Sold by: Salient Engineering
Deployed on AWS
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A self-hosted, production-ready Gemma 4 26B model, with 4 billion active parameters 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 Gemma 4 26B A4B 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. The model is preloaded into GPU memory on boot, so the first prompt does not wait for a cold load. Once the instance is powered on, the model is ready in about 8 minutes. Highlights of the Gemma 4 26B model include:
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Advanced Reasoning - Every model in the family is built for strong reasoning performance, with adjustable thinking modes to fit different use cases.
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Expanded Multimodal Support - Handles text and images with flexible aspect ratio and resolution support across all models, plus native video and audio capabilities on the E2B and E4B models.
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Flexible and Efficient Architectures - Includes both Dense and Mixture-of-Experts (MoE) model variants in multiple sizes, enabling scalable deployment options.
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Built for On-Device Performance - Smaller models are optimized for efficient local use on laptops, smartphones, and other mobile devices.
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Larger Context Windows - Small models support up to 128K context, while medium models extend this to 256K for more complex tasks.
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Stronger Coding & Agentic Performance - Delivers significant gains on coding benchmarks and includes native function-calling support for powerful autonomous agent workflows.
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Native System Prompting - Gemma 4 adds built-in system role support, allowing for more structured, guided, and controllable interactions.
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 |
|---|---|
g6.xlarge Recommended | $0.09 |
g5.2xlarge | $0.09 |
g6e.2xlarge | $0.09 |
g5.xlarge | $0.09 |
g6e.xlarge | $0.09 |
Dimensions summary
You pay by the hour for the EC2 instance that runs this model in your own AWS account. There are no token or usage fees beyond the instance time. The five dimensions map to different GPU instance types and sizes. The g5.xlarge and g6.xlarge give you single-GPU options, while the g5.2xlarge and g6e.2xlarge provide more capacity. The g6e.xlarge adds another single-GPU choice. You pick the instance that fits your workload, and your cost scales with the hours you run it.
Top-of-mind questions for buyers
You pay for the EC2 machine that runs the model, billed per hour it runs. You are not charged per token or per request. The model runs inside your own AWS account, so your cost is tied to the instance size you pick and how long it stays running.
The software fee meters running time only. When you stop the instance, the hourly model charge stops accruing. You may still pay underlying AWS storage fees for the stopped instance, but those are separate from the model fee. Start the instance again to resume model charges.
Each option bills independently at its own hourly rate. You run one instance type at a time, so only that instance's rate applies. The xlarge options are single-GPU; the 2xlarge options give more capacity. You pick one based on your workload, and hours on that instance drive your cost.
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Refunds may be considered on a per-case basis. Please contact us at support at 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 8 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: g6.xlarge, g5.xlarge, g6e.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 (g6.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 g6.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 8 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":"gemma4:26b","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
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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