alt.freeweights.glm / GLM-4.7-Flash-GGUF
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.glmSubject:

GLM-4.7-Flash-GGUF

Date: 2026-11-14Commit: 0d32489Signed: 2DC28CC7B26A283B ✓

Text generation model. Gguf weights, 520 GB in all. Published by unsloth under MIT.

glm520GBGLM-4.7-Flash-GGUFggufpermissive
FactsParamsnot statedSize520 GBFormatsggufTasktext generationLicenseMITFrom sourcepermissive
$ fw get unsloth/GLM-4.7-Flash-GGUF
# manifest sha256 6f96bec50d0e… · 520 GB · 32 files
$ fw verify ./GLM-4.7-Flash-GGUF unsloth/GLM-4.7-Flash-GGUF
From sourceHosted (signed)unsloth/GLM-4.7-Flash-GGUFLast check: 2026-11-14 21:32 UTC

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

Quantized of GLM-4.7-Flash.

Works with

Convert with

Overview

Size
520 GB
Weights
8.33 GB (smallest of 28 GGUF variants)
Parameters
not stated
Formats
gguf
Task
text generation
License
MIT (permissive)
Files
32, each with a sha256
Publisher
unsloth
Added
2026-11-14
Section
alt.freeweights.glm
Lineage

Original release from the publisher.

Base model: zai-org/GLM-4.7-Flash

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.co2026-11-14 21:32 UTCpassed

Model card

From the publisher at commit 0d32489. Shown as plain text with links; images open at the publisher.

Read our How to Run GLM-4.7-Flash Guide!#

Jan 21 update: llama.cpp fixed a bug that caused looping and poor outputs. We updated the GGUFs - please re-download the model for much better outputs.#

  • Repeat penalty: Disable it, or set --repeat-penalty 1.0

You can now use Z.ai's recommended parameters and get great results:

  • For general use-case: --temp 1.0 --top-p 0.95
  • For tool-calling: --temp 0.7 --top-p 1.0
  • If using llama.cpp, set --min-p 0.01 as llama.cpp's default is 0.05

You can also fine-tune GLM-4.7-Flash with Unsloth via our GLM free notebook.


Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

https://github.com/unslothai/unsloth/ https://discord.gg/unsloth https://unsloth.ai/docs/models/glm-4.7-flash


GLM-4.7-Flash#

Image: image

👋 Join our Discord community.

📖 Check out the GLM-4.7 technical blog, technical report(GLM-4.5).

📍 Use GLM-4.7-Flash API services on Z.ai API Platform.

👉 One click to GLM-4.7.

Introduction#

GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.

Performances on Benchmarks#
BenchmarkGLM-4.7-FlashQwen3-30B-A3B-Thinking-2507GPT-OSS-20B
AIME 2591.685.091.7
GPQA75.273.471.5
LCB v664.066.061.0
HLE14.49.810.9
SWE-bench Verified59.222.034.0
τ²-Bench79.549.047.7
BrowseComp42.82.2928.3

Serve GLM-4.7-Flash Locally#

For local deployment, GLM-4.7-Flash supports inference frameworks including vLLM and SGLang. Comprehensive deployment instructions are available in the official Github repository.

vLLM and SGLang only support GLM-4.7-Flash on their main branches.

vLLM#
  • using pip (must use pypi.org as the index url):
pip install -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly
pip install git+https://github.com/huggingface/transformers.git
SGLang#
  • using pip install sglang from source, then update transformers to the latest main branch.
transformers#

using with transformers as

pip install git+https://github.com/huggingface/transformers.git

and then run:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_PATH = "zai-org/GLM-4.7-Flash"
messages = [{"role": "user", "content": "hello"}]
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
inputs = tokenizer.apply_chat_template(
    messages,
    tokenize=True,
    add_generation_prompt=True,
    return_dict=True,
    return_tensors="pt",
)
model = AutoModelForCausalLM.from_pretrained(
    pretrained_model_name_or_path=MODEL_PATH,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
inputs = inputs.to(model.device)
generated_ids = model.generate(**inputs, max_new_tokens=128, do_sample=False)
output_text = tokenizer.decode(generated_ids[0][inputs.input_ids.shape[1]:])
print(output_text)
vLLM#
vllm serve zai-org/GLM-4.7-Flash \
     --tensor-parallel-size 4 \
     --speculative-config.method mtp \
     --speculative-config.num_speculative_tokens 1 \
     --tool-call-parser glm47 \
     --reasoning-parser glm45 \
     --enable-auto-tool-choice \
     --served-model-name glm-4.7-flash
SGLang#
python3 -m sglang.launch_server \
  --model-path zai-org/GLM-4.7-Flash \
  --tp-size 4 \
  --tool-call-parser glm47  \
  --reasoning-parser glm45 \
  --speculative-algorithm EAGLE \
  --speculative-num-steps 3 \
  --speculative-eagle-topk 1 \
  --speculative-num-draft-tokens 4 \
  --mem-fraction-static 0.8 \
  --served-model-name glm-4.7-flash \
  --host 0.0.0.0 \
  --port 8000

