Sold by: Salient Engineering
Deployed on AWS
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A self-hosted, production-ready Qwen 3 8B model deployed into your AWS environment with a single click. Because everything runs entirely within your private cloud, your data stays secure, isolated, and fully under your control. Best of all, unlimited tokens.
Overview
This is a self-hosted deployment of the Qwen 3 8B 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. Once the instance is powered on, the server requires 10 minutes to load the LLM before it is ready to serve requests. Highlights of the Qwen 3 model include:
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Causal language model with 8.2 billion parameters (6.95 billion non-embedding), 36 layers, and grouped-query attention with 32 query heads and 8 key-value heads.
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Native context length of 32,768 tokens, and up to 131,072 tokens with YaRN.
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Switches between thinking mode for reasoning, math, and coding, and non-thinking mode for general dialogue. Thinking can also be toggled per turn with /think and /no_think.
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Tool calling and agent workflows in both thinking and non-thinking modes.
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Support for 100+ languages and dialects, including multilingual instruction following and translation.
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Fully open-source under the Apache 2.0 license, allowing for unrestricted commercial use.
Highlights
- Data security, privacy, and confidentiality
- Predictable cost
- Unlimited usage of a dedicated model
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
g6e.xlarge Recommended | $0.09 |
Dimensions summary
You pay by the hour for running this model on a single g6e.xlarge instance. This is usage-based pricing, so your cost tracks the time the instance stays running. There are no tiers or upfront commitments to choose between. You start and stop the instance as needed, and billing follows actual runtime. The model runs as a causal language model with a 32,768-token context length. Scaling to more capacity means running the instance for more hours.
Top-of-mind questions for buyers
You run the model on a single g6e.xlarge instance. This is a GPU-backed AWS instance type sized for one machine. You pay per hour that instance stays running. Scaling capacity means running the instance for more hours or launching more instances.
Hourly software charges apply only while the instance runs. A stopped instance does not accrue software charges. You may still pay separate AWS storage fees for the stopped instance's attached volumes, but the software meters running time only.
No. Billing tracks instance runtime only, not tokens processed or features used. The model supports a 32,768-token context and can switch between reasoning and general dialogue modes. These affect performance, not your hourly cost. Longer or more complex requests may need more runtime.
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Vendor refund policy
Refunds may be considered on a per-case basis. Please contact us at support@salientengineering.com for inquiries.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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 the instance is powered on for the Ollama service to fully load the LLM. Ollama is exposed on port 11434.
Test via HTTP with: curl -X POST http://<PUBLIC_IP>:11434/api/generate -d '{"model":"qwen3:8b","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)
- After the instance is powered on, allow 10 minutes for the server to load the LLM before sending requests.
- Access the Qwen 3 8B 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":"qwen3:8b","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.
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