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First, identify which backend layer you need to host
“AI-agent backend” can refer to several components, and they do not have to run on the same provider or server. OpenAI’s Agents API architecture describes three distinct parts:
- Agent harness: the component that manages the agent’s steps and progress. With a managed API, the provider can operate this layer; with an SDK, your application runs the agent loop.
- Execution environment: where commands, code, and files run. This might be a hosted sandbox or an environment your team operates.
- Application server: the service that accepts work from your users, submits tasks, receives events, and handles application functions or tools.
Before choosing a plan, list which of these you actually need to operate. An application that calls an agent API and handles ordinary function tools may need an application server but no separate code sandbox. A task that executes scripts or creates files may need an execution environment as well.
Choose the runtime before choosing a server size
Runtime options determine who operates the agent loop and where the work happens; they are not simply different sizes of hosting plan. OpenAI’s runtime guide distinguishes these approaches:
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- EVOLUTION CORE ULTRA 9 285H MINI PC - GMKtec EVO-T1 is the next evolution in AI mini PC Ultra 9 series. The Core Ultra 9 285H offers 16 cores (six P-cores + eight E-cores + two LPE-cores) and 16 threads with a turbo clock of 5.4 GHz. It is currently one of the best value for performance AI mini PC computers.
- AI NPU - The 285H features an Intel AI Boost NPU, capable of up to 13 TOPS (Tera Operations per Second) for INT8 calculations, which is designed to accelerate AI tasks.
- INTEL ARC 140T GAMING PC - The Arc 140T GPU includes 8 Xe cores and supports features like DirectX 12, OpenGL 4.5, and OpenCL 3, making it capable of handling modern games and creative applications. It also supports Quick Sync Video for efficient video encoding and decoding, as well as AV1 encoding and decoding.
- 64GB DDR5 RAM + 1TB SSD - The EVO-T1 is equipped with Dual 32GB (Total 64GB) SO-DIMM DDR5 5600MHz memory sticks. 2TB PCIE 4.0 SSD Drive with 3x M.2 2280 Expansion slots. Each slot capable of reading up to 4TB. (12TB MAX)
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-T1 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and USB Type-C Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
- Agents API: a managed, long-running harness with saved progress. Your application still needs to connect to it and manage its own user-facing responsibilities.
- Agents SDK: the application runs the agent loop and has more control over deployment and storage.
- Responses API: direct model calls, or a custom loop built by the application.
These options differ in operational responsibility and control. They do not by themselves tell you how much CPU, memory, or storage your workload needs.
Managed service or self-hosted runtime?
A managed service can take recurring infrastructure tasks off your team’s plate, but its supported configuration, networking, persistence, and lifecycle need to fit the application. Self-hosting offers more control at the cost of operating the runtime and its surrounding systems.
