{"content_id":"36pbdomwc3","slug":"nvidia-dynamo-korean-open-model-deployment-recipes","locale":"en","schema_type":"NewsArticle","category":"news","category_name":"News","title":"NVIDIA Dynamo Deployment Recipes Released for Developers","summary":"NVIDIA said it will release Dynamo-optimized deployment recipes for 4 Korean open models. GPU, storage, and runtime image requirements vary by model, and neither the comparison conditions for the claim of up to 2x performance nor operating costs have been confirmed.","sponsorship_disclosure":null,"affiliate_disclosure":null,"commerce_disclosure":null,"author":{"name":"Injoys Editorial Team","url":"https://injoys.com/ko/about"},"key_points":["NVIDIA said it will release deployment recipes for A.X K2, K-EXAONE 2.0, Solar Open 2, and Motif-3.","The B200 configuration for A.X-K2 requires 8 GPUs for integrated deployment and 12 GPUs for disaggregated deployment.","K-EXAONE 2.0 requires a ReadWriteMany storage class with at least 700 GB of free space.","Solar Open2 requires the dedicated image pinned in the recipe rather than the default Dynamo 1.4.1 vLLM runtime.","The claim of up to 2x performance comes from NVIDIA; comparison conditions and independent verification results have not been confirmed."],"content_markdown":"NVIDIA announced that it is releasing Dynamo deployment recipes for Korean open models. The official page is dated November 8, 2026. The feed timestamp is November 9 at 14:00 Korean time. Developers can use the model-specific configurations for their own deployments.\n\nThis article follows NVIDIA's announcement and excerpts from official documentation and is current as of November 9, 2026.\n\n## Deployment Recipes for 4 Korean Open Models\n\nNVIDIA's announcement covers 4 open models developed by Korean companies. The recipes provide configurations for deploying each model with Dynamo. NVIDIA said it optimized these recipes for B200 GPUs.\n\n| Model | Developer | Configuration Confirmed in Official Documentation |\n|---|---|---|\n| A.X K2 | SK Telecom | Serving on B200 and H200 with Dynamo and vLLM |\n| K-EXAONE 2.0 | LG AI Research | Serving the 750B-A37B model in NVFP4 format on B200 |\n| Solar Open 2 | Upstage | Serving with a dedicated image pinned in the recipe |\n| Motif-3 | Motif Technologies | An aggregated worker or a disaggregated configuration with KV-aware routing |\n\nNVIDIA Dynamo is an open-source distributed inference serving framework. Inference serving means running a model so it can receive requests and return results. NVIDIA describes it as a tool for data-center-scale, multi-node deployments.\n\n## Model-Specific Requirements for Self-Deployment\n\nDevelopers who plan to run a model themselves should check the resource requirements of their chosen recipe. The A.X-K2 documentation covers B200 and H200 configurations. The A.X-K2 GPU and memory figures below are requirements for the B200 configuration.\n\n| Model | Configuration and Resource Requirements | Scope |\n|---|---|---|\n| A.X-K2 | 4 B200 GPUs and 400 GiB of host memory per worker | 8 GPUs total for aggregated deployment, 12 for disaggregated deployment |\n| K-EXAONE 2.0 | A ReadWriteMany storage class with at least 700 GB of free space | Checkpoint disk usage is approximately 530 GB |\n| Solar Open2 | 4 GPUs for 1 prefill worker, 4 GPUs total for 2 decode workers | 8 GPUs total for the disaggregated configuration |\n| Motif-3 | 1 aggregated worker or a 3P1D configuration with 3 prefill workers and 1 decode worker | Each worker uses 2 GPUs |\n\nSolar Open2's prefill configuration uses TP4 and expert parallelism. Each decode worker uses TP2. Motif-3 workers use TP2 and expert parallelism. Motif-3's MTP2 setting uses 2 speculative tokens.\n\nThese documents describe configurations for self-deployment. Usage conditions for Korea have not been confirmed. Whether hosting services are available in Korea is also not specified.\n\n## Recipe Fees and GPU Operating Costs\n\nNVIDIA's announcement and the documentation excerpts do not list recipe fees. GPU acquisition costs and cloud operating costs are also not provided. Dynamo being open source does not mean that operating it is free.