Overview
This is a self-hosted deployment of the Qwen 3.8 27B large language model. It runs as a single GPU-powered EC2 instance allowing you to keep your data private and leverage unlimited tokens. Access to the model is via HTTPS, ensuring data is encrypted in-transit at all times. Highlights of the Qwen 3.8 model include:
-
Dense 27B causal language model with a native vision encoder for image and video understanding, including STEM diagrams, documents, and hour-scale video.
-
Native context window of 262,144 tokens, extensible up to 1,000,000 tokens with YaRN.
-
Thinking mode is on by default and can be disabled per request; reasoning depth is tunable with reasoning_effort, and preserve_thinking retains reasoning context across turns.
-
Stronger agent execution for autonomous planning and end-to-end task completion, with published scores including 61.7 on SWE-bench Pro and 84.3 on OSWorld-Verified.
-
Hybrid Gated DeltaNet and Gated Attention architecture, with Multi-Token Prediction (MTP).
-
Fully open-source under the Apache 2.0 license.
Highlights
- Data security, privacy, and confidentiality
- Predictable cost
- Unlimited usage of a dedicated model
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
Pricing
Dimension | Cost/hour |
|---|---|
g6e.2xlarge Recommended | $0.09 |
Vendor refund policy
Refunds may be considered on a per-case basis. Please contact us at support@salientengineering.com for inquiries.
How can we make this page better?
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
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
Configured for production environments, please allow 10 minutes once launched for the Ollama service to fully boot the model. Ollama is exposed on port 11434.
Test via HTTP with: curl -X POST http://<PUBLIC_IP>:11434/api/generate -d '{"model":"qwen3.8:27b","prompt":"In one sentence, explain what a large language model is capable of."}'
Additional details
Usage instructions
- Deploy the EC2 instance, configure the Security Group to only allow inbound port 22 and 11434 from your trusted IP address(es)
- Access the Qwen 3.8 27B model via the Ollama service exposed on port 11434 for HTTP.
Test via HTTP with: curl -X POST http://<PUBLIC_IP>:11434/api/generate -d '{"model":"qwen3.8:27b","prompt":"In one sentence, explain what a large language model is capable of."}'
Resources
Vendor resources
Support
Vendor support
The Salient Engineering support team can be reached at: support@salientengineering.com
Our team is happy to assist with deployment and configuration issues.
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.