GLM-5.2 is a 744-billion-parameter Mixture-of-Experts language model with roughly
40B active parameters per token and a 1,000,000-token context window, released
under the MIT license. This product packages it as a turnkey inference server that
runs entirely inside your own AWS account and VPC. No data leaves your
environment, and there are no per-token fees beyond your EC2 costs.
The image ships GLM-5.2 (FP8), vLLM configured for 8-way tensor parallelism, the
matching NVIDIA driver and CUDA runtime, and a systemd-managed boot sequence that
provisions the model and starts the server without any manual steps.
HOW IT DEPLOYS
Launch on a supported GPU instance. On first boot the instance downloads the
GLM-5.2 weights over the internet and starts vLLM. It generates a unique random
API key for that instance and writes it to the EC2 system log. Once the server is
ready, it exposes an OpenAI-compatible endpoint:
http://<INSTANCE_PUBLIC_IP>:8000/v1
Initial startup takes approximately 40-45 minutes while the weights are retrieved
and loaded into GPU memory. The endpoint returns HTTP 503 until it is ready; poll
/health to detect readiness. See Usage Instructions for full detail.
EXTERNAL DEPENDENCIES
This product requires an internet connection to deploy properly. The following are
downloaded on deployment: GLM-5.2 model weights (approximately 750 GB) from a
public Amazon S3 bucket operated by Holbox AI. No ongoing external connection is
required after startup completes; the server runs fully offline thereafter.
Smaller instance types are not supported. GLM-5.2 at FP8 requires approximately
744 GB of aggregate GPU memory for weights alone, before KV cache.
DATA HANDLING AND SECURITY
No prompt or completion data is transmitted outside your instance. The generated
API key is stored at /opt/holbox/api_key with 0600 permissions, owned by root, and
mirrored to the EC2 system log for retrieval. Rotate it by running
/opt/holbox/rotate-key.sh; see Usage Instructions. Root login is disabled;
administrative access is via sudo from the default user over SSH key auth only.
Highlights
Frontier open-weight quality without the token bill. GLM-5.2 is a 744B-parameter MoE model with a 1M-token context window under the MIT license. Run it on your own GPUs and pay only for compute - no per-token API charges, no rate limits, no vendor lock-in.
Drop-in OpenAI-compatible endpoint. Point any OpenAI SDK, LangChain, LlamaIndex, or agent framework at http://<your-instance>:8000/v1 by changing the base URL and key. No SDK rewrites, no application changes.
Fully private, fully in your VPC. Prompts and completions never leave your AWS account. Suitable for regulated workloads and data-residency requirements where hosted model APIs are not an option.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
This listing bills by the hour for running the model on your chosen AWS GPU instance. You pick between two instance types, each a separate pricing dimension. The p5en.48xlarge and the p6-b200.48xlarge differ in their underlying GPU hardware. You pay only for the hours the instance runs, so cost scales with how long you keep the endpoint active. The software itself carries no charge, so each dimension reflects the hourly rate for that instance type. Select the instance that fits your performance needs and run time.
Top-of-mind questions for buyers
What distinguishes the two instance types I can run this endpoint on?
Each dimension maps to a different AWS GPU instance. The p5en.48xlarge and the p6-b200.48xlarge use different GPU hardware. You choose based on the throughput and performance your workload needs. Both bill per hour of running time for the same model.
Am I charged when the instance is stopped or the endpoint is idle?
Hourly charges apply only while the instance runs. If you stop or terminate the instance, software metering stops. Idle running instances still accrue hourly charges. You can set an auto-terminate window on deployment so idle GPUs stop billing instead of running unused.
Does the hourly rate cover the software, or only the instance?
The software itself carries no charge under this listing. Each dimension reflects the hourly rate tied to running the model on your chosen GPU instance type. You pay for the instance-hours you consume, and that cost scales with how long the endpoint stays active.
www.holbox.ai
Helpful?
Vendor refund policy
This product is offered free of charge by Holbox AI. There are no software charges,
and therefore nothing to refund through this listing.
