GLM-5.3 Flash
Z.ai’s open-weight 321B-total / 18B-active multimodal agent model. Self-host the native FP8 checkpoint on a documented multi-GPU Linux server or rented GPU Pod; use Strix for an authorized repository review.
What do you want to do?
Choose a task. Get the software, files, settings, and steps to run it.
Build a private AI agent with GLM-5.3 Flash
Serve GLM-5.3 Flash · FP8 privately, connect Hermes to the model endpoint, and have the agent inspect files and produce a review checklist.
Code with GLM-5.3 Flash in VS Code + Cline
Serve GLM-5.3 Flash · FP8 privately, connect VS Code and Cline, then review and test a real code change.
Run GLM-5.3 with Strix for Authorized Security Reviews
Choose GLM-5.3 Flash or full GLM-5.3, then run Strix with a self-hosted Linux cluster, rented RunPod GPUs, or the OpenRouter hosted API to review a disposable repository you are authorized to assess.
Open a guide for its software, hardware requirements, and setup steps.
At a glance
- Parameters
- 321B total · 18B active
- Architecture
- Mixture of experts; hybrid KDA and sparse MLA
- Context length
- 1,048,576 architectural maximum; practical limit depends on GPU memory
- License
- MIT
- Disk space
- 306 GB
- Software
- vLLM, Strix, RunPod
Will it run on your machine?
Save your machine to see a personalized rating and its reasoning.
Add my hardwareBest for
- Self-host a tool-using agent for an authorized source-code security review.
- Serve a private multimodal reasoning model on a suitable multi-GPU Linux host.
Tradeoffs
- The 1M architectural context is not a practical default on the recommended hardware.
- Native FP8 weights cannot run on a single consumer GPU; no compact quantized package is verified in this guide.
- No native Windows or Apple Silicon GPU-server route is claimed.
Ways to run it
vLLM · Linux · 4× GB200 or rented RunPod Pod
Publisher standard NVIDIA topology; verify the current vLLM container and FlashInfer version. The specialized text-only H200 offload result is a separate recipe.
vllm serve zai-org/GLM-5.3-Flash --host 127.0.0.1 --port 8000 --tensor-parallel-size 4 --max-model-len 16384 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choicevLLM ROCm · Linux · 4× MI355X
Use the AMD-specific publisher recipe and compatible ROCm build.
Official instructionsExplore its uses
Sources and files
Primary sources and files behind this model page.
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