Citation#

If you find our work useful in your research, please consider citing the following paper:

@misc{5team2025glm45agenticreasoningcoding,
      title={GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models}, 
      author={GLM Team and Aohan Zeng and Xin Lv and Qinkai Zheng and Zhenyu Hou and Bin Chen and Chengxing Xie and Cunxiang Wang and Da Yin and Hao Zeng and Jiajie Zhang and Kedong Wang and Lucen Zhong and Mingdao Liu and Rui Lu and Shulin Cao and Xiaohan Zhang and Xuancheng Huang and Yao Wei and Yean Cheng and Yifan An and Yilin Niu and Yuanhao Wen and Yushi Bai and Zhengxiao Du and Zihan Wang and Zilin Zhu and Bohan Zhang and Bosi Wen and Bowen Wu and Bowen Xu and Can Huang and Casey Zhao and Changpeng Cai and Chao Yu and Chen Li and Chendi Ge and Chenghua Huang and Chenhui Zhang and Chenxi Xu and Chenzheng Zhu and Chuang Li and Congfeng Yin and Daoyan Lin and Dayong Yang and Dazhi Jiang and Ding Ai and Erle Zhu and Fei Wang and Gengzheng Pan and Guo Wang and Hailong Sun and Haitao Li and Haiyang Li and Haiyi Hu and Hanyu Zhang and Hao Peng and Hao Tai and Haoke Zhang and Haoran Wang and Haoyu Yang and He Liu and He Zhao and Hongwei Liu and Hongxi Yan and Huan Liu and Huilong Chen and Ji Li and Jiajing Zhao and Jiamin Ren and Jian Jiao and Jiani Zhao and Jianyang Yan and Jiaqi Wang and Jiayi Gui and Jiayue Zhao and Jie Liu and Jijie Li and Jing Li and Jing Lu and Jingsen Wang and Jingwei Yuan and Jingxuan Li and Jingzhao Du and Jinhua Du and Jinxin Liu and Junkai Zhi and Junli Gao and Ke Wang and Lekang Yang and Liang Xu and Lin Fan and Lindong Wu and Lintao Ding and Lu Wang and Man Zhang and Minghao Li and Minghuan Xu and Mingming Zhao and Mingshu Zhai and Pengfan Du and Qian Dong and Shangde Lei and Shangqing Tu and Shangtong Yang and Shaoyou Lu and Shijie Li and Shuang Li and Shuang-Li and Shuxun Yang and Sibo Yi and Tianshu Yu and Wei Tian and Weihan Wang and Wenbo Yu and Weng Lam Tam and Wenjie Liang and Wentao Liu and Xiao Wang and Xiaohan Jia and Xiaotao Gu and Xiaoying Ling and Xin Wang and Xing Fan and Xingru Pan and Xinyuan Zhang and Xinze Zhang and Xiuqing Fu and Xunkai Zhang and Yabo Xu and Yandong Wu and Yida Lu and Yidong Wang and Yilin Zhou and Yiming Pan and Ying Zhang and Yingli Wang and Yingru Li and Yinpei Su and Yipeng Geng and Yitong Zhu and Yongkun Yang and Yuhang Li and Yuhao Wu and Yujiang Li and Yunan Liu and Yunqing Wang and Yuntao Li and Yuxuan Zhang and Zezhen Liu and Zhen Yang and Zhengda Zhou and Zhongpei Qiao and Zhuoer Feng and Zhuorui Liu and Zichen Zhang and Zihan Wang and Zijun Yao and Zikang Wang and Ziqiang Liu and Ziwei Chai and Zixuan Li and Zuodong Zhao and Wenguang Chen and Jidong Zhai and Bin Xu and Minlie Huang and Hongning Wang and Juanzi Li and Yuxiao Dong and Jie Tang},
      year={2025},
      eprint={2508.06471},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.06471}, 
}