\n\n- Recipe fees: Not specified.\n- GPU and cloud operating costs: Not specified.\n- Managed API availability: Not specified.\n- Managed API request fees and limits: Not specified.\n\n## Up to 2x Performance and Requests Excluded from Evaluation\n\nNVIDIA said the B200-optimized recipes deliver **up to 2x** performance with the default configuration. This is a performance claim made by the company. The official excerpts reviewed do not include the comparison baseline or measurement conditions. No independent verification results were provided.\n\n| Item | What the Official Source States | Remaining Caveats |\n|---|---|---|\n| Recipe performance | NVIDIA's announcement claims up to 2x performance | Comparison baseline and measurement conditions unconfirmed |\n| K-EXAONE 2.0 evaluation requests | 1,805 requests in NVIDIA's official evaluation documentation | 38 of these requests were excluded from the metrics |\n| Reason for exclusion | HTTP 400 returned because requests exceeded the 262,144-token context limit | These failed requests are not reflected in the performance metrics |\n\nThe K-EXAONE 2.0 figures come from NVIDIA's official evaluation documentation. There is no basis for treating them as independent measurements. When citing the evaluation metrics, the request exclusion conditions should also be disclosed. The relationship between this evaluation and the up to 2x claim is also unconfirmed.\n\n## Exact Release Time and Service Scope Remain Unconfirmed\n\nThe difference between the official page date and the feed timestamp has not been explained. The official page displays November 8, 2026. The feed timestamp is November 9, 2026, at 05:00 UTC. Converted to Korean time, this is 14:00 on the same day.\n\nThis information alone cannot establish the exact release time. The time zone used for the official page date is also unconfirmed. The scope of managed services available in Korea has not been specified either.\n\n- The reason for the date difference and the exact release time are unconfirmed.\n- Usage conditions for Korea and the availability of hosting in Korea are unconfirmed.\n- Managed API availability and request conditions are unconfirmed.\n\n## What to Check Before Deploying in Korea\n\nFor self-deployment, first check the runtime environment in each model's official documentation. Solar Open2, in particular, requires the specified dedicated image. The default Dynamo 1.4.1 vLLM runtime does not include this model's definition.\n\n- A.X-K2 has different total GPU requirements for aggregated and disaggregated deployments. The B200 requirements should not be applied unchanged to the H200 configuration.\n- A.X-K2 can reuse a PVC that already stores the model. A PVC is a request that specifies storage for a deployment. Set `claimName` in both the download job and the selected deployment source to that PVC. In this case, creating a new PVC can be skipped.\n- For K-EXAONE 2.0, the checkpoint size and required free space differ. Securing only approximately 530 GB does not meet the documented requirements. A ReadWriteMany storage class needs at least 700 GB of free space.\n- Solar Open2 must use the image pinned in the recipe. It is not an optional component that can be replaced with the default runtime.\n- For Motif-3, choose either an aggregated or a 3P1D deployment configuration. Check each worker's GPU requirements as well.\n\nBefore paying for cloud resources, check the cost estimate for your chosen environment. NVIDIA's up to 2x claim cannot be used as a performance guarantee for your own environment. Usage conditions for Korea and managed API support require separate confirmation.","content_html":"\u003cp\u003eNVIDIA announced that it is releasing Dynamo deployment recipes for Korean open models. The official page is dated November 8, 2026. The feed timestamp is November 9 at 14:00 Korean time. Developers can use the model-specific configurations for their own deployments.\u003c/p\u003e\n\u003cp\u003eThis article follows NVIDIA's announcement and excerpts from official documentation and is current as of November 9, 2026.