The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Devin CLI supports several model families, but that does not mean it runs every model locally. Its terminal agent works with local files and shell tools while model inference may still be hosted. If your goal is to replace paid cloud inference with a local LLM, you need a separate local runtime and suitable hardware; Devin’s model list alone does not establish that switch.
Which AI models does Devin CLI support?
As of October 7, 2026, Devin’s product page lists Anthropic Claude, OpenAI GPT, Google Gemini, Cognition models, and open-weight families including Kimi, GLM, and DeepSeek. That is a selection of named families, not evidence that Devin works with every AI model. The list can change; consult the current Devin CLI model listing for availability. The page displays version v2026.9.2 and says the CLI supports macOS, Linux, and Windows.
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Devin says you can switch models in a session with the /model command. Its Fusion mode is described as using a frontier lead model for decisions and important edits, with a lower-cost sidekick for exploration, file reads, and test runs. Those are vendor descriptions, not independent performance findings.
Does Devin CLI mean inference happens on your computer?
No. “Local” describes where the CLI runs and what it can access: your terminal, local repository, shell, and credentials. It does not, on its own, tell you where the language model is running. Devin’s documentation treats the CLI and Devin Cloud as distinct workflows; Cloud runs in a VM and offers features the CLI does not currently include. The docs say CLI does not yet support account Knowledge, Playbooks, or Secrets. Check the Devin CLI documentation for current feature availability.
#1 Best Overall
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
Devin’s model catalog includes hosted-provider families as well as open-weight models. The cited product material does not establish a built-in local-inference path for every listed model. Choosing an open-weight model is not enough to prove that inference is occurring on-device; verify the runtime and endpoint handling the request.
What a true local-LLM setup requires
For local inference, use a runtime that explicitly loads and runs models on your machine. Ollama distinguishes its local models from hosted cloud models, and notes that speed depends on hardware; large models can be slow without a strong GPU. Ollama’s download page describes those modes.
Rank #2
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- 𝗔𝗔𝗔 𝗚𝗮𝗺𝗶𝗻𝗴 𝗨𝗻𝗹𝗲𝗮𝘀𝗵𝗲𝗱—𝗨𝗽 𝘁𝗼 𝟭𝟯𝟬 𝗙𝗣𝗦 𝘄𝗶𝘁𝗵 𝗜𝗰𝗲𝗕𝗹𝗮𝘀𝘁 𝟯.𝟬 – Powered by AMD Ryzen AI 9 HX 470 (12C/24T, up to 5.2GHz), Radeon 890M Graphics, the GEEKOM A9MAX is built for smooth 1080p AAA gaming, streaming and 4K creation. Radeon 890M platforms have demonstrated up to 90 FPS in Cyberpunk 2077, 99 FPS in Forza Horizon 5 and 130 FPS in F1 24 with optimized settings and supported upscaling or frame generation. The all-metal chassis and IceBlast 3.0 cooling system combine a large copper heatsink, dual heat pipes and a quiet fan, with Standard and Performance modes to help maintain stable performance during long gaming, editing and rendering sessions.
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LM Studio provides another local-model runtime. Its system guidance recommends Apple Silicon M1, M2, M3, or M4 with macOS 14.0 or later and 16GB or more of RAM; it says 8GB Macs may work with smaller models and modest context. For Windows x64 or ARM, it recommends at least 16GB RAM and 4GB dedicated VRAM. These are recommendations, not guarantees of a particular model’s speed or coding quality. See LM Studio’s system requirements.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsBefore buying hardware, check the memory needs of the specific model and the context size you expect to use. An Apple Silicon Mac with 16GB RAM is a hardware category matching LM Studio’s recommendation, not a guarantee that any particular coding model will run quickly or well.
Rank #3
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
What changes when you replace cloud inference?
A local setup changes more than the provider on a settings screen. Compare the whole workflow against what you actually use:
- Cost: Cloud usage or subscription charges may be replaced by hardware acquisition and electricity costs. The result depends on your usage volume, model, and existing computer; the available figures do not establish an individual user’s savings.
- Performance: Local speed and coding quality depend on the model, hardware, and context. A model that loads successfully may still be slow or unsuitable for a task.