You remain responsible for the AWS infrastructure costs of running it - the EC2
instance and its EBS root volume. Those are billed by AWS, not by Holbox AI, and are
not refundable through this listing. Stop or terminate instances when they are idle.
For questions about AWS charges, contact AWS Support or see
https://aws.amazon.com/marketplace/help/
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Initial release.
GLM-5.2 (744B MoE, FP8 weights) served via vLLM with 8-way tensor parallelism
OpenAI-compatible API on port 8000 (/v1)
Automatic weight provisioning on first boot (~750 GB)
Per-instance random API key generated at boot and written to the EC2 system log
Initial startup to ready state: approximately 20-25 minutes
Additional details
Usage instructions
PREREQUISITES
Your account must have an EC2 service quota for P5/P6 On-Demand instances
("Running On-Demand P instances", measured in vCPUs). p5en.48xlarge and
p6-b200.48xlarge each require 192 vCPUs. New accounts default to 0. Request an
increase at Service Quotas > Amazon EC2 > Running On-Demand P instances well
before launch; approval can take several business days. See
https://docs.aws.amazon.com/general/latest/gr/aws_service_limits.html
These instance families have constrained capacity. If launch fails with
InsufficientInstanceCapacity, try another Availability Zone, or use a Capacity
Reservation or ML Capacity Block.
LAUNCH
Subscribe to this product and choose Launch through EC2 (or Launch from Website).
Select p5en.48xlarge (recommended), p6-b200.48xlarge, or p5e.48xlarge. No other
instance types are supported.
Assign a security group. Restrict port 22 to your administrative CIDR and port
8000 to the CIDR of the clients that will call the API. Do not open port 8000 to
0.0.0.0/0.
Ensure the subnet provides outbound internet access (internet gateway, or NAT
gateway for private subnets). The instance must reach Amazon S3 to download the
model weights.
Launch.
WAIT FOR THE SERVER TO BECOME READY
*** Initial startup takes approximately 40-45 minutes. ***
The instance downloads approximately 750 GB of model weights and loads them into
GPU memory. The API returns HTTP 503 until this completes. Do not assume a failure
before 30 minutes have elapsed.
A unique random API key is generated on the first boot of each instance. It is not
baked into the image and is different for every instance you launch.
Via the console (no SSH required):
EC2 console > Instances > select your instance.
Actions > Monitor and troubleshoot > Get system log.
Find the API Key and Endpoint Url.
(The system log can take a few minutes to populate after boot.)
Example:
Status : READY
Model name : glm-5.2-fp8
Endpoint URL : http://<public-ip>:8000/v1
API key : sk-glm-xxxxxxxx...
Via SSH:
ssh -i <your-key.pem> ubuntu@<INSTANCE_PUBLIC_IP>
sudo cat /opt/holbox/api_key
CALL THE ENDPOINT
Base URL: http://<INSTANCE_PUBLIC_IP>:8000/v1
Replace <INSTANCE_PUBLIC_IP> with the public IP shown in the EC2 console.
EC2 console > Instances > select your instance > Status checks tab. Both
system and instance checks must pass.
Service status: glm-status
If /health does not return 200 after 35 minutes, check journalctl for weight
download errors (usually a missing route to the internet) or CUDA OOM (usually an
unsupported instance type).
There are no additional AWS resource charges: the product uses only the EC2
instance and its EBS root volume. Instances are billed while running regardless of whether the endpoint is being called; stop or terminate instances when idle. Note that stopping and restarting triggers the model load again (though not the download).
Support description: Support is provided via email for product installation, deployment, configuration, and troubleshooting. Assistance includes AMI startup problems, endpoint availability, and product-specific questions. Please include your AWS Region, CloudFormation stack events, and relevant logs when contacting support to help us investigate issues more efficiently.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Private OpenAI-compatible vLLM endpoint serving Qwen3-4B on a GPU EC2 instance in your account. Function/tool calling and 32K context. Returns an endpoint URL and API key.
Self-hosted GLM 5.3 Flash served via SGLang with an OpenAI-compatible API. Weights are fetched from public S3 at first boot and an API key is auto-generated.
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