5-Air-Q5_K_S-00001-of-00002.gguf39.5 GBf553481374fd3773fa1e719e66efdcfb45ba6b1e53de4e83442b0f4c4afecb7a
zai-org_GLM-4.5-Air-Q5_K_S/zai-org_GLM-4.5-Air-Q5_K_S-00002-of-00002.gguf39.1 GB0b752bdd65be603fadbc228cc75265ab7a39a79877780c02425892c3d481a711
zai-org_GLM-4.5-Air-Q6_K/zai-org_GLM-4.5-Air-Q6_K-00001-of-00003.gguf39.2 GB8f06661212248e639009110c9beca94359c0d1f02999e42f6deb55dc3bac80a6
zai-org_GLM-4.5-Air-Q6_K/zai-org_GLM-4.5-Air-Q6_K-00002-of-00003.gguf40.0 GBbcc5acf61dabedf9c811eec5cc2f6e5f33c2b2af530b8cc935a65e73f149d77f
zai-org_GLM-4.5-Air-Q6_K/zai-org_GLM-4.5-Air-Q6_K-00003-of-00003.gguf20.0 GBe24dba862619a1a52adc5321650844c2e00d9424151e55659bca5412766f93a9
zai-org_GLM-4.5-Air-Q8_0/zai-org_GLM-4.5-Air-Q8_0-00001-of-00003.gguf39.8 GB98df3cff5cf9c0c6745c5a7cc39184544fe798fdb0221cdb287e5d9579e5249e
zai-org_GLM-4.5-Air-Q8_0/zai-org_GLM-4.5-Air-Q8_0-00002-of-00003.gguf39.8 GB80d6bd0736ce97ce4801a763209d4e7baf188fe9411e40f4d6cbf1ed28a02de6
zai-org_GLM-4.5-Air-Q8_0/zai-org_GLM-4.5-Air-Q8_0-00003-of-00003.gguf37.8 GBe271fcf97c81485302d3fe1209f8f986b32dd5abf5090fd479dcc473f42d1655
zai-org_GLM-4.5-Air-imatrix.gguf228 MBf21d0c0a55a67c52d6cebf71be5db0560f48991c0253240edfe7e181661e77ef
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
bd907156c1 pinned now2026-11-15 04:50 UTC47 files · 1.46 TB

Use it

$ fw get bartowski/zai-org_GLM-4.5-Air-GGUF
# manifest sha256 1078ad8ec8c9… · 1.46 TB · 47 files
$ fw verify ./zai-org_GLM-4.5-Air-GGUF bartowski/zai-org_GLM-4.5-Air-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/bartowski/zai-org_GLM-4.5-Air-GGUF.json --dir ./zai-org_GLM-4.5-Air-GGUF $ python3 fw.py verify ./zai-org_GLM-4.5-Air-GGUF ./bartowski__zai-org_GLM-4.5-Air-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/zai-org_GLM-4.5-Air-GGUF --revision bd907156c1ca4dd837540eda77043fddfd6d5caf --local-dir ./zai-org_GLM-4.5-Air-GGUF
llama.cppDownload one GGUF variant (zai-org_GLM-4.5-Air-imatrix, 228 MB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/zai-org_GLM-4.5-Air-GGUF --include "zai-org_GLM-4.5-Air-imatrix*" --local-dir ./zai-org_GLM-4.5-Air-GGUF $ llama-server -m ./zai-org_GLM-4.5-Air-GGUF/zai-org_GLM-4.5-Air-imatrix.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./zai-org_GLM-4.5-Air-GGUF/zai-org_GLM-4.5-Air-imatrix.gguf\n' > Modelfile $ ollama create zai-org-glm-4.5-air-gguf -f Modelfile
Run at home

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
Inherited from the base model zai-org/GLM-4.5-Air: the strictest license along the lineage applies. 2026-11-15
Text in
README.md
Text sha256
3176506b63cf54dacc971b560f70801881f2c1473c169509dad653b9b24a3194
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: bartowski <huggingface.co/bartowski>Newsgroups: alt.freeweights.glmSubject: zai-org_GLM-4.5-Air-GGUFDate: 2026-11-15Commit: bd90715Signed: 2DC28CC7B26A283B ✓
Upstream
bartowski/zai-org_GLM-4.5-Air-GGUF
Pinned commit
bd907156c1ca4dd837540eda77043fddfd6d5caf
Manifest
zai-org_GLM-4.5-Air-GGUF.json · .minisig
Manifest sha256
1078ad8ec8c95e39e0325fb9c3afad24922213e5e0902525d966ebdbabab35d1
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 04:50 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/bartowski/zai-org_GLM-4.5-Air-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/bartowski/zai-org_GLM-4.5-Air-GGUF.json.minisig $ minisign -Vm zai-org_GLM-4.5-Air-GGUF.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

Parent

zai-org/GLM-4.5-Air · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download bartowski/zai-org_GLM-4.5-Air-GGUF
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. zai-org_GLM-4.5-Air-GGUF.json. Provenance. Takedown history: none.
Source
huggingface.co/bartowski/zai-org_GLM-4.5-Air-GGUF

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