- Data handling: Local inference can reduce the need to send prompts to a hosted model, but verify that the runtime is actually using a local model and review any other services or tools in the workflow.
- Setup and upkeep: You take responsibility for obtaining models, configuring the runtime, managing updates, and troubleshooting hardware limits.
- Agent features: Model inference is only one part of an agent workflow. Devin CLI’s local terminal access and Devin Cloud’s VM-based workflow are distinct, and the documentation identifies Knowledge, Playbooks, and Secrets as Cloud features not yet supported in CLI.
What Devin’s cost comparison does—and does not—show
Devin’s product page reports that, on Artificial Analysis Coding Agent Index 1.5, Devin Fusion with Fable 5.1 cost $7.90 per run versus $12.36 for Claude Code with Fable 5.1; it reports $4.54 for Devin Fusion with Astra 6 versus $7.47 for Codex with Astra 6. These are vendor-presented benchmark figures for the named index and runs. They are not local-runtime costs, a monthly bill estimate, or proof that a reader would save those amounts.
Rank #4
- Built for Local AI and Advanced Workflows – The BOSGAME M5 AI Mini PC is powered by AMD Ryzen AI Max+ 395 with 16 cores, 32 threads, up to 5.1GHz, 50 TOPS NPU performance and up to 126 TOPS total AI performance. It is designed for local AI inference, private AI assistants, coding, data analysis, virtualization, content creation and demanding multitasking while keeping sensitive data on the device.
- 128GB Unified Memory for Large Models and Creative Projects – M5 includes 128GB LPDDR5X-8000 unified memory, giving the CPU and Radeon 8060S graphics access to a large shared memory pool. This helps support memory-intensive AI workloads, large project files, multiple virtual machines, 3D work, video editing and complex professional applications without the capacity limits of typical 32GB or 64GB mini computers.
- Radeon 8060S Graphics for Creation, Rendering and Gaming – Integrated Radeon 8060S graphics with 40 RDNA 3.5 compute units delivers high-end visual performance without a separate graphics card. Use the M5 creator workstation for 4K video editing, 3D rendering, CAD, AI image workflows, high-resolution media and modern gaming, while maintaining a compact desktop footprint.
- 2TB PCIe 4.0 SSD and Flexible Expansion – A pre-installed 2TB NVMe PCIe 4.0 SSD provides fast access to models, datasets, media libraries and project files. A second M.2 2280 PCIe 4.0 slot allows additional storage expansion, while the SD 4.0 card reader supports efficient photo and video workflows for creators and production teams.
- Professional Connectivity and Four-Display Support – Dual USB4 ports, HDMI 2.1 and DisplayPort 1.4 support up to four displays and resolutions up to 8K@60Hz. WiFi 7, Bluetooth 5.4 and 2.5GbE deliver fast networking for cloud collaboration, NAS access and business deployment. Windows 11 Pro, performance-mode switching, Wake-on-LAN and auto power-on support flexible workstation use.
Is an open-source agent another route?
OpenDevin is a separate project, not the Devin product by Cognition. Its README describes configurable LLM backends, including a local Ollama path, but labels the project alpha and warns that it may be unstable, can issue many prompts, and that most configured LLMs cost money. It is an option for readers willing to configure and maintain an experimental agent, not a drop-in equivalent established by the available documentation.
Quick Recap
Best Value
- 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
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How to decide whether to switch
- Identify what you are replacing. Record the provider, billing basis, and actual usage you want to displace. Without that baseline, “expensive” cannot be translated into a savings claim.
- Choose a specific model and runtime. Confirm that the runtime runs the model locally rather than routing it to a hosted service.
- Check your machine against runtime guidance. Treat published memory and platform recommendations as starting points, then account for the model and context you intend to use.
- Try representative coding tasks. Compare correctness, latency, and how often you need to intervene, using the same tasks and context you use in your normal workflow.
- Calculate total cost for your usage. Include model charges avoided, hardware you would need to buy, and electricity. Existing hardware and frequent usage can change the calculation, but no universal break-even point is established here.
- Check workflow requirements. Confirm whether you need Devin Cloud features such as Knowledge, Playbooks, or Secrets, or whether local terminal and repository access is sufficient.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
