GLM 5.3 Download: Official Weights, Real File Sizes, and Apps

Quick answer: the only official GLM 5.3 download is the model weights, published by Z.ai at zai-org/GLM-5.3 on Hugging Face (mirrored as ZhipuAI/GLM-5.3 on ModelScope). The default FP8 checkpoint is about 756 GB, and serving it needs a multi-GPU server, not a laptop. If you only want to chat with GLM 5.3 or call it from code, you do not need to download anything: use it in a browser or through an API.

We checked the Hugging Face repositories and license file, the official vLLM and Unsloth deployment pages, Ollama's model library, Z.ai's ZCode download page, and the US App Store and Google Play listings on November 5, 2026. File sizes come from the Hugging Face API file listings. We did not run the full model on our own hardware for this article.

Two people type "GLM 5.3 download"Copy Anchor Link

Search data for this query mixes two groups who want different things:

1. People who want the model files. They want to run GLM 5.3 on their own hardware, fine-tune it, or keep data off third-party servers.
2. People who want an app. They want a GLM 5.3 program on their phone or desktop, the way ChatGPT or Claude have apps.

Most download guides answer only the first group, and many still repeat launch-week claims that the weights are "coming soon." That changed on August 25, 2026, when the repositories went public. This page covers both groups, with the real numbers. It also gives a rule for when downloading is worth it and when it just costs you a weekend and a very large disk.

Which GLM 5.3 files can you download?Copy Anchor Link

Four official repositories exist under zai-org on Hugging Face. Sizes below are the sum of every file in each repo, from the Hugging Face API on November 5.

A few points that most guides skip:

• FP8 is the default, not a cut-down copy. The vLLM recipe calls the zai-org/GLM-5.3 checkpoint "native FP8"; BF16 weights live in the separate -BF16 repo. You only need BF16 if your hardware or fine-tuning setup requires it.
• The parameter count depends on who is counting. The vLLM recipe lists GLM 5.3 as a ~743B MoE with 39B active per token; Unsloth's guide says 744B with 40B active. Hugging Face's checkpoint metadata counts about 753B, which likely includes extra layers such as the multi-token-prediction head. All of these describe the same files. The size you budget for is the ~756 GB on disk.
• The code is on GitHub, the weights are not. github.com/zai-org/GLM-5 holds inference examples and deployment notes. There is no separate GLM 5.3 weights repo on GitHub.
• Flash is the smaller download, but it is not small. If you searched "glm 5.3 download size" because of Flash, the per-layer breakdown and hardware fit are in our GLM 5.3 Flash parameters and size guide.

For release history and what changed from GLM 5.2, see GLM 5.3 weights: release timeline and specs. In short, GLM 5.3 uses the same base model as GLM 5.2, and all the gains come from post-training.

Is the GLM 5.3 download free, and can you use it commercially?Copy Anchor Link

Yes, the files cost nothing, and the license is close to MIT, with one difference to know about. The LICENSE file in zai-org/GLM-5.3 grants the usual rights to use, copy, modify, fine-tune, redistribute, and sell. It adds one condition. If you run a "Model as a Service" business (giving third parties API-style inference or fine-tuning) and your group's revenue is over $10 billion in any 12 months, you must pass a Z.ai security review before commercial use. For nearly every individual, startup, and mid-size company, that clause never applies.

GLM 5.3 Flash is plain MIT. Either way, "open source download" here means open weights: you get the trained model, not the training data.

How to download GLM 5.3 weights (step by step)Copy Anchor Link

Before you start, check three things. They catch most failed attempts:

1. Disk: at least ~800 GB free for FP8 (more if you keep a converted copy), on fast NVMe storage you can serve from.
2. Bandwidth: at a steady 1 Gbps, 756 GB takes about 1 hour 40 minutes. The BF16 repo takes about 3 hours 20 minutes at the same speed. Slower links scale linearly.
3. Target hardware: see the next section. Downloading weights you cannot load is the most common waste of time.

Then use the Hugging Face CLI:

pip install -U "huggingface_hub[cli]"

# Flagship GLM 5.3, native FP8 (about 756 GB)
hf download zai-org/GLM-5.3 --local-dir ./GLM-5.3

# Or the smaller GLM 5.3 Flash (about 328 GB)
hf download zai-org/GLM-5.3-Flash --local-dir ./GLM-5.3-Flash

The repos are not gated, so you do not need to accept terms first. A logged-in token still helps with rate limits on downloads this large. If Hugging Face is slow from your region, the ModelScope mirror ZhipuAI/GLM-5.3 carries the same model under the same license.

To serve it, Z.ai's model card lists SGLang, vLLM, TokenSpeed, Transformers, KTransformers, and Unsloth. The vLLM recipe's standard launch on one 8-GPU node is:

VLLM_USE_RUST_FRONTEND=1 vllm serve zai-org/GLM-5.3 \
  --tokenizer-mode glm5_next \
  --kv-cache-dtype fp8 \
  --tensor-parallel-size 8 \
  --tool-call-parser glm47 \
  --reasoning-parser glm47 \
  --enable-auto-tool-choice \
  --served-model-name glm-5.3

The recipe requires vLLM 0.29.0 or newer, built with native GLM5Next support. Pin the version it names instead of guessing. For SGLang settings, quantization choices, and a preparation checklist, see our GLM 5.3 local deployment guide.

The hardware reality checkCopy Anchor Link

This table shows what each download path needs before it produces a single token.

Two cautions. First, the GGUF quantizations come from the community (Unsloth), not from Z.ai. Unsloth reports that its 2-bit build reaches about 81% top-1 agreement with the full model. That is useful for trying the model, but it is not the model Z.ai benchmarked. Second, a consumer GPU with 24 GB or 48 GB cannot run any version of the flagship. If your machine is a gaming PC or a normal laptop, the download path stops here.

