{"id":1301,"date":"2025-09-09T10:11:28","date_gmt":"2025-09-09T10:11:28","guid":{"rendered":"https:\/\/blog.aetherix.com\/?p=1301"},"modified":"2026-03-27T13:44:56","modified_gmt":"2026-03-27T13:44:56","slug":"how-to-run-ollama-on-jetson-agx-thor-with-openwebui","status":"publish","type":"post","link":"https:\/\/blog.openzeka.com\/en\/how-to-run-ollama-on-jetson-agx-thor-with-openwebui\/","title":{"rendered":"How to Run Ollama on Jetson AGX Thor with OpenwebUI?"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1331.2px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-three\"><h3 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">What is Ollama?<\/h3><\/div><div class=\"fusion-text fusion-text-1\"><p>Ollama is a lightweight and flexible platform that allows you to run large language models (LLMs) directly on your own device. When running on powerful AI hardware such as the <strong>NVIDIA Jetson AGX Thor<\/strong>, it provides a local, fast, and secure experience without the need for cloud-based solutions.<\/p>\n<p>Thanks to the high processing power of Jetson AGX Thor, Ollama:<\/p>\n<ul>\n<li><strong>Runs LLMs locally<\/strong> \u2192 Can be used even without an internet connection.<\/li>\n<li><strong>Utilizes hardware acceleration<\/strong> \u2192 Leverages GPU power to generate faster responses.<\/li>\n<li><strong>Ensures data privacy<\/strong> \u2192 All processing happens on-device, so sensitive data never leaves the system.<\/li>\n<li><strong>Offers flexibility<\/strong> \u2192 Different models can be downloaded, customized, and tested.<\/li>\n<\/ul>\n<p>In short, Ollama leverages the hardware advantages of AGX Jetson Thor to make AI applications more accessible, portable, and secure.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-2 fusion-sep-none fusion-title-text fusion-title-size-three\"><h3 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">Requirements for AGX Thor<\/h3><\/div><div class=\"fusion-text fusion-text-2\"><ol>\n<li>JetPack 7 must be installed<\/li>\n<li>Stable high-speed internet connection<\/li>\n<li>At least 15 GB of free disk space (excluding model storage for Ollama itself)<\/li>\n<\/ol>\n<\/div><div class=\"fusion-title title fusion-title-3 fusion-sep-none fusion-title-text fusion-title-size-three\"><h3 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">Installation Process<\/h3><\/div><div class=\"fusion-text fusion-text-3\"><p>First, we create a folder to mount into the container.<\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-1 > .CodeMirror, .fusion-syntax-highlighter-1 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-1 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_1\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_1\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_1\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">mkdir ~\/ollama-data\/<\/textarea><\/div><div class=\"fusion-text fusion-text-4\" style=\"--awb-margin-top:20px;\"><p>Next, we download the image from the <strong>GitHub Container Registry.<\/strong><br \/>\nThe <strong>ghcr.io<\/strong> prefix indicates that the image is hosted on the GitHub Container Registry.<\/p>\n<p>To access other images or check for the latest updates, you can visit the following <strong><a style=\"color: #2a9e00;\" href=\"https:\/\/github.com\/orgs\/NVIDIA-AI-IOT\/packages\/container\/package\/ollama\">link.<\/a><\/strong><\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-2 > .CodeMirror, .fusion-syntax-highlighter-2 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-2 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_2\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_2\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_2\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">docker run --rm -it -v ${HOME}\/ollama-data:\/data ghcr.io\/nvidia-ai-iot\/ollama:r38.2.arm64-sbsa-cu130-24.04<\/textarea><\/div><div class=\"fusion-text fusion-text-5\" style=\"--awb-margin-top:20px;\"><p>It will take some time to pull (download) the container image.<\/p>\n<p>Once in the container, you will see something like this.<\/p>\n<\/div><div class=\"fusion-image-element \" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-1 hover-type-none\"><img decoding=\"async\" width=\"848\" height=\"817\" title=\"Screenshot from 2025-09-08 11-44-34\" src=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34.png\" alt class=\"img-responsive wp-image-1306\" srcset=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34-200x193.png 200w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34-400x385.png 400w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34-600x578.png 600w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34-800x771.png 800w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-44-34.png 848w\" sizes=\"(max-width: 640px) 100vw, 848px\" \/><\/span><\/div><div class=\"fusion-text fusion-text-6\" style=\"--awb-margin-top:20px;\"><p>Try running a GPT OSS (20b parameter) model by issuing a command below.