Sold by: FriendliAI
Deployed on AWS
Unleash the power of your generative AI with Friendli Engine, the fastest LLM serving engine on the market! Friendli Suite offers three options to suit your preferences: Friendli Container, Friendli Dedicated Endpoints, and Friendli Serverless Endpoints.
4.2
Overview
Friendli Suite is our SaaS service powered by Friendli Engine, the fastest LLM serving engine on the market. Friendli Suite offers three options to suit your preferences:
Friendli Container: Deploy the engine on your own infrastructure for ultimate control. Friendli Dedicated Endpoints: Run any custom generative AI models on dedicated GPU instances in autopilot. Friendli Serverless Endpoints: No setup required, simply call our APIs and let us handle the rest. The Friendli Engine cuts LLM inference serving costs by 40-80% while providing low latency and high throughput during LLM serving. Friendli Engine employs various specialized optimizations, including our groundbreaking iteration batching (a.k.a. continuous batching) technology, protected by patents in the United States and Korea. Experience the extraordinary performance of LLM serving on the Friendli Suite!
Highlights
- Innovation for high speed and low cost
- Effortless deployment
- Automatic management
Details
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
$5,000 | $5,000 Friendli Suite Plan | $5,000.00 |
$10,000 | $10,000 Friendli Suite Plan | $10,000.00 |
$20,000 | $20,000 Friendli Suite Plan | $20,000.00 |
The following dimensions are not included in the contract terms, which will be charged based on your usage.
Dimension | Description | Cost/unit |
|---|---|---|
Usage Fee | Additional Usage Fee | $0.01 |
Dimensions summary
You buy Friendli Suite through a contract plan at one of three fixed commitment levels: $5,000, $10,000, or $20,000. Each plan sets a prepaid amount you draw against as you run AI inference. The plans share the same structure and differ only by the committed dollar amount you select. If your usage goes beyond your plan's committed amount, the Additional Usage Fee covers that overage. This lets you pick a commitment that matches expected demand while still allowing room to scale past it.
Top-of-mind questions for buyers
Your committed amount funds AI inference you run through FriendliAI. You draw against it as you generate output. Inference can be billed per token for model API usage or per GPU time for dedicated compute, depending on how you deploy.
The Additional Usage Fee covers any inference beyond your committed amount. You keep running without stopping at the limit. Overage accrues under the usage fee dimension rather than requiring you to move to a different plan.
For on-demand dedicated inference, you pay for the compute you use, billed per second, with no extra charges for start-up time. Serverless model API usage bills per token, so you pay only for processed input and output, not idle time.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Customer reviews
Gaurav S.
Friendli AI – Optimizing AI Performance, Scalability, and Operational Efficiency
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
What I like best about Friendli AI is its focus on fast and efficient AI model inference, helping applications generate responses with low latency and optimized resource utilization. It supports scalable AI deployment and makes it easier to integrate AI capabilities into business workflows, improving automation potential, productivity, and overall operational efficiency.
What do you dislike about the product?
One area for improvement is making model deployment and configuration more intuitive, especially for users without a strong technical background. Clearer documentation, simpler integration options, and more transparent pricing and performance comparisons would make Friendli AI easier to adopt and manage for different business needs.
What problems is the product solving and how is that benefiting you?
Friendli AI helps optimize AI model deployment and inference, enabling faster response generation and more efficient use of computing resources. This can reduce latency, support scalable AI-powered workflows, and improve the efficiency of automation initiatives. It helps businesses explore AI solutions that reduce manual effort, streamline operations, and enhance overall productivity.
Prateek M.
Fast, Reliable Inference with a Great Dashboard and Helpful Docs
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
I really like the inference speed they provide. We mainly fine-tune several models for our document extraction, so inference needs to be fast, and this platform has been reliable, quick, and works well for us. The dashboard also has a very good user interface, and the support documentation helped us get set up without spending a lot of time at the beginning. Integration with other platforms, mainly Hugging Face, was smooth as well. I also really like their AI-based inference optimizations.
What do you dislike about the product?
Their pricing model isn’t very transparent, since it’s charged per endpoint and per GPU hour, so the overall cost can add up quickly. Also, the advanced settings for modifying our AI models took some time to understand and figure out.
What problems is the product solving and how is that benefiting you?
The main challenge for us was finding a reliable, fast platform where we could host our AI models. Previously, we ran our models on other platforms, but they came with several issues. With this platform, any modification is quick, and it’s reliable, which helps ensure our main pipeline runs fast and consistently. It has also improved our processing time overall.
Construction
Flexible Friendli AI Deployment Across Hardware, Containers, and Serverless APIs
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
We can deploy Friendli AI with our own hardware, containers or serverless APIs. This creates flexibility for where we choose to use the product and keep the deployment as close as possible to the use case. Onboarding is made easier since we don't have to buy brand new hardware.
What do you dislike about the product?
The UI can use a bit more polish. It is getting there but I think as the product continues to mature, the UX will come along with it.
What problems is the product solving and how is that benefiting you?
Friendli is helping us with integrations throughout the entire organization. We have a lot of data points and this is really helping to tie it all together.
Igor Z.
High-Performance AI Inference with Low Latency, Autoscaling, and Easy OpenAI-Compatible Integration
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
What I appreciate most is its focus on high-performance AI inference without the operational complexity of managing GPU infrastructure. The combination of low latency, high throughput, and autoscaling is particularly valuable. It has OpenAI-compatible APIs and built-in monitoring, making it easier for us to integrate AI workloads into existing flows while maintaining scalability, reliability, and cost control.
What do you dislike about the product?
The main drawback is limited integration with enterprise observability platforms and, at some scale, a complex onboarding process.
What problems is the product solving and how is that benefiting you?
Complexity and cost of deploying and scaling AI inference workloads.
Irfaana H.
Simplifies AI Model Experimentation, Though Some Settings Take Learning
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
I appreciate that Friendli AI makes working with AI models feel more manageable, especially while I’m still learning the technical side. It makes it easier to test different models without worrying too much about the infrastructure, and helps me understand their speed and responsiveness. It saves me time on the technical side so I can focus more on exploring what AI can do and how I can apply it to my everyday tasks. The initial setup was straightforward.
What do you dislike about the product?
I think Friendli AI could be a little more approachable for users without a strong technical background. Some features and settings take a bit of time to understand, especially when I’m just experimenting rather than developing AI applications professionally.
What problems is the product solving and how is that benefiting you?
I can run and test different AI models without getting caught up in complicated infrastructure or technical setup. Friendli AI saves me time on the technical side and helps me understand model speed and responsiveness, so I can focus on exploring what AI can do and how to apply it to my everyday tasks.