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#deployment-recipes-for-4-korean-open-models\" class=\"anchor\" id=\"deployment-recipes-for-4-korean-open-models\"\u003e\u003c/a\u003eDeployment Recipes for 4 Korean Open Models\u003c/h2\u003e\n\u003cp\u003eNVIDIA's announcement covers 4 open models developed by Korean companies. The recipes provide configurations for deploying each model with Dynamo. NVIDIA said it optimized these recipes for B200 GPUs.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eModel\u003c/th\u003e\n\u003cth\u003eDeveloper\u003c/th\u003e\n\u003cth\u003eConfiguration Confirmed in Official Documentation\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eA.X K2\u003c/td\u003e\n\u003ctd data-label=\"Developer\"\u003eSK Telecom\u003c/td\u003e\n\u003ctd data-label=\"Configuration Confirmed in Official Documentation\"\u003eServing on B200 and H200 with Dynamo and vLLM\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eK-EXAONE 2.0\u003c/td\u003e\n\u003ctd data-label=\"Developer\"\u003eLG AI Research\u003c/td\u003e\n\u003ctd data-label=\"Configuration Confirmed in Official Documentation\"\u003eServing the 750B-A37B model in NVFP4 format on B200\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eSolar Open 2\u003c/td\u003e\n\u003ctd data-label=\"Developer\"\u003eUpstage\u003c/td\u003e\n\u003ctd data-label=\"Configuration Confirmed in Official Documentation\"\u003eServing with a dedicated image pinned in the recipe\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eMotif-3\u003c/td\u003e\n\u003ctd data-label=\"Developer\"\u003eMotif Technologies\u003c/td\u003e\n\u003ctd data-label=\"Configuration Confirmed in Official Documentation\"\u003eAn aggregated worker or a disaggregated configuration with KV-aware routing\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eNVIDIA Dynamo is an open-source distributed inference serving framework. Inference serving means running a model so it can receive requests and return results. NVIDIA describes it as a tool for data-center-scale, multi-node deployments.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#model-specific-requirements-for-self-deployment\" class=\"anchor\" id=\"model-specific-requirements-for-self-deployment\"\u003e\u003c/a\u003eModel-Specific Requirements for Self-Deployment\u003c/h2\u003e\n\u003cp\u003eDevelopers who plan to run a model themselves should check the resource requirements of their chosen recipe. The A.X-K2 documentation covers B200 and H200 configurations. The A.X-K2 GPU and memory figures below are requirements for the B200 configuration.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eModel\u003c/th\u003e\n\u003cth\u003eConfiguration and Resource Requirements\u003c/th\u003e\n\u003cth\u003eScope\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eA.X-K2\u003c/td\u003e\n\u003ctd data-label=\"Configuration and Resource Requirements\"\u003e4 B200 GPUs and 400 GiB of host memory per worker\u003c/td\u003e\n\u003ctd data-label=\"Scope\"\u003e8 GPUs total for aggregated deployment, 12 for disaggregated deployment\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eK-EXAONE 2.0\u003c/td\u003e\n\u003ctd data-label=\"Configuration and Resource Requirements\"\u003eA ReadWriteMany storage class with at least 700 GB of free space\u003c/td\u003e\n\u003ctd data-label=\"Scope\"\u003eCheckpoint disk usage is approximately 530 GB\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eSolar Open2\u003c/td\u003e\n\u003ctd data-label=\"Configuration and Resource Requirements\"\u003e4 GPUs for 1 prefill worker, 4 GPUs total for 2 decode workers\u003c/td\u003e\n\u003ctd data-label=\"Scope\"\u003e8 GPUs total for the disaggregated configuration\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Model\"\u003eMotif-3\u003c/td\u003e\n\u003ctd data-label=\"Configuration and Resource Requirements\"\u003e1 aggregated worker or a 3P1D configuration with 3 prefill workers and 1 decode worker\u003c/td\u003e\n\u003ctd data-label=\"Scope\"\u003eEach worker uses 2 GPUs\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eSolar Open2's prefill configuration uses TP4 and expert parallelism. Each decode worker uses TP2. Motif-3 workers use TP2 and expert parallelism. Motif-3's MTP2 setting uses 2 speculative tokens.