<\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-3 > .CodeMirror, .fusion-syntax-highlighter-3 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-3 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_3\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_3\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_3\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">ollama run --verbose gpt-oss:20b<\/textarea><\/div><div class=\"fusion-text fusion-text-7\" style=\"--awb-margin-top:20px;\"><p>Once ready, it will show something like this:<\/p>\n<\/div><div class=\"fusion-image-element \" style=\"text-align:center;--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-2 hover-type-none\"><img decoding=\"async\" width=\"697\" height=\"522\" title=\"Screenshot from 2025-09-08 11-50-28\" src=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-50-28.png\" alt class=\"img-responsive wp-image-1310\" srcset=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-50-28-200x150.png 200w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-50-28-400x300.png 400w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-50-28-600x449.png 600w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-11-50-28.png 697w\" sizes=\"(max-width: 640px) 100vw, 697px\" \/><\/span><\/div><div class=\"fusion-title title fusion-title-4 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-margin-top:20px;\"><h3 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">Troubleshooting<\/h3><\/div><div class=\"fusion-text fusion-text-8\"><p><strong>CUDA out of memory<\/strong><\/p>\n<p>If you encounter CUDA out of memory errors, try running a <strong>smaller model.<\/strong><br \/>\nYou can also use quantization to reduce memory usage and run models more efficiently on your device.<\/p>\n<p>Different model sizes and quantized versions can be found <strong><a style=\"color: #1bcc00;\" href=\"https:\/\/ollama.com\">here<\/a><span style=\"color: #1bcc00;\">.<\/span> <\/strong><\/p>\n<\/div><div class=\"fusion-title title fusion-title-5 fusion-sep-none fusion-title-text fusion-title-size-three\"><h3 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">Installing OpenwebUI<\/h3><\/div><div class=\"fusion-text fusion-text-9\"><p>Firsty run this command on terminal ;<\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-4 > .CodeMirror, .fusion-syntax-highlighter-4 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-4 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_4\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_4\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_4\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">docker run -it --rm --network=host --add-host=host.docker.internal:host-gateway ghcr.io\/open-webui\/open-webui:main<\/textarea><\/div><div class=\"fusion-text fusion-text-10\" style=\"--awb-margin-top:20px;\"><p><em>If you see the <strong>&#8220;application startup&#8221;<\/strong> message on the screen, you can proceed to the next step.<\/em><br \/>\n<em>If it says <strong>&#8220;retrying&#8221;<\/strong> and you don\u2019t see any progress in the download section, stop the process with <strong>Control + C<\/strong> and try again or just wait. There should be no problem.<\/em><\/p>\n<\/div><div class=\"fusion-image-element \" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-3 hover-type-none\"><img decoding=\"async\" width=\"960\" height=\"589\" title=\"Screenshot from 2025-09-08 13-31-30\" src=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30.png\" alt class=\"img-responsive wp-image-1314\" srcset=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30-200x123.png 200w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30-400x245.png 400w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30-600x368.png 600w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30-800x491.png 800w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-31-30.png 960w\" sizes=\"(max-width: 640px) 100vw, 960px\" \/><\/span><\/div><div class=\"fusion-text fusion-text-11\" style=\"--awb-margin-top:20px;\"><p>You can then navigate your browser to <em><strong>http:\/\/JETSON_IP:8080<\/strong><\/em> , and create a fake account to log in (these credentials are only local). Instead of <strong>JETSON_IP<\/strong>, you can also use localhost.<\/p>\n<p>Create an account .<\/p>\n<\/div><div class=\"fusion-image-element \" style=\"text-align:center;--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-4 hover-type-none\"><img decoding=\"async\" width=\"613\" height=\"482\" title=\"Screenshot from 2025-09-08 13-36-48\" src=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-36-48.png\" alt class=\"img-responsive wp-image-1315\" srcset=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-36-48-200x157.png 200w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-36-48-400x315.png 400w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-36-48-600x472.png 600w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-13-36-48.png 613w\" sizes=\"(max-width: 640px) 100vw, 613px\" \/><\/span><\/div><div class=\"fusion-text fusion-text-12\"><p><em><strong>\u26a0\ufe0f Be careful !