Rank #2
- LOW ENERGY HIGH PERFORMANCE MINI PC - The Intel Core Ultra 5 125U is part of the Ultra 5 lineup, using the Meteor Lake architecture with BGA 2049. Intel Hyper-Threading technology is available and effectly doubles the core-count of the P-Cores, to a total of 14 threads. Core Ultra 5 125U has 12 MB of L3 cache and operates at 1300 MHz by default, but can boost up to 4.3 GHz, depending on the workload. With a TDP of 15 W, the Core Ultra 5 125U consumes very little energy but outputs high performance efficiency
- 32GB DDR5 RAM + 512GB SSD - The K15 mini computer is equipped with Dual 16GB (Total 32GB) SO-DIMM DDR5 4800MHz memory sticks. 512GB PCIE 4.0 SSD Drive with 3x M.2 2280 Expansion slots. Each slot capable of reading up to 8TB. (24TB MAX)
- QUAD SCREEN 4K DISPLAY SUPPORT - K15 Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and USB Type-C Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support
- OCULINK PORT - The Oculink port on the rear interface enables higher bandwidth capabilities, better frame rates and lower lag. The standard also operates at PCIe x4 speeds, compared to Thunderbolt's x3. Gamers and content creators can benefit from Oculink's higher bandwidth, resulting in better performance and lower lag for eGPU setups
- DUAL NIC FAST 2.5GBE + WIFI 6E + BT 5.2 - Dual Ethernet 2.5GbE LAN port design provides more applications, such as firewall, multichannel aggregation, soft routing, file storage server. Built-in WIFI 6E / Bluetooth 5.2 is more stable and efficient to connect multiple wireless devices such as projector, printer, monitor, speakers and etc
| Decision area | Managed service or hosted sandbox | Self-hosted runtime |
|---|---|---|
| Containers and lifecycle | The provider may provision, scale, and manage session lifecycle, depending on the service. | Your team starts and manages the environment and its lifecycle. |
| Control and network access | You use the provider’s supported configuration and network model. | A better fit when private networking, custom software, or infrastructure control is required. |
| Persistence and recovery | Check the exact service’s session persistence, expiry, artifact handling, and durable-workflow support. | Your team chooses and operates persistence, reconnection, recovery, and file retention. |
| Costs to include | Model, tool, and container usage can be separate charges; check the current rates and billing model. | Compute, storage, network, monitoring, reliability work, and staff time, in addition to model usage where applicable. |
| Best fit | Workloads that fit the provider’s execution and integration features, with less infrastructure work for your team. | Workloads whose bespoke environment or need for control warrants the added operating burden. |
For example, OpenAI’s hosted sandbox documentation describes a Linux workspace that the application supplies tasks to and retrieves results from; model usage is billed separately from standard container rates. With a self-hosted environment, the application connects an executor and manages startup, reconnection, shutdown, and preservation of needed files.
Microsoft describes a similar division in its Agent Framework hosting guide: managed Foundry Hosted Agents operate containers, scaling, session lifecycle, and platform integration, while a self-hosted application operates routes, identity, request policy, storage, deployment, and scaling. That guide describes Hosted Agents as generally available and its current Python self-hosting packages as prerelease; check the current lifecycle status before relying on either for a production deployment.
Rank #3
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- Set Your Devices Free, Expand Your Digital World: This unified storage hub supports massive capacity up to 64TB.*Storage drives not included. Stop Deleting, Start Storing. You can store 22 million 3MB images, or 2 million 30MB songs, or 43K 1.5GB movies or 67 million 1MB documents! UGREEN NAS is a better way to free up storage across all your devices such as phones, computers, tablets and also does automatic backups across devices regardless of the operating system—Window, iOS, Android or macOS.
- The Smarter Long-term Way to Store: Unlike cloud storage with recurring monthly fees, a UGREEN NAS enclosure requires only a one-time purchase for long-term use. For example, you only need to pay $459.98 for a NAS, while for cloud storage, you need to pay $719.88 per year, $2,159.64 for 3 years, $3,599.40 for 5 years. You will save $6,738.82 over 10 years with UGREEN NAS! *NAS cost based on DH2300 + 12TB HDD; cloud cost based on 12TB plan (e.g. $59.99/month).
- Blazing Speed, Minimal Power: Equipped with a high-performance processor, 1GbE port, and 4GB RAM on Board, this NAS handles multiple tasks with ease. File transfers reach up to 125MB/s—a 1GB file takes only 8 seconds. Don't let slow clouds hold you back; they often need over 100 seconds for the same task. The difference is clear.
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Use this decision sequence
- Map the work. Decide whether you need an application API, an agent loop, code or file execution, background workers, or several of them. Avoid renting execution capacity for a sandbox you do not need.
- Try the managed route against real requirements. Start with the managed option if its tools, execution environment, network model, and persistence meet the application’s needs. Add hosted execution when tasks genuinely require scripts, files, or artifacts.