What about Ollama?Copy Anchor Link

ollama run glm-5.3 is the command people try first. As of November 5, the only tag in Ollama's GLM 5.3 library is glm-5.3:cloud, and GLM 5.3 Flash also has only a cloud tag. The model runs on Ollama's servers, so nothing is downloaded to your machine. To run GLM 5.3 fully offline, use the GGUF files with llama.cpp or the full weights with vLLM or SGLang.

Is there an official GLM 5.3 app to download?Copy Anchor Link

Partly. Here is what we found on November 5:

• ZCode (desktop, official). Z.ai calls ZCode the "official harness for GLM-5.3." It is a multi-agent coding app for macOS (Apple Silicon and Intel), Windows (x64 and ARM64), and Linux (AppImage), version 3.17.2 at the time of checking. You install the app, but the model still runs on Z.ai's servers. ZCode does not download the GLM 5.3 weights, and it is built for coding, not general chat.
• Mobile apps. A search for "z.ai" in the US App Store found no app from Z.ai. On Google Play, apps with "Z.ai" or "GLM" in their names came from other developers. Before you install one, check the developer name. An app that only uses the name is not an official GLM 5.3 app.
• Web chat. Z.ai's own chat at chat.z.ai runs in the browser. You don't install anything, but it is Z.ai's interface and plan structure.

So for most people, the "app" is a browser tab.

Download or not? A decision boxCopy Anchor Link

Here is the cost logic behind the last row. Weights are free, but 8 high-memory GPUs are not, and they cost money whether or not you send traffic. A hosted API charges per token instead. Take a team that sends 20M input tokens and 2M output tokens a month at GLM 5.3's $1.40 / $4.40 per 1M rate. That works out to $28 + $8.80 = $36.80 for the month. That workload is nowhere near the point where buying or renting a GPU node makes sense. For more ways to cut the token bill, see our GLM 5.3 pricing breakdown.

The no-download route: GLM 5.3 on glm5.appCopy Anchor Link

If the decision box sent you to "don't download," glm5.app is one option. It is an independent third-party service, not Z.ai. It hosts GLM 5.3 alongside GLM 5.3 Flash, FlashX, and GLM 5.2, in two forms:

• In the browser: open GLM 5.3 on glm5.app and start a chat on any device. Free accounts get a small daily allowance on GLM 5.3 Flash plus welcome credits. Unlimited GLM 5.3 chat (fair use) comes with the Plus plan.
• As an API: an OpenAI-compatible endpoint at https://glm5.app/api/v1 with model ID glm-5.3, billed at $1.40 input / $4.40 output per 1M tokens. One key and one credit balance cover GLM 5.3, 5.2, and Flash, and there are no Coding Plan endpoint rules to work around. API access unlocks after your first purchase. The API quickstart shows the base URL and key setup.

If you don't want a subscription, one-time credit packs start at $12, never expire, and accept Alipay and WeChat Pay as well as cards. All options are on the pricing page.

Use Z.ai directly instead if you need its Coding Plan inside ZCode, or if your company already has a Z.ai contract. Use the downloaded weights if your data cannot leave your own servers. glm5.app is for everyone else: people who want GLM 5.3 working today without a 756 GB download.

FAQCopy Anchor Link

Where can I download GLM 5.3? From Hugging Face at zai-org/GLM-5.3 (FP8) or zai-org/GLM-5.3-BF16, or from the ModelScope mirror ZhipuAI/GLM-5.3. These are the only official sources. GitHub (zai-org/GLM-5) hosts code and deployment examples, not weights.

Is the GLM 5.3 download free? Yes. The weights are free to download and use commercially under the GLM-5.3 License. The only extra condition applies to model-as-a-service businesses with over $10 billion in yearly revenue. Running them is not free: you pay for the hardware.

What is the GLM 5.3 download size? About 756 GB for the default FP8 checkpoint and about 1,507 GB for BF16. GLM 5.3 Flash is about 328 GB (FP8). Community 2-bit GGUF builds of GLM 5.3 are about 239 GB. The Flash size guide covers Flash in detail.

Can I download GLM 5.3 for my PC or laptop? You can download it, but a normal PC cannot run it. The smallest practical build needs about 223 to 256 GB of combined memory. On a typical machine, use GLM 5.3 in the browser or through an API instead.

Is GLM 5.3 open source? It is open-weight. The trained weights are public under a permissive license, and inference code is on GitHub. The training data is not released.

Is there a GLM 5.3 app for iPhone or Android? We did not find a mobile app published by Z.ai as of November 5, 2026. Treat store listings that use the GLM or Z.ai name with caution. The official desktop app is ZCode, a coding agent. For chat on a phone, use a browser.

SourcesCopy Anchor Link

• zai-org/GLM-5.3 on Hugging Face — official weights, model card, supported inference frameworks; file sizes summed from the repo listing. Checked November 5, 2026.
• GLM-5.3 License — usage rights and the $10B model-as-a-service security-review clause.
• vLLM recipe for GLM-5.3 — 743B/39B MoE description, native FP8 default, 8x H200/H20 single-node and 8x B200 full-context hardware, launch flags.
• Unsloth: GLM-5.3 how to run locally — community GGUF sizes (2-bit ~239 GB) and total-memory requirements. These are community quantizations, not Z.ai releases.
• ZCode download page — Z.ai's official desktop harness for GLM-5.3, with platforms and version as of the check date.

File sizes, app availability, and Ollama tags change. Re-check the linked pages before you buy hardware or start a long download.