<\/strong> When OpenWebUI is launched, <strong>no model<\/strong> will appear in the <strong>Load Models<\/strong> section at the top left. To connect models to <strong>OpenWebUI<\/strong>, we need to assign a port. Restart the Ollama container with the following command:<\/em><\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-5 > .CodeMirror, .fusion-syntax-highlighter-5 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-5 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_5\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_5\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_5\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">docker run --rm -it \\\n  -p 11434:11434 \\\n  -v ${HOME}\/ollama-data:\/data \\\n  ghcr.io\/nvidia-ai-iot\/ollama:r38.2.arm64-sbsa-cu130-24.04<\/textarea><\/div><div class=\"fusion-text fusion-text-13\" style=\"--awb-margin-top:20px;\"><p data-start=\"53\" data-end=\"98\">You can check it by sending a <strong>curl request:<\/strong><\/p>\n<\/div><style type=\"text\/css\" scopped=\"scopped\">.fusion-syntax-highlighter-6 > .CodeMirror, .fusion-syntax-highlighter-6 > .CodeMirror .CodeMirror-gutters {background-color:#000000;}<\/style><div class=\"fusion-syntax-highlighter-container fusion-syntax-highlighter-6 fusion-syntax-highlighter-theme-dark\" style=\"opacity:0;margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;font-size:14px;border-width:1px;border-style:solid;border-color:rgba(242,243,245,0);\"><div class=\"syntax-highlighter-copy-code\"><span class=\"syntax-highlighter-copy-code-title\" data-id=\"fusion_syntax_highlighter_6\" style=\"font-size:14px;\">Copy to Clipboard<\/span><\/div><label for=\"fusion_syntax_highlighter_6\" class=\"screen-reader-text\">Syntax Highlighter<\/label><textarea class=\"fusion-syntax-highlighter-textarea\" id=\"fusion_syntax_highlighter_6\" data-readOnly=\"nocursor\" data-lineNumbers=\"\" data-lineWrapping=\"\" data-theme=\"oceanic-next\" data-mode=\"text\/x-sh\">curl http:\/\/localhost:11434<\/textarea><\/div><div class=\"fusion-text fusion-text-14\" style=\"--awb-margin-top:20px;\"><p>If you see \u201c<strong>Ollama is running<\/strong>\u201d, you can continue using it.<\/p>\n<\/div><div class=\"fusion-image-element \" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\" fusion-imageframe imageframe-none imageframe-5 hover-type-none\"><img decoding=\"async\" width=\"1024\" height=\"261\" title=\"Screenshot from 2025-09-08 14-08-00\" src=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00-1024x261.png\" alt class=\"img-responsive wp-image-1320\" srcset=\"https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00-200x51.png 200w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00-400x102.png 400w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00-600x153.png 600w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00-800x204.png 800w, https:\/\/blog.openzeka.com\/en\/wp-content\/uploads\/2025\/09\/Screenshot-from-2025-09-08-14-08-00.png 1058w\" sizes=\"(max-width: 640px) 100vw, 1024px\" \/><\/span><\/div><div class=\"fusion-title title fusion-title-6 fusion-sep-none fusion-title-text fusion-title-size-four\"><h4 class=\"fusion-title-heading title-heading-left\" style=\"margin:0;\">Which Jetson should I choose for my LLM model?<\/h4><\/div><div class=\"fusion-text fusion-text-15 fusion-text-no-margin\" style=\"--awb-margin-bottom:-20px;\"><p>Below, you can find the RAM requirements of the most popular LLM models along with Jetson recommendations that meet the minimum specifications to run them. You can choose the one that best fits your needs.<\/p>\n<\/div>\n<div class=\"table-1\">\n<p>&nbsp;<\/p>\n<table width=\"100%\">\n<thead>\n<tr>\n<th align=\"left\">Model<\/th>\n<th align=\"left\">Parameters<\/th>\n<th align=\"left\">Quantization<\/th>\n<th align=\"left\">Required RAM (GB)<\/th>\n<th align=\"left\">Recommended Minimum Jetson<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td align=\"left\">DeepSeek-R1<\/td>\n<td align=\"left\">671B<\/td>\n<td align=\"left\">Dynamic-1.58-bit (MoE 1.5-bit + other layers 4\u20136-bit)<\/td>\n<td align=\"left\">159.03<\/td>\n<td align=\"left\">Not supported (\u2265128 GB and above)<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">DeepSeek-R1 Distill-Qwen-1.5B<\/td>\n<td align=\"left\">1.5B<\/td>\n<td align=\"left\">Q4_K_M<\/td>\n<td align=\"left\">0.90<\/td>\n<td align=\"left\">Jetson Orin Nano 4 GB, Jetson Nano 4 GB<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">DeepSeek-R1 Distill-Qwen-7B<\/td>\n<td align=\"left\">7B<\/td>\n<td align=\"left\">Q5_K_M<\/td>\n<td align=\"left\">5.25<\/td>\n<td align=\"left\">Jetson Orin Nano 8 GB, Jetson Orin NX 8 GB, Jetson Xavier NX 8 GB<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">Qwen 2.5<\/td>\n<td align=\"left\">14B<\/td>\n<td align=\"left\">FP16<\/td>\n<td align=\"left\">33.60<\/td>\n<td align=\"left\">Jetson AGX Orin 64 GB, Jetson AGX Xavier 64 GB<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">CodeLlama<\/td>\n<td align=\"left\">34B<\/td>\n<td align=\"left\">Q4_K_M<\/td>\n<td align=\"left\">20.40<\/td>\n<td align=\"left\">Jetson AGX Orin 32 GB, Jetson AGX Xavier 32 GB<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">Llama 3.2 Vision<\/td>\n<td align=\"left\">90B<\/td>\n<td align=\"left\">Q5_K_M<\/td>\n<td align=\"left\">67.50<\/td>\n<td align=\"left\">Jetson AGX Thor (T5000) 128 GB<\/td>\n<\/tr>\n<tr>\n<td align=\"left\">Phi-3<\/td>\n<td align=\"left\">3.8B<\/td>\n<td align=\"left\">FP16<\/td>\n<td align=\"left\">9.12<\/td>\n<td align=\"left\">Jetson Orin NX 16 GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":1607,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[],"class_list":["post-1301","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-generative-ai"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.3.1 (Yoast SEO v25.3.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to Run Ollama on Jetson AGX Thor with OpenwebUI? 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