Files

32 files · 520 GBWeights 8.33 GB (smallest of 28 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 32 files with their sha256
FileSizesha256
.gitattributes3.45 KB9c6c62d64d348b9a3b19319dcd47d05ce4d9a553b6789b627fee1d295a456650
BF16/GLM-4.7-Flash-BF16-00001-of-00002.gguf49.9 GB67ff61e44750b0caf0f674bb22e8083da0dafd4a8b98e8a5212c398266ba3167
BF16/GLM-4.7-Flash-BF16-00002-of-00002.gguf10.00 GBfc3b83f60bd00b9b7b045aa0fc6a9f551f65c1e855a0ad8d17fab18391d1b45f
GLM-4.7-Flash-IQ4_NL.gguf17.2 GBda2e17e8227fa048092798b66a9ae5f4e38155811af5d8b2cbcc6104d42c5e6b
GLM-4.7-Flash-IQ4_XS.gguf16.3 GB44ad6ab1885f3fd2282b1b684df729868ef2da65fd8adeab4eb848b25ac3925b
GLM-4.7-Flash-MXFP4_MOE.gguf17.0 GBecf4f3fd9448e45d01e1cacb54d9feaf308253d77e97893fac22b78bd9d04c4e
GLM-4.7-Flash-Q2_K.gguf11.3 GB96b400bda76c8297a12e6aa4ff894f260baf3e8dd814c8a49cce0d90bf114996
GLM-4.7-Flash-Q2_K_L.gguf11.4 GBfffb4a51cdd37902106102078e12f949a9e5a985243df4a4e7ef333f3bff57ad
GLM-4.7-Flash-Q3_K_M.gguf14.6 GBd11329183bbb320f11d025b66c4d546e4b58010381a580708ef2fe7415a92307
GLM-4.7-Flash-Q3_K_S.gguf13.3 GB21d16834f428215926466ce44862fccbd3337008b49ea4ac2f58abdd8ddd1e91
GLM-4.7-Flash-Q4_0.gguf17.2 GBd0bbdfcde6e323ebf90a8b9e95da57100e972be1ec6f0bfa0fad0feaa426557e
GLM-4.7-Flash-Q4_1.gguf19.0 GB417217f748759db0787a248859555b48d7b8b0538fa575b98cb64647586d1df1
GLM-4.7-Flash-Q4_K_M.gguf18.3 GB29837ed2c0fc5f51981adf8ac8083fcf80743c598381f13e9f06cbad0498b174
GLM-4.7-Flash-Q4_K_S.gguf17.3 GB4329be1a90062c8be84790322bfa3d0989cb4396f37f1a2e159788fa5e71c6be
GLM-4.7-Flash-Q5_K_M.gguf21.4 GB167848c4b460887d7a52c44c378d3996a0d38b3302ac2045494dc8b50869a893
GLM-4.7-Flash-Q5_K_S.gguf20.8 GB6c50f2e5251d1c77a0305c6dafdde93fceb8ab15bc9cd263cc4b707e0f71ff46
GLM-4.7-Flash-Q6_K.gguf24.7 GBf5bdc431802d7a3dab3be5a50ad0848a5569fd45c98c5e2ad83412c87cd887dc
GLM-4.7-Flash-Q8_0.gguf31.8 GB8c0922b03326932a40315ce92bbee01cc836ad18664268019143c898bdd7dd0b
GLM-4.7-Flash-UD-IQ1_M.gguf9.81 GBbbfe183ffd1bdb1d2f22878c9179d6336194ef35aa17d35045677c6f40de2cb4
GLM-4.7-Flash-UD-IQ1_S.gguf9.25 GB234e0149f81b181bf52ca3998386604965bb6062985e8e8ba7e77785cb6aade6
GLM-4.7-Flash-UD-IQ2_M.gguf11.0 GBc07e2be576052a3acda8c43683a1816c45639d05e82302fab1b0ad5f71c0db62
GLM-4.7-Flash-UD-IQ2_XXS.gguf10.5 GBd927162886f337ef4e1ddbeb6de1aac2872981629291d3b2444da9e6a1205166
GLM-4.7-Flash-UD-IQ3_XXS.gguf12.9 GB36b022b9cc24dd09bac703def9b065267e7ea3e51367d927958baa21484d745c
GLM-4.7-Flash-UD-Q2_K_XL.gguf11.9 GB08a432581d3a797af07a021455ada33499185213ad250e85fb26daf3fe34c421
GLM-4.7-Flash-UD-Q3_K_XL.gguf13.8 GB582728c0f6931a1cf734d5a7cf60ec73522fb79811e004cbc12476dd69b033bf
GLM-4.7-Flash-UD-Q4_K_XL.gguf17.5 GBb0d4fbc1211f891b4cfbf2a497160bfe06a49412420068904d426b7a13f4ba7f
GLM-4.7-Flash-UD-Q5_K_XL.gguf21.7 GB1e02f8b6cb4ae5d14e05aa3bf57361db0a69c79cc2f44e12f5a0e4d10fb93cd5
GLM-4.7-Flash-UD-Q6_K_XL.gguf26.2 GBb5ddf6a5531a4d06ce84a652419c8d32c0cb15ca64549d715f783de948a3f3e2
GLM-4.7-Flash-UD-Q8_K_XL.gguf35.6 GBf07a3b8fce22b5774610ba60f7db9176ea9538ea9f6be357c4a1fced0c7c0882
GLM-4.7-Flash-UD-TQ1_0.gguf8.33 GBa68a7af6b8b7620eb3367668be8c4b2dc3988aeed409d864ce2781bc4f5844c8
README.md8.60 KBc3ca90d7a4c4969a151d58f48d3672d1a2f0b95d90a5856a125c169918730aec
imatrix_unsloth.gguf_file72.4 MB585336847c79c2fc9ba778169a775634b3acaeb4f107546d3f47f2022f916354
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
0d32489ecb pinned now manifest updated, same commit2026-11-14 21:32 UTC32 files · 520 GB
0d32489ecb2026-11-14 21:32 UTC32 files · 520 GB