- Self-host for an explicit control requirement. Private infrastructure or networking, custom software, and infrastructure control are concrete reasons to consider it. Include the work of managing startup, reconnection, shutdown, and retained files in the decision.
- Plan for tasks that outlast a web request. Establish maximum run duration and how progress must survive interruption. If tasks need queueing, retries, human approval, replay, or recovery, choose a workflow and state strategy rather than relying on a process simply staying alive. The Agents SDK documents integrations with Restate for durable workflows and DBOS for progress preserved across failures and restarts; validate their fit for your workload.
- Estimate the complete workload. Measure representative tasks for concurrency, memory, runtime, storage, and network use. Keep model charges separate from compute or container charges when they are billed separately. Do not select a fixed tier based only on the word “agent.”
- Review data and access boundaries. Keep provider API keys outside an execution sandbox and use the provider’s documented secret mechanism. For the exact service and workload, check region, retention, isolation, and contractual terms; general product documentation does not replace that deployment review.
Does an AI-agent backend need a GPU?
Not by default. If the agent calls a hosted model API and its environment mainly handles orchestration, ordinary application code, or tool calls, choose compute based on the measured work those components perform. A GPU is a conditional requirement when you run local inference or a task with substantial GPU-compute needs—not a blanket requirement for every agent backend. Test representative work before committing to a plan.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to budget hosting without a universal monthly price
There is no single monthly price or server size that fits every agent backend. On the documented Agents API route, model, tool, and hosted-container usage are distinct components to account for. A self-hosted deployment also has compute, persistence, networking, monitoring, security, reliability, and staff-time costs. Compare the full workload and current service rates, rather than treating the server bill as the whole cost.
Quick Recap
Rank #4
- [Powerful PC] Gaming PC equipped with Core i9-14900F, 24 Cores 32 Threads, 36M Cache, Max Turbo Frequency: 5.8GHz, Windows 11 pro (64 Bit). With GeForce RTX 50 Series GPUs. Adopting DLSS 4 technology, it dramatically improves frame rate performance, supports FP4 low-precision computing, and doubles the efficiency of AI inference. SD graph generation speed is 3 times faster than RTX 4070 Super, significantly increasing creative productivity. Graphics work productivity has increased significantly.
- [High Speed DDR5 RAM & PCIE4.0 SSD] The desktop computer is equipped with Dual-DDR5 RAM (dual channel DDR5 high-speed memory, which can support up to 128GB RAM), 1 x M.2 2280 PCIE4.0 high-speed SSD, and support add 2 x 2.5-inch SATA HDD/SSD(not include) is enough to accommodate system files and massive games, Excellent reading and writing speed greatly shortening your boot time.
- [8K@60Hz Quad-Display] Desktop PC with GeForce RTX 5070 12G GDDR7, supporting DLSS 4, ray tracing, and AI cores. Easily connect 4 monitors via 1×HDMI 2.1 + 3×DP 1.4a — all ports support 8K@60Hz. Delivers stunning visuals and ultra-smooth performance for home entertainment, live streaming, video editing, AI workloads, 3D rendering, and AAA gaming.
- [Functional Interfaces] Mini computer is equipped with 4 x USB 3.2, 4 x USB2.0, 1 x HDMI2.1 port, 3 x DP ports, 2xRJ-45 Gigabit Network Ethernet, 1 x Fiber Optic PORT, 1 x Audio in/out. Built-in Bluetooth 5.4 and IEEE 802.11be wifi 7, Higher transfer rates and lower latency. Mini PC supports multiple device connection and can be used with servers, monitoring equipment, office equipment, projectors, televisions, etc, Mini desktop computer support automatic power on and Wake On Lan.
- [Warranty & Liquid Cooling] Warrant: 2 year/24 months. The compact computer size: 11.6*9.3*3.9in, 9.25lb, Chassis built-in 2 large copper fans, built-in liquid cooling device, to further enhance the computer heat dissipation, and at the same time can reduce noise, give full play to the overall performance of the computer.
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