\u003c/p\u003e\n\u003cp\u003eThese documents describe configurations for self-deployment. Usage conditions for Korea have not been confirmed. Whether hosting services are available in Korea is also not specified.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#recipe-fees-and-gpu-operating-costs\" class=\"anchor\" id=\"recipe-fees-and-gpu-operating-costs\"\u003e\u003c/a\u003eRecipe Fees and GPU Operating Costs\u003c/h2\u003e\n\u003cp\u003eNVIDIA's announcement and the documentation excerpts do not list recipe fees. GPU acquisition costs and cloud operating costs are also not provided. Dynamo being open source does not mean that operating it is free.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRecipe fees: Not specified.\u003c/li\u003e\n\u003cli\u003eGPU and cloud operating costs: Not specified.\u003c/li\u003e\n\u003cli\u003eManaged API availability: Not specified.\u003c/li\u003e\n\u003cli\u003eManaged API request fees and limits: Not specified.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003e\n\u003ca href=\"#up-to-2x-performance-and-requests-excluded-from-evaluation\" class=\"anchor\" id=\"up-to-2x-performance-and-requests-excluded-from-evaluation\"\u003e\u003c/a\u003eUp to 2x Performance and Requests Excluded from Evaluation\u003c/h2\u003e\n\u003cp\u003eNVIDIA said the B200-optimized recipes deliver \u003cstrong\u003eup to 2x\u003c/strong\u003e performance with the default configuration. This is a performance claim made by the company. The official excerpts reviewed do not include the comparison baseline or measurement conditions. No independent verification results were provided.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eItem\u003c/th\u003e\n\u003cth\u003eWhat the Official Source States\u003c/th\u003e\n\u003cth\u003eRemaining Caveats\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Item\"\u003eRecipe performance\u003c/td\u003e\n\u003ctd data-label=\"What the Official Source States\"\u003eNVIDIA's announcement claims up to 2x performance\u003c/td\u003e\n\u003ctd data-label=\"Remaining Caveats\"\u003eComparison baseline and measurement conditions unconfirmed\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Item\"\u003eK-EXAONE 2.0 evaluation requests\u003c/td\u003e\n\u003ctd data-label=\"What the Official Source States\"\u003e1,805 requests in NVIDIA's official evaluation documentation\u003c/td\u003e\n\u003ctd data-label=\"Remaining Caveats\"\u003e38 of these requests were excluded from the metrics\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Item\"\u003eReason for exclusion\u003c/td\u003e\n\u003ctd data-label=\"What the Official Source States\"\u003eHTTP 400 returned because requests exceeded the 262,144-token context limit\u003c/td\u003e\n\u003ctd data-label=\"Remaining Caveats\"\u003eThese failed requests are not reflected in the performance metrics\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eThe K-EXAONE 2.0 figures come from NVIDIA's official evaluation documentation. There is no basis for treating them as independent measurements. When citing the evaluation metrics, the request exclusion conditions should also be disclosed. The relationship between this evaluation and the up to 2x claim is also unconfirmed.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#exact-release-time-and-service-scope-remain-unconfirmed\" class=\"anchor\" id=\"exact-release-time-and-service-scope-remain-unconfirmed\"\u003e\u003c/a\u003eExact Release Time and Service Scope Remain Unconfirmed\u003c/h2\u003e\n\u003cp\u003eThe difference between the official page date and the feed timestamp has not been explained. The official page displays November 8, 2026. The feed timestamp is November 9, 2026, at 05:00 UTC. Converted to Korean time, this is 14:00 on the same day.