[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-kimi-k2-5-local-setup-ollama-docker-en":3,"article-related-kimi-k2-5-local-setup-ollama-docker-en":30,"series-ai-agent-a72fc4a2-7e7d-4f06-b34a-857d65ad30e2":73},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":16,"key_takeaways":22,"views":26,"created_at":27,"published_at":28,"topic_cluster_id":29},"a72fc4a2-7e7d-4f06-b34a-857d65ad30e2","kimi-k2-5-local-setup-ollama-docker-en","Kimi-K2.5 Local Setup with Ollama and Docker","\u003Cp data-speakable=\"summary\">Set up Kimi-K2.5 locally with \u003Ca href=\"\u002Ftag\u002Fdocker\">Docker\u003C\u002Fa> and Ollama for offline model runs.\u003C\u002Fp>\u003Cp>This guide is for developers who want a fast local Kimi-K2.5 build without cloud setup. After following the steps, you will have a Docker-based Ollama stack running the model, plus a simple way to verify the service is live and ready for prompts.\u003C\u002Fp>\u003Ch2>Before you start\u003C\u002Fh2>\u003Cul>\u003Cli>Docker Desktop 4.30+ or Docker Engine 24+ with Docker Compose v2\u003C\u002Fli>\u003Cli>Ollama installed locally, or an Ollama container image you can pull\u003C\u002Fli>\u003Cli>Node.js 20+ only if you plan to test the API from a script\u003C\u002Fli>\u003Cli>At least 16 GB RAM for stable local loading, with more recommended for larger quantized builds\u003C\u002Fli>\u003Cli>50 GB free disk space for model files, cache, and future updates\u003C\u002Fli>\u003Cli>A GitHub account if you want to clone and version your compose files\u003C\u002Fli>\u003Cli>Access to the Ollama docs and image repo: \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Follama\u002Follama\">Ollama GitHub\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Follama.com\u002Fdocs\">Ollama docs\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>Step 1: Create the project folder\u003C\u002Fh2>\u003Cp>Your first goal is to create a clean workspace for the Kimi-K2.5 Docker build so the compose file, model assets, and logs stay organized.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782828171334-ysrs.png\" alt=\"Kimi-K2.5 Local Setup with Ollama and Docker\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>mkdir kimi-k2-5-local\ncd kimi-k2-5-local\nmkdir models data logs\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>Verification: you should see the new folders when you run \u003Ccode>ls\u003C\u002Fcode> or \u003Ccode>dir\u003C\u002Fcode>, and the terminal should remain inside the project directory.\u003C\u002Fp>\u003Ch2>Step 2: Add the Docker Compose file\u003C\u002Fh2>\u003Cp>Next, define a repeatable container setup that starts Ollama and exposes the local \u003Ca href=\"\u002Ftag\u002Fapi\">API\u003C\u002Fa> on your machine.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782828177807-9jza.png\" alt=\"Kimi-K2.5 Local Setup with Ollama and Docker\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>services:\n  ollama:\n    image: ollama\u002Follama:latest\n    container_name: kimi-k2-5-ollama\n    ports:\n      - \"11434:11434\"\n    volumes:\n      - .\u002Fmodels:\u002Froot\u002F.ollama\n    restart: unless-stopped\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>Verification: you should have a \u003Ccode>docker-compose.yml\u003C\u002Fcode> file in the project root, and the service name should be easy to identify in Docker.\u003C\u002Fp>\u003Ch2>Step 3: Start the Ollama container\u003C\u002Fh2>\u003Cp>Now launch the container so the local Ollama runtime is available before you pull or run the model.\u003C\u002Fp>\u003Cpre>\u003Ccode>docker compose up -d\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>Verification: you should see the container start without errors, and \u003Ccode>docker ps\u003C\u002Fcode> should list \u003Ccode>kimi-k2-5-ollama\u003C\u002Fcode> as running.\u003C\u002Fp>\u003Ch2>Step 4: Pull the Kimi-K2.5 model\u003C\u002Fh2>\u003Cp>With the runtime active, fetch the model tag you intend to use so the local machine has the model weights ready for \u003Ca href=\"\u002Ftag\u002Finference\">inference\u003C\u002Fa>.\u003C\u002Fp>\u003Cpre>\u003Ccode>docker exec -it kimi-k2-5-ollama ollama pull kimi-k2.5\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>Verification: you should see a completed download with no failed layer messages, and the model should appear in the Ollama model list.\u003C\u002Fp>\u003Ch2>Step 5: Run a local prompt test\u003C\u002Fh2>\u003Cp>Finish by sending a simple prompt to confirm the model answers correctly through the local Ollama endpoint.\u003C\u002Fp>\u003Cpre>\u003Ccode>docker exec -it kimi-k2-5-ollama ollama run kimi-k2.5 \"Write one sentence about local AI development.\"\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>Verification: you should see a text response in the terminal, which confirms the model is serving requests from your own machine.