Use it

$ fw get unsloth/GLM-4.7-Flash-GGUF
# manifest sha256 6f96bec50d0e… · 520 GB · 32 files
$ fw verify ./GLM-4.7-Flash-GGUF unsloth/GLM-4.7-Flash-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/unsloth/GLM-4.7-Flash-GGUF.json --dir ./GLM-4.7-Flash-GGUF $ python3 fw.py verify ./GLM-4.7-Flash-GGUF ./unsloth__GLM-4.7-Flash-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/GLM-4.7-Flash-GGUF --revision 0d32489ecb9db6d2a4fc93bd27ef01519f95474d --local-dir ./GLM-4.7-Flash-GGUF
llama.cppDownload one GGUF variant (GLM-4.7-Flash-UD-TQ1_0, 8.33 GB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/GLM-4.7-Flash-GGUF --include "GLM-4.7-Flash-UD-TQ1_0*" --local-dir ./GLM-4.7-Flash-GGUF $ llama-server -m ./GLM-4.7-Flash-GGUF/GLM-4.7-Flash-UD-TQ1_0.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./GLM-4.7-Flash-GGUF/GLM-4.7-Flash-UD-TQ1_0.gguf\n' > Modelfile $ ollama create glm-4.7-flash-gguf -f Modelfile

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-14
Text in
README.md
Text sha256
c3ca90d7a4c4969a151d58f48d3672d1a2f0b95d90a5856a125c169918730aec
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: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.glmSubject: GLM-4.7-Flash-GGUFDate: 2026-11-14Commit: 0d32489Signed: 2DC28CC7B26A283B ✓
Upstream
unsloth/GLM-4.7-Flash-GGUF
Pinned commit
0d32489ecb9db6d2a4fc93bd27ef01519f95474d
Manifest
GLM-4.7-Flash-GGUF.json · .minisig
Manifest sha256
6f96bec50d0e89334355d2e837bb65d791e51bb9a364add79c484cb5c255d2bf
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 21:32 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/GLM-4.7-Flash-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/GLM-4.7-Flash-GGUF.json.minisig $ minisign -Vm GLM-4.7-Flash-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-4.7-Flash · 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 unsloth/GLM-4.7-Flash-GGUF
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. GLM-4.7-Flash-GGUF.json. Provenance. Takedown history: none.
From: bartowski <huggingface.co/bartowski>Subject: arcee-ai_GLM-4-32B-Base-32K-GGUF
From: ggml-org <huggingface.co/ggml-org>Subject: AutoGLM-Phone-9B-GGUF
From: zai-org <huggingface.co/zai-org>Subject: cogagent-chat-hf
From: zai-org <huggingface.co/zai-org>Subject: CogView3-Plus-3B
From: zai-org <huggingface.co/zai-org>Subject: cogvlm-base-490-hf
From: laion <huggingface.co/laion>Subject: dev_set_part1_10k_glm_4_7_traces_jupiter