\u003c/p\u003e\n\u003cp\u003eThis information alone cannot establish the exact release time. The time zone used for the official page date is also unconfirmed. The scope of managed services available in Korea has not been specified either.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe reason for the date difference and the exact release time are unconfirmed.\u003c/li\u003e\n\u003cli\u003eUsage conditions for Korea and the availability of hosting in Korea are unconfirmed.\u003c/li\u003e\n\u003cli\u003eManaged API availability and request conditions are unconfirmed.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003e\n\u003ca href=\"#what-to-check-before-deploying-in-korea\" class=\"anchor\" id=\"what-to-check-before-deploying-in-korea\"\u003e\u003c/a\u003eWhat to Check Before Deploying in Korea\u003c/h2\u003e\n\u003cp\u003eFor self-deployment, first check the runtime environment in each model's official documentation. Solar Open2, in particular, requires the specified dedicated image. The default Dynamo 1.4.1 vLLM runtime does not include this model's definition.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eA.X-K2 has different total GPU requirements for aggregated and disaggregated deployments. The B200 requirements should not be applied unchanged to the H200 configuration.\u003c/li\u003e\n\u003cli\u003eA.X-K2 can reuse a PVC that already stores the model. A PVC is a request that specifies storage for a deployment. Set \u003ccode\u003eclaimName\u003c/code\u003e in both the download job and the selected deployment source to that PVC. In this case, creating a new PVC can be skipped.\u003c/li\u003e\n\u003cli\u003eFor K-EXAONE 2.0, the checkpoint size and required free space differ. Securing only approximately 530 GB does not meet the documented requirements. A ReadWriteMany storage class needs at least 700 GB of free space.\u003c/li\u003e\n\u003cli\u003eSolar Open2 must use the image pinned in the recipe. It is not an optional component that can be replaced with the default runtime.\u003c/li\u003e\n\u003cli\u003eFor Motif-3, choose either an aggregated or a 3P1D deployment configuration. Check each worker's GPU requirements as well.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eBefore paying for cloud resources, check the cost estimate for your chosen environment. NVIDIA's up to 2x claim cannot be used as a performance guarantee for your own environment. Usage conditions for Korea and managed API support require separate confirmation.\u003c/p\u003e\n","tags":["Generative AI","AI Data Center","AI Development","Development Tools"],"faqs":[{"question":"Has a managed API that can be called directly from Korea been released?","answer":"The confirmed announcement covers a Dynamo recipe for deploying the model yourself. The availability of a managed API, call pricing, and usage limits were not specified. Terms of use in Korea and the availability of hosting in Korea have not been confirmed either."},{"question":"How many GPUs are needed to deploy A.X K2?","answer":"The B200 configurations in the official documentation require 8 GPUs for the aggregated setup and 12 GPUs for the disaggregated setup. Each worker requires 4 B200 GPUs and 400 GiB of host memory. H200 configurations are also documented, but there is no basis for applying these figures as H200 requirements."},{"question":"Can I expect up to 2 times the performance and free use even if I run it in Korea?","answer":"NVIDIA claims up to 2 times the performance. The comparison baseline, measurement conditions, and independent verification results have not been confirmed. Recipe usage fees and GPU and cloud operating costs were not specified either."