Viewing enriched Twitter post
Ray (@raydistributed) and @vllm_project are helping developers understand when prefill-decode disaggregation can improve throughput and reduce compute costs, and when aggregated serving remains the better choice. Read more: https://t.co/8oD7LzUDPx
{
"media": [
{
"url": "https://crmoxkoizveukayfjuyo.supabase.co/storage/v1/object/public/media/posts/2067702252383703401/media_0.jpg",
"media_url": "https://crmoxkoizveukayfjuyo.supabase.co/storage/v1/object/public/media/posts/2067702252383703401/media_0.jpg",
"type": "photo",
"filename": "media_0.jpg"
}
],
"processed_at": "2026-06-18T20:20:19.970530",
"pipeline_version": "2.0"
}{
"type": "tweet",
"id": "2067702252383703401",
"url": "https://x.com/PyTorch/status/2067702252383703401",
"twitterUrl": "https://twitter.com/PyTorch/status/2067702252383703401",
"text": "Ray (@raydistributed) and @vllm_project are helping developers understand when prefill-decode disaggregation can improve throughput and reduce compute costs, and when aggregated serving remains the better choice.\n\nRead more: https://t.co/8oD7LzUDPx",
"source": "Twitter for iPhone",
"retweetCount": 3,
"replyCount": 0,
"likeCount": 3,
"quoteCount": 0,
"viewCount": 481,
"createdAt": "Thu Jun 18 20:13:27 +0000 2026",
"lang": "en",
"bookmarkCount": 0,
"isReply": false,
"inReplyToId": null,
"conversationId": "2067702252383703401",
"displayTextRange": [
0,
250
],
"inReplyToUserId": null,
"inReplyToUsername": null,
"author": {
"type": "user",
"userName": "PyTorch",
"url": "https://x.com/PyTorch",
"twitterUrl": "https://twitter.com/PyTorch",
"id": "776585502606721024",
"name": "PyTorch",
"isVerified": false,
"isBlueVerified": true,
"verifiedType": null,
"profilePicture": "https://pbs.twimg.com/profile_images/1813965160702451712/yXV1vRhr_normal.jpg",
"coverPicture": "https://pbs.twimg.com/profile_banners/776585502606721024/1761575044",
"description": "",
"location": "",
"followers": 497974,
"following": 87,
"status": "",
"canDm": false,
"canMediaTag": true,
"createdAt": "Fri Sep 16 00:56:26 +0000 2016",
"entities": {
"description": {
"urls": []
},
"url": {}
},
"fastFollowersCount": 0,
"favouritesCount": 951,
"hasCustomTimelines": true,
"isTranslator": false,
"mediaCount": 1512,
"statusesCount": 3347,
"withheldInCountries": [],
"affiliatesHighlightedLabel": {},
"possiblySensitive": false,
"pinnedTweetIds": [],
"profile_bio": {
"description": "Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation",
"entities": {
"description": {
"hashtags": [
{
"indices": [
132,
150
],
"text": "PyTorchFoundation"
}
]
},
"url": {
"urls": [
{
"display_url": "pytorch.org",
"expanded_url": "http://pytorch.org",
"indices": [
0,
23
],
"url": "https://t.co/6SwTBhUwTJ"
}
]
}
}
},
"isAutomated": false,
"automatedBy": null
},
"extendedEntities": {},
"card": {
"binding_values": [
{
"key": "photo_image_full_size_large",
"value": {
"image_value": {
"height": 419,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x419",
"width": 800
}
}
},
{
"key": "thumbnail_image",
"value": {
"image_value": {
"height": 150,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=280x150",
"width": 225
}
}
},
{
"key": "description",
"value": {
"string_value": "Boost LLM Inference on AMD MI325X with Ray Serve and vLLM. Up to 2.7x More Throughput and 67% Lower Compute Costs"
}
},
{
"key": "domain",
"value": {
"string_value": "www.anyscale.com"
}
},
{
"key": "thumbnail_image_large",
"value": {
"image_value": {
"height": 320,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x320_1",
"width": 480
}
}
},
{
"key": "summary_photo_image_small",
"value": {
"image_value": {
"height": 202,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=386x202",
"width": 386
}
}
},
{
"key": "thumbnail_image_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
},
{
"key": "photo_image_full_size_small",
"value": {
"image_value": {
"height": 202,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=386x202",
"width": 386
}
}
},
{
"key": "summary_photo_image_large",
"value": {
"image_value": {
"height": 419,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x419",
"width": 800
}
}
},
{
"key": "thumbnail_image_small",
"value": {
"image_value": {
"height": 67,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=100x100",
"width": 100
}
}
},
{
"key": "thumbnail_image_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "photo_image_full_size_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
},
{
"key": "vanity_url",
"value": {
"scribe_key": "vanity_url",
"string_value": "anyscale.com"
}
},
{
"key": "photo_image_full_size",
"value": {
"image_value": {
"height": 314,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=600x314",
"width": 600
}
}
},
{
"key": "thumbnail_image_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "title",
"value": {
"string_value": "Achieving Up to 67% Cost Savings with Prefill-Decode Disaggregation Using Ray + vLLM on AMD MI325X..."
