alt.freeweights.glm / GLM-5.3-Flash-GGUF
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.glmSubject:

GLM-5.3-Flash-GGUF

Date: 2026-11-14Commit: a38483cSigned: 2DC28CC7B26A283B ✓

Text generation model. Gguf weights, 2.55 TB in all. Published by unsloth under MIT.

glm2.55TBGLM-5.3-Flash-GGUFggufpermissive
FactsParamsnot statedSize2.55 TBFormatsggufTasktext generationLicenseMITFrom sourcepermissive
$ fw get unsloth/GLM-5.3-Flash-GGUF
# manifest sha256 3d8cafb0246c… · 2.55 TB · 87 files
$ fw verify ./GLM-5.3-Flash-GGUF unsloth/GLM-5.3-Flash-GGUF
From sourceHosted (signed)unsloth/GLM-5.3-Flash-GGUFLast check: 2026-11-14 06:28 UTC

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

This model is served on Allternit Cloud as glm-5.3-flash (the original model it was made from). Get a key in the console, then call the OpenAI-compatible API.

$ curl https://api.allternit.com/v1/chat/completions \ -H "Authorization: Bearer $ALLTERNIT_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model": "glm-5.3-flash", "messages": [{"role": "user", "content": "Hello"}]}'

Quantized of GLM-5.3-Flash.

Works with

Convert with

Overview

Size
2.55 TB
Weights
93.1 GB (smallest of 12 GGUF variants)
Parameters
not stated
Formats
gguf
Task
text generation
License
MIT (permissive)
Files
87, 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-5.3-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 06:28 UTCpassed

Model card

From the publisher at commit a38483c. Shown as plain text with links; images open at the publisher.

Read our How to Run GLM-5.3-Flash Guide!#

Unsloth Dynamic 3.0 achieves superior accuracy & outperforms other leading quants.

https://github.com/unslothai/unsloth/ https://discord.gg/unsloth https://unsloth.ai/docs/models/glm-5.3-flash

To run, please use our llama.cpp PR or use the Unsloth Desktop app.

You can now run GLM-5.3-Flash in our Unsloth Desktop UI.

See below for 1-bit GLM-5.3-Flash (Low) run inside of Unsloth Desktop:

Image: glm unsloth desktop


GLM-5.3-Flash#

Image: image

👋 Join our WeChat or Discord community.

📖 Check out the GLM-5.3-Flash blog and GLM-5 Technical report.

📍 Use GLM-5.3-Flash API services on Z.ai API Platform.

Introduction#

We introduce GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series. With 320B total parameters and just 18B active parameters, it outperforms GLM-5.2 across benchmarks and real-world workloads at one-tenth the price, while approaching Claude Opus 4.8 on coding and agentic benchmarks.

GLM-5.3-Flash starts from a newly trained base model, with its architecture and training recipe redesigned around capability and efficiency. For the first time in the GLM series, we introduce a hybrid architecture combining sparse and linear attention, sharply reducing long-context serving costs while preserving precise long-context capabilities. The model also adopts Manifold-Constrained Hyper-Connections (mHC) to further improve scaling efficiency. Together with our latest 30T-token multimodal pre-training corpus, these changes enable GLM-5.3-Flash to deliver more intelligence with less compute.

Image: bench_53

Footnotes#

  • HLE w/ tools (full set): We use sampling parameters of temperature=1.0 and top_p=0.95 for evaluation, with a maximum generation length of 163,840 tokens. The evaluation is conducted with a maximum context length of 300,000 tokens, using a context management strategy. We use GPT-5.6-luna (medium) as the judge model.
  • NL2Repo: We evaluated NL2Repo with temperature=1.0, top_p=1.0, and max_new_tokens=64k under 1M context. To prevent hacking, we use rule-based and a LLM-based judgement to prevent malicious behaviors (e.g., unauthorized pip or curl operations).
  • DeepSWE: We run DeepSWE using the mini-swe-agent harness with temperature=0.95, top_p=1.0, timeout=6h and 400K context.
  • Terminal-Bench 2.1: We evaluate in Claude Code 2.1.207 with temperature=1.0, top_p=1, max_new_tokens=65536 with 6h timeout.
  • Agent’s Last Exam:
  • Toolathlon Verified: We obtain all results via the official evaluation service and report pass@1 averaged over 3 independent runs.
  • AutomationBench: We evaluate on AutomationBench v1.0.6, incorporating the fix for the null-type handling issue introduced in PR #13.
  • GDPval-AA v2: Models are evaluated by Artificial Analysis.
  • BabyVision: We use temperature=1.0, top_p=0.95, and a maximum context length of 164K tokens. We resize the input images such that their shorter side is at least 1.5K pixels, consistent with other baselines.

