Why Turnkey Solutions
Accelerate Time to Business Value
Turnkey solutions bring together validated hardware, software, and models, accelerating deployment and simplifying ongoing operations. AMD technology-powered solutions combine high-performance compute with an open software ecosystem and experienced partners—giving you the flexibility to choose the right solution, keep sensitive data under your governance, and manage costs as AI adoption grows.
AI Assisted Coding
AMD Instinct™ Coder 355
AMD Instinct™ Coder solutions boost developer productivity with turnkey, on-premises AI-assisted coding - simplifying deployment, helping control costs, and keeping sensitive code local - with on-premises inference by default and frontier models when justified and permitted by policy.
Up to
75%
Token savings vs Frontier only with payback in ~5 months¹
Solutions
A next-generation turnkey AI coding solution powered by Spectro Cloud, with high-performance AMD compute and a choice of Dell PowerEdge or Supermicro servers. Built for demanding coding workloads with support for up to 85 developers per node.
Frequently Asked Questions
A turnkey enterprise AI solution combines pre-integrated hardware, software, and AI models in a validated configuration. It reduces the work required to build and deploy AI infrastructure and helps simplify ongoing operations.
Turnkey solutions help accelerate deployment, reduce integration complexity, and simplify support. Customers can focus on business outcomes while working with a solution designed and validated for specific AI workloads.
AMD technology-powered solutions combine AMD EPYC™ processors, AMD Instinct™ GPUs, and an open software ecosystem with partner expertise. Customers gain high-performance AI infrastructure with flexibility in models, software, and deployment options.
Building your own stack offers extensive customization but requires selecting, integrating, validating, and maintaining its components. Turnkey solutions provide a fully integrated solution, reducing engineering effort and deployment complexity.
On-premises AI can reduce reliance on usage-based cloud services and give organizations greater visibility into infrastructure spending. Actual costs and savings depend on utilization, model selection, hardware, software, and operational requirements.
On-premises solutions allow organizations to process supported workloads within their own infrastructure. Data handling, external model access, and retention depend on the solution’s configuration and the organization’s policies.
Start with your use case, model requirements, expected usage, response-time goals, and data policies. AMD and its partners can help evaluate configurations based on workload performance, infrastructure requirements, support, and total cost.
Contact us
Get Started
Talk to your AMD representative to learn how AMD Enterprise AI Turnkey Solutions can help your organization accelerate AI deployments.
Footnotes
- TKS-001 - Based on AMD analysis of a modeled deployment using one server configured with 8 AMD Instinct™ MI355X GPUs. Assumptions include 85 developers spending $2,000 per month each on AI coding/API services ($2.04 million annually); Server list price of $590,000 including software and licensing with a three-year hardware amortization; continued frontier cloud API costs equal to 10% of baseline AI coding/API spend ($204,000 annually); and $50,000 in annual data center operating costs. Under these assumptions, modeled annual costs are approximately $513,500, representing approximately 75% of annual cost savings. The estimated five-month payback period is based on the modeled initial investment, relative to modeled monthly savings. Results are illustrative only. Actual costs, savings, and payback will vary based on workload, utilization, pricing, routing, infrastructure costs, and other factors.
Footnotes
- TKS-001 - Based on AMD analysis of a modeled deployment using one server configured with 8 AMD Instinct™ MI355X GPUs. Assumptions include 85 developers spending $2,000 per month each on AI coding/API services ($2.04 million annually); Server list price of $590,000 including software and licensing with a three-year hardware amortization; continued frontier cloud API costs equal to 10% of baseline AI coding/API spend ($204,000 annually); and $50,000 in annual data center operating costs. Under these assumptions, modeled annual costs are approximately $513,500, representing approximately 75% of annual cost savings. The estimated five-month payback period is based on the modeled initial investment, relative to modeled monthly savings. Results are illustrative only. Actual costs, savings, and payback will vary based on workload, utilization, pricing, routing, infrastructure costs, and other factors.