\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>Metric\u003C\u002Fth>\u003Cth>Before\u002FBaseline\u003C\u002Fth>\u003Cth>After\u002FResult\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>Setup path\u003C\u002Ftd>\u003Ctd>Manual local install steps\u003C\u002Ftd>\u003Ctd>Docker Compose launch\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>RAM guidance\u003C\u002Ftd>\u003Ctd>No explicit target\u003C\u002Ftd>\u003Ctd>16 GB minimum for stable 8B loading\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Storage planning\u003C\u002Ftd>\u003Ctd>Ad hoc disk usage\u003C\u002Ftd>\u003Ctd>50 GB free space recommended\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>Common mistakes\u003C\u002Fh2>\u003Cul>\u003Cli>Using too little memory: if the container exits or swaps heavily, add RAM or use a smaller quantized model tag.\u003C\u002Fli>\u003Cli>Forgetting port 11434: if the API is unreachable, confirm the port mapping is exposed in the compose file and not blocked by another service.\u003C\u002Fli>\u003Cli>Pulling the wrong model name: if Ollama says the model is missing, recheck the tag spelling and pull the exact name shown in the repo or docs.\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>What’s next\u003C\u002Fh2>\u003Cp>After the local build works, add a client app, \u003Ca href=\"\u002Ftag\u002Fbenchmark\">benchmark\u003C\u002Fa> prompt latency, or place the stack behind a reverse proxy so you can share the model safely on a LAN.\u003C\u002Fp>","Set up Kimi-K2.5 locally with Docker and Ollama for offline model runs.","okanmorkoc.com","https:\u002F\u002Fokanmorkoc.com\u002Fhow-to-setup-kimi-k2-5-locally-via-ollama-2-easy-build\u002F",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782828171334-ysrs.png","ai-agent","en","be07f530-b13a-4c07-ada2-f93f112970e3",[17,18,19,20,21],"Kimi-K2.5","Ollama","Docker Compose","local LLM","model serving",[23,24,25],"Docker Compose gives you the fastest repeatable local Kimi-K2.5 setup.","A 16 GB RAM baseline helps avoid unstable model loading on smaller machines.","Verifying the Ollama container and running a test prompt confirms the model is live.",0,"2026-06-30T14:02:23.039595+00:00","2026-06-30T14:02:23.026+00:00","a9bee732-b07c-4e5b-a0e6-3048577e32a7",{"tags":31,"relatedLang":32,"relatedPosts":36},[],{"id":15,"slug":33,"title":34,"language":35},"kimi-k2-5-local-setup-ollama-docker-zh","Kimi-K2.5 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wikis beat raw RAG for real knowledge work","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782760670241-gdea.png","2026-06-29T19:17:21.2178+00:00",{"id":56,"slug":57,"title":58,"cover_image":59,"image_url":59,"created_at":60,"category":13},"6c32d3c9-f5b9-4f47-8786-b6e8efd2660a","mcps-new-primitives-make-agent-middleware-obsolete-en","MCP’s new primitives make agent middleware obsolete","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782748973197-wvm6.png","2026-06-29T16:02:25.212097+00:00",{"id":62,"slug":63,"title":64,"cover_image":65,"image_url":65,"created_at":66,"category":13},"8c46d754-431a-4c64-a11d-d1978ee1d948","mcp-servers-ai-workflows-explained-en","MCP servers turn AI tools into connected workflows","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782747182218-n3ml.png","2026-06-29T15:32:33.962535+00:00",{"id":68,"slug":69,"title":70,"cover_image":71,"image_url":71,"created_at":72,"category":13},"d6956b2a-b5fb-44f5-b316-9b6dddb3ca47","openmontage-open-source-ai-video-production-en","OpenMontage proves open-source should own AI video production","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782685070172-081n.png","2026-06-28T22:17:23.291322+00:00",[74,79,84,89,94,99,104,109,114,119],{"id":75,"slug":76,"title":77,"created_at":78},"03db8de8-8dc2-4ac1-9cf7-898782efbb1f","anthropic-claude-ai-agent-task-automation-en","Anthropic's Claude AI Agent: A New Era of Task Automation","2026-03-25T16:25:06.513026+00:00",{"id":80,"slug":81,"title":82,"created_at":83},"045d1abc-190d-4594-8c95-91e2a26f0c5a","googles-2026-ai-agent-report-decoded-en","Google’s 2026 AI Agent Report, Decoded","2026-03-26T11:15:23.046616+00:00",{"id":85,"slug":86,"title":87,"created_at":88},"e64aba21-254b-4f93-aa21-837484bb52ec","kimi-k25-review-stronger-still-not-legend-en","Kimi K2.5 review: stronger, still not a legend","2026-03-27T07:15:55.385951+00:00",{"id":90,"slug":91,"title":92,"created_at":93},"30dfb781-a1b2-4add-aebe-b3df40247c37","claude-code-controls-mac-desktop-en","Claude Code now controls your Mac desktop","2026-03-28T03:01:59.384091+00:00",{"id":95,"slug":96,"title":97,"created_at":98},"254405b6-7833-4800-8e13-f5196deefbe6","cloudflare-100x-faster-ai-agent-sandbox-en","Cloudflare’s 100x Faster AI Agent 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