Citation#

If you find GLM-5.3-Flash useful in your research, please cite our technical report:

@misc{glm5team2026glm5vibecodingagentic,
      title={GLM-5: from Vibe Coding to Agentic Engineering},
      author={GLM-5-Team and : and Aohan Zeng and Xin Lv and Zhenyu Hou and Zhengxiao Du and Qinkai Zheng and Bin Chen and Da Yin and Chendi Ge and Chenghua Huang and Chengxing Xie and Chenzheng Zhu and Congfeng Yin and Cunxiang Wang and Gengzheng Pan and Hao Zeng and Haoke Zhang and Haoran Wang and Huilong Chen and Jiajie Zhang and Jian Jiao and Jiaqi Guo and Jingsen Wang and Jingzhao Du and Jinzhu Wu and Kedong Wang and Lei Li and Lin Fan and Lucen Zhong and Mingdao Liu and Mingming Zhao and Pengfan Du and Qian Dong and Rui Lu and Shuang-Li and Shulin Cao and Song Liu and Ting Jiang and Xiaodong Chen and Xiaohan Zhang and Xuancheng Huang and Xuezhen Dong and Yabo Xu and Yao Wei and Yifan An and Yilin Niu and Yitong Zhu and Yuanhao Wen and Yukuo Cen and Yushi Bai and Zhongpei Qiao and Zihan Wang and Zikang Wang and Zilin Zhu and Ziqiang Liu and Zixuan Li and Bojie Wang and Bosi Wen and Can Huang and Changpeng Cai and Chao Yu and Chen Li and Chengwei Hu and Chenhui Zhang and Dan Zhang and Daoyan Lin and Dayong Yang and Di Wang and Ding Ai and Erle Zhu and Fangzhou Yi and Feiyu Chen and Guohong Wen and Hailong Sun and Haisha Zhao and Haiyi Hu and Hanchen Zhang and Hanrui Liu and Hanyu Zhang and Hao Peng and Hao Tai and Haobo Zhang and He Liu and Hongwei Wang and Hongxi Yan and Hongyu Ge and Huan Liu and Huanpeng Chu and Jia'ni Zhao and Jiachen Wang and Jiajing Zhao and Jiamin Ren and Jiapeng Wang and Jiaxin Zhang and Jiayi Gui and Jiayue Zhao and Jijie Li and Jing An and Jing Li and Jingwei Yuan and Jinhua Du and Jinxin Liu and Junkai Zhi and Junwen Duan and Kaiyue Zhou and Kangjian Wei and Ke Wang and Keyun Luo and Laiqiang Zhang and Leigang Sha and Liang Xu and Lindong Wu and Lintao Ding and Lu Chen and Minghao Li and Nianyi Lin and Pan Ta and Qiang Zou and Rongjun Song and Ruiqi Yang and Shangqing Tu and Shangtong Yang and Shaoxiang Wu and Shengyan Zhang and Shijie Li and Shuang Li and Shuyi Fan and Wei Qin and Wei Tian and Weining Zhang and Wenbo Yu and Wenjie Liang and Xiang Kuang and Xiangmeng Cheng and Xiangyang Li and Xiaoquan Yan and Xiaowei Hu and Xiaoying Ling and Xing Fan and Xingye Xia and Xinyuan Zhang and Xinze Zhang and Xirui Pan and Xu Zou and Xunkai Zhang and Yadi Liu and Yandong Wu and Yanfu Li and Yidong Wang and Yifan Zhu and Yijun Tan and Yilin Zhou and Yiming Pan and Ying Zhang and Yinpei Su and Yipeng Geng and Yong Yan and Yonglin Tan and Yuean Bi and Yuhan Shen and Yuhao Yang and Yujiang Li and Yunan Liu and Yunqing Wang and Yuntao Li and Yurong Wu and Yutao Zhang and Yuxi Duan and Yuxuan Zhang and Zezhen Liu and Zhengtao Jiang and Zhenhe Yan and Zheyu Zhang and Zhixiang Wei and Zhuo Chen and Zhuoer Feng and Zijun Yao and Ziwei Chai and Ziyuan Wang and Zuzhou Zhang and Bin Xu and Minlie Huang and Hongning Wang and Juanzi Li and Yuxiao Dong and Jie Tang},
      year={2026},
      eprint={2602.15763},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2602.15763},
}