}
},
{
"key": "summary_photo_image_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "summary_photo_image_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "summary_photo_image",
"value": {
"image_value": {
"height": 314,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=600x314",
"width": 600
}
}
},
{
"key": "photo_image_full_size_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "photo_image_full_size_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "card_url",
"value": {
"scribe_key": "card_url",
"string_value": "https://t.co/8oD7LzUDPx"
}
},
{
"key": "summary_photo_image_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
}
],
"card_platform": {
"platform": {
"audience": {
"name": "production"
},
"device": {
"name": "iPhone",
"version": "13"
}
}
},
"name": "summary_large_image",
"url": "https://t.co/8oD7LzUDPx",
"user_refs_results": []
},
"place": {},
"entities": {
"urls": [
{
"display_url": "anyscale.com/blog/ray-vllm-…",
"expanded_url": "https://www.anyscale.com/blog/ray-vllm-prefill-decode-disaggregation-amd-mi325x-67-percent-savings",
"indices": [
227,
250
],
"url": "https://t.co/8oD7LzUDPx"
}
],
"user_mentions": [
{
"id_str": "1158917863538745344",
"indices": [
5,
20
],
"name": "ray",
"screen_name": "raydistributed"
},
{
"id_str": "1774187564276289536",
"indices": [
27,
40
],
"name": "vLLM",
"screen_name": "vllm_project"
}
]
},
"quoted_tweet": {
"type": "tweet",
"id": "2066609210008453258",
"url": "https://x.com/anyscalecompute/status/2066609210008453258",
"twitterUrl": "https://twitter.com/anyscalecompute/status/2066609210008453258",
"text": "Save 67% with prefill-decode disaggregation using Ray + vLLM on AMD GPUs.\n\nhttps://t.co/vTwluijGVW",
"source": "Twitter for iPhone",
"retweetCount": 5,
"replyCount": 0,
"likeCount": 13,
"quoteCount": 2,
"viewCount": 6112,
"createdAt": "Mon Jun 15 19:50:06 +0000 2026",
"lang": "en",
"bookmarkCount": 5,
"isReply": false,
"inReplyToId": null,
"conversationId": "2066609210008453258",
"displayTextRange": [
0,
98
],
"inReplyToUserId": null,
"inReplyToUsername": null,
"author": {
"type": "user",
"userName": "anyscalecompute",
"url": "https://x.com/anyscalecompute",
"twitterUrl": "https://twitter.com/anyscalecompute",
"id": "1173110913517281280",
"name": "Anyscale",
"isVerified": false,
"isBlueVerified": true,
"verifiedType": null,
"profilePicture": "https://pbs.twimg.com/profile_images/1849862648239988736/ruJveZZX_normal.jpg",
"coverPicture": "https://pbs.twimg.com/profile_banners/1173110913517281280/1729828853",
"description": "",
"location": "",
"followers": 13022,
"following": 3,
"status": "",
"canDm": false,
"canMediaTag": true,
"createdAt": "Sun Sep 15 05:46:59 +0000 2019",
"entities": {
"description": {
"urls": []
},
"url": {}
},
"fastFollowersCount": 0,
"favouritesCount": 1667,
"hasCustomTimelines": true,
"isTranslator": false,
"mediaCount": 493,
"statusesCount": 1924,
"withheldInCountries": [],
"affiliatesHighlightedLabel": {},
"possiblySensitive": false,
"pinnedTweetIds": [],
"profile_bio": {
"description": "The best way to run @raydistributed, the distributed compute framework for scaling AI workloads.",
"entities": {
"description": {
"user_mentions": [
{
"id_str": "",
"indices": [
20,
35
],
"name": "",
"screen_name": "raydistributed"
}
]
},
"url": {
"urls": [
{
"display_url": "anyscale.com",
"expanded_url": "https://anyscale.com",
"indices": [
0,
23
],
"url": "https://t.co/e1xNdOIezu"
}
]
}
}
},
"isAutomated": false,
"automatedBy": null
},
"extendedEntities": {},
"card": {
"binding_values": [
{
"key": "photo_image_full_size_large",
"value": {
"image_value": {
"height": 419,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x419",
"width": 800
}
}
},
{
"key": "thumbnail_image",
"value": {
"image_value": {
"height": 150,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=280x150",
"width": 225
}
}
},
{
"key": "description",
"value": {
"string_value": "Boost LLM Inference on AMD MI325X with Ray Serve and vLLM. Up to 2.7x More Throughput and 67% Lower Compute Costs"
}
},
{
"key": "domain",
"value": {
"string_value": "www.anyscale.com"
}
},
{
"key": "thumbnail_image_large",
"value": {
