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 is over HTTPS on port 443 with a per-instance API key; Ollama itself listens only on localhost. GPU instance types need EC2 quota for "Running On-Demand G and VT instances" (L-DB2E81BA), which new AWS accounts often have set to 0. Once the instance is powered on, the model is ready in about 4 minutes. 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 |
|---|---|
g4dn.xlarge Recommended | $0.09 |
g6e.xlarge | $0.09 |
c7i.2xlarge | $0.09 |
m7i.2xlarge | $0.09 |
c7i.4xlarge | $0.09 |
g4dn.2xlarge | $0.09 |
g6.xlarge | $0.09 |
g5.xlarge | $0.09 |
Dimensions summary
You pay by the hour for the machine that runs this model, not for tokens used. The model runs in your own AWS account. Pricing is set per EC2 instance type, so your hourly rate depends on which instance you pick. GPU-backed instances (g6e.xlarge, g4dn.xlarge, g4dn.2xlarge, g6.xlarge, g5.xlarge) suit model inference. CPU-based instances (c7i.2xlarge, c7i.4xlarge) and general-purpose instances (m7i.2xlarge) offer other options. Choose the instance that matches your workload, and your total cost scales with the hours you run it.
Top-of-mind questions for buyers
You pay for the EC2 instance that runs the model, charged per hour it runs. You are not charged per token processed. The rate covers the software running on that specific instance type. Underlying AWS compute and storage fees are separate and billed by AWS.
The hourly software charge applies while the instance runs. When you stop the instance, the hourly software meter stops. AWS may still charge for attached storage on a stopped instance, but the model's hourly fee meters running time only.
Each listed instance type carries its own hourly rate. GPU-backed instances (g6e.xlarge, g4dn.xlarge, g4dn.2xlarge, g6.xlarge, g5.xlarge) handle model inference work. CPU instances (c7i.2xlarge, c7i.4xlarge) and the general-purpose m7i.2xlarge offer alternatives. Your bill reflects only the single instance type you launch.
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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.
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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
HTTPS on port 443 with a per-instance API key (Bearer). Ollama now listens on 127.0.0.1:11434 only and OLLAMA_ORIGINS is no longer "*" (set SALIENT_ALLOWED_ORIGINS to allow browser apps). The baked model is read off EBS in parallel at boot, so it is ready in about 4 minutes instead of up to 90. The EC2 system log and the SSH login banner show the endpoint, API key, TLS fingerprint and example requests. Added instance types: c7i.2xlarge, m7i.2xlarge, g4dn.xlarge, c7i.4xlarge, g4dn.2xlarge, g6.xlarge, g5.xlarge.
Upgrading from an earlier version: clients that called http://:11434 must switch to https:// with the API key, or set SALIENT_EXPOSE_OLLAMA_HTTP=1 in user data to keep the old plain-HTTP listener.
Additional details
Usage instructions
Before you launch: GPU instance types need the EC2 quota "Running On-Demand G and VT instances" (quota code L-DB2E81BA) in your Region to be at least the instance's vCPU count (g4dn.xlarge = 4 vCPUs). New AWS accounts often have 0, and the launch then fails. Check it or request an increase at https://console.aws.amazon.com/servicequotas/home/services/ec2/quotas/L-DB2E81BA before you subscribe.
- Launch on g4dn.xlarge or another listed type. In the Security Group, allow inbound TCP 443 from the addresses that will call the API, and TCP 22 only if you need SSH.
- Wait about 4 minutes. EC2 console > your instance > Actions > Monitor and troubleshoot > Get system log shows "Salient LLM appliance: READY" with the endpoint, API key and examples. Status at any time: curl -k https://<PUBLIC_IP>/healthz
- Call the API with the key from the system log (or /home/ubuntu/salient-api-key over SSH): curl -k https://<PUBLIC_IP>/api/tags -H "Authorization: Bearer <API_KEY>" curl -k https://<PUBLIC_IP>/v1/chat/completions -H "Authorization: Bearer <API_KEY>" -H "Content-Type: application/json" -d '{"model":"qwen3:8b","messages":[{"role":"user","content":"Hello"}]}'
- The TLS certificate is self-signed: use -k, or pin the SHA-256 fingerprint printed in the system log. For a trusted certificate, set SALIENT_DOMAIN and SALIENT_LETSENCRYPT_EMAIL in user data (needs a DNS record and TCP 80 open), or run sudo salient-enable-letsencrypt DOMAIN EMAIL. Settings (your own API key, allowed browser origins, context length) go in /etc/salient/salient.conf or EC2 user data, for example SALIENT_ALLOWED_ORIGINS=https://app.example.com .
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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