Sold by: Salient Engineering
Deployed on AWS
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A self-hosted, production-ready Qwen 2.5 7B 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 2.5 7B 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 2.5 7B model include:
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Delivers stronger knowledge coverage with major gains in coding and mathematical reasoning, powered by domain-optimized expert components.
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Provides robust instruction following, improved long-form generation (8K+ tokens), better comprehension of structured data such as tables, and more reliable structured outputs like JSON; also handles diverse system prompts more consistently for role-play and chatbot control.
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Supports extended context windows up to 128K tokens with generation capability of up to 8K tokens.
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Offers multilingual capabilities across 29+ languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
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 24.04
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.2xlarge Recommended | $0.09 |
g5.2xlarge | $0.09 |
g5.xlarge | $0.09 |
Dimensions summary
You pay by the hour for the GPU instance that runs this model in your own AWS account. Three instance sizes are available: g5.xlarge, g5.2xlarge, and g6e.2xlarge. Each represents a different compute configuration, so you pick the one that fits your workload. Billing is usage-based, charged per hour the instance runs. You pay for the machine, not for tokens or request volume. There are no upfront commitments or fixed terms. Costs scale with how long you keep an instance running and which size you select.
Top-of-mind questions for buyers
Each name maps to a different AWS GPU instance type with its own compute, memory, and GPU configuration. You pick the size that fits how you run the model. The hourly software rate differs by instance because each delivers a different amount of compute capacity.
The software fee meters each hour the instance runs. When you stop the instance, the hourly software charge stops too. Stopped instances may still incur underlying AWS storage fees for attached volumes, but those are separate from the model's hourly charge.
No. You pay for the machine, not for tokens or request volume. The charge is based only on the instance size you select and how many hours it runs. Sending more requests during a running hour does not raise the cost.
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Vendor refund policy
Customers will be charged for usage. Subscriptions can be cancelled at anytime, however, usage fees are non-refundable.
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Content disclaimer
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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
In this release, we've fixed some bugs and optimized the GPU for maximum token throughput. Configured for production environments, please allow 10 minutes once launched for the Ollama service to fully boot the model. Ollama is exposed on ports 443 and 11434.
Test via HTTPS with: curl -X POST -k https:///api/generate -d '{"model":"qwen2.5:7b","prompt":"In one sentence, explain what a large language model is capable of."}'
Test via HTTP with: curl -X POST http://:11434/api/generate -d '{"model":"qwen2.5:7b","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, 443, and 11434 from your trusted IP address(es)
- Access the Qwen 2.5 7B model via the Ollama service exposed on port 443 for HTTPS or port 11434 for HTTP.
Test via HTTPS with: curl -X POST -k https://<Instance Public DNS Address>/api/generate -d '{"model":"qwen2.5:7b","prompt":"In one sentence, explain what a large language model is capable of."}'
Test via HTTP with: curl -X POST http://<Instance Public DNS Address>:11434/api/generate -d '{"model":"qwen2.5:7b","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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