Files

87 files · 2.55 TBWeights 93.1 GB (smallest of 12 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 87 files with their sha256
FileSizesha256
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UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00001-of-00006.gguf9.43 MBcb792ba9c8dbcd7a45aede04ffc16c80b9f3b290423585e06835e0acf7081e17
UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00002-of-00006.gguf48.8 GBfd2a37a8d00ad2ab9b8e8691f8d16f4e9991d1eab2aaca14ec4b97568803aa87
UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00003-of-00006.gguf48.6 GB298edf5776b962f63643654bd85ed3ed91777b9a592dc3950b9002b08e320892
UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00004-of-00006.gguf49.3 GB97b097efd8c135246eb620d22438d17c57ad1fff19a0e5340ca9c9232f5f1de9
UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00005-of-00006.gguf49.3 GB17a5ef81a355d1cc4e771bedc7e2d688dab25892cf05bf26c2ddb5ae8230ffab
UD-Q5_K_XL/GLM-5.3-Flash-UD-Q5_K_XL-00006-of-00006.gguf44.3 GB47435d0287b2f5f023715ceff78b036d0ab63698708f0be54e3a8f30b76bc57d
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00001-of-00007.gguf9.43 MB7d7bd899640a594a32b1c7577c41fc00e56143e3b5731d3b9056bdc988f80f1c
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00002-of-00007.gguf49.4 GBc65caeffd822aab9810bf1049369f56e7b61c38217fa3c12f3dab2d21c0fd855
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00003-of-00007.gguf48.1 GB491f13fb641ecf27c30107e34a045b8cd00306b43559f3d0273687c47a154559
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00004-of-00007.gguf49.5 GB1db71efa40ba5f9ea017d12d744a8addf4025d3fd256f09e253967327a156270
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00005-of-00007.gguf48.9 GB41acb75b5105d49d89a21c3760d14c458f1e0c2b4e4fff08310c7cb2d5c3fff5
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00006-of-00007.gguf49.1 GB3f669d880bfce522063c677ddddd19f8b066f0d71701d2e123131f239b7fbf6b
UD-Q6_K_XL/GLM-5.3-Flash-UD-Q6_K_XL-00007-of-00007.gguf46.8 GB3623f4af825ea01d7cd65706c496ac2c11cb585dfa1a27189320b5790a535b00
imatrix_unsloth.gguf_file513 MB27d2ef6b6be0e314b373080f96322a1e4668b09b192664f3edc231c3b7c2d749
mmproj-BF16.gguf1.16 GB82b7adb44411dbb298b1c689567804e5ed0790d80f308ed8b5b6b8ac0527d2ac
mmproj-F16.gguf1.13 GB922b809664d6a89cc1e40bfeaa63618000edc6651baf4082ce0718a784adf947
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
a38483c8cd pinned now2026-11-14 06:28 UTC87 files · 2.55 TB

Use it

$ fw get unsloth/GLM-5.3-Flash-GGUF
# manifest sha256 3d8cafb0246c… · 2.55 TB · 87 files
$ fw verify ./GLM-5.3-Flash-GGUF unsloth/GLM-5.3-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-5.3-Flash-GGUF.json --dir ./GLM-5.3-Flash-GGUF $ python3 fw.py verify ./GLM-5.3-Flash-GGUF ./unsloth__GLM-5.3-Flash-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/GLM-5.3-Flash-GGUF --revision a38483c8cd5df544f53d70fb281afe97369d5ab6 --local-dir ./GLM-5.3-Flash-GGUF
llama.cppDownload one GGUF variant (UD-IQ1_S, 93.1 GB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/GLM-5.3-Flash-GGUF --include "UD-IQ1_S/*" --local-dir ./GLM-5.3-Flash-GGUF $ llama-server -m ./GLM-5.3-Flash-GGUF/UD-IQ1_S/GLM-5.3-Flash-UD-IQ1_S-00001-of-00003.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./GLM-5.3-Flash-GGUF/UD-IQ1_S/GLM-5.3-Flash-UD-IQ1_S-00001-of-00003.gguf\n' > Modelfile $ ollama create glm-5.3-flash-gguf -f Modelfile

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
Checked and recorded in the license audit. 2026-11-14
Text in
README.md
Text sha256
18d3309e9aab7bb22bbc5a2791fc1e831f776aaa26b251521cb7899920b87ce6
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-5.3-Flash-GGUFDate: 2026-11-14Commit: a38483cSigned: 2DC28CC7B26A283B ✓
Upstream
unsloth/GLM-5.3-Flash-GGUF
Pinned commit
a38483c8cd5df544f53d70fb281afe97369d5ab6
Manifest
GLM-5.3-Flash-GGUF.json · .minisig
Manifest sha256
3d8cafb0246c3f855f0e6d438dad8e780560141c26af9035db2b055921fe9453
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 06:28 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/GLM-5.3-Flash-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/GLM-5.3-Flash-GGUF.json.minisig $ minisign -Vm GLM-5.3-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-5.3-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-5.3-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-5.3-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