}],"sources":[{"url":"https://blogs.nvidia.com/blog/nvidia-dynamo-korea-open-models/","title":"NVIDIA Dynamo Recipes Bring Korea’s Leading Open Models to Production - NVIDIA","type":"source"},{"url":"https://docs.nvidia.com/dynamo/dev/recipes/ax-k2","title":"A.X-K2 - NVIDIA","type":"source"},{"url":"https://docs.nvidia.com/dynamo/dev/recipes/k-exaone-2","title":"K-EXAONE 2.0 - NVIDIA","type":"source"},{"url":"https://docs.nvidia.com/dynamo/dev/recipes/solar-open2-250b","title":"Solar Open2 250B - NVIDIA","type":"source"},{"url":"https://docs.nvidia.com/dynamo/dev/recipes/motif-3","title":"Motif-3 NVFP4 - NVIDIA","type":"source"}],"images":[{"id":2614,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6NDAzNjMsInB1ciI6ImJsb2JfaWQifX0=--dd83975b25d621fd4e4e9a989609a481ad2c2219/ai-f1259fd5.webp","is_representative":true,"generation_method":"ai_photo","license":"ai_generated","mime_type":"image/webp","width":1536,"height":1024,"translations":{"ko":{"alt":"서버실에서 랙 밖으로 꺼낸 GPU 서버의 내부를 점검하는 기술자","caption":"Dynamo 배포에 필요한 GPU 구성은 모델마다 다르다.","description":null},"en":{"alt":"A technician inspects the inside of a GPU server pulled out from a rack in a server room.","caption":"GPU configuration requirements for Dynamo deployment vary by model.","description":null},"ja":{"alt":"サーバールームでラックから引き出したGPUサーバーの内部を点検する技術者","caption":"Dynamoのデプロイに必要なGPU構成はモデルによって異なる。","description":null},"es":{"alt":"Un técnico revisa el interior de un servidor GPU extraído de un rack en una sala de servidores.","caption":"Los requisitos de configuración de GPU para desplegar con Dynamo varían según el modelo.","description":null},"id":{"alt":"Seorang teknisi memeriksa bagian dalam server GPU yang ditarik keluar dari rak di ruang server.","caption":"Kebutuhan konfigurasi GPU untuk deployment dengan Dynamo berbeda menurut model.","description":null},"pt":{"alt":"Um técnico inspeciona o interior de um servidor GPU retirado de um rack em uma sala de servidores.","caption":"Os requisitos de configuração de GPU para implantação com Dynamo variam conforme o modelo.","description":null},"zh-hant":{"alt":"技術人員在伺服器機房內，檢查從機櫃拉出的 GPU 伺服器內部。","caption":"透過 Dynamo 部署時，所需的 GPU 配置因模型而異。","description":null},"de":{"alt":"Ein Techniker prüft das Innere eines aus dem Rack gezogenen GPU-Servers im Serverraum.","caption":"Die erforderliche GPU-Konfiguration für die Bereitstellung mit Dynamo hängt vom Modell ab.","description":null}}},{"id":2615,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6NDAzNjksInB1ciI6ImJsb2JfaWQifX0=--5566781ab9cb13485cab83b54fe0e6368ad019ae/ai-d903a943.webp","is_representative":false,"generation_method":"ai_semi","license":"ai_generated","mime_type":"image/webp","width":1536,"height":1024,"translations":{"ko":{"alt":"데이터센터에서 여성 기술자가 보라색 광케이블을 패치 패널에 연결하고 있다.","caption":"NVIDIA의 Dynamo 레시피는 한국 공개 모델 4종의 최적화 배포를 지원한다.","description":null},"en":{"alt":"A woman technician connects a purple fibre cable to a patch panel in a data centre.","caption":"NVIDIA’s Dynamo recipes support optimized deployment of four Korean open models.","description":null},"ja":{"alt":"データセンターで女性技術者が紫色の光ファイバーケーブルをパッチパネルに接続している。","caption":"NVIDIAのDynamoレシピは、韓国の公開モデル4種の最適化されたデプロイを支援する。","description":null},"es":{"alt":"Una técnica conecta un cable de fibra óptica violeta a un panel de conexiones en un centro de datos.","caption":"Las recetas de Dynamo de NVIDIA facilitan el despliegue optimizado de cuatro modelos abiertos coreanos.","description":null},"id":{"alt":"Seorang teknisi perempuan menghubungkan kabel serat optik ungu ke panel patch di pusat data.","caption":"Resep Dynamo NVIDIA mendukung penerapan yang dioptimalkan untuk empat model terbuka Korea.","description":null},"pt":{"alt":"Uma técnica conecta um cabo de fibra óptica roxo a um painel de conexões em um centro de dados.","caption":"As receitas do NVIDIA Dynamo apoiam a implantação otimizada de quatro modelos abertos coreanos.","description":null},"zh-hant":{"alt":"一名女性技術人員在資料中心將紫色光纖纜線接上配線面板。","caption":"NVIDIA 的 Dynamo 部署配方支援四款韓國開放模型的最佳化部署。","description":null},"de":{"alt":"Eine Technikerin verbindet ein violettes Glasfaserkabel mit einem Patchpanel im Rechenzentrum.","caption":"NVIDIAs Dynamo-Rezepte unterstützen die optimierte Bereitstellung von vier koreanischen offenen Modellen.","description":null}}}],"published_at":"2026-11-09T14:46:39+09:00","updated_at":"2026-11-09T14:46:39+09:00","license":"cc_by","translation_status":"reviewed","available_locales":["ko","en","ja","es"],"data_locales":["ko","en","ja","es","id","pt","zh-hant","de"],"url":"https://injoys.com/en/articles/nvidia-dynamo-korean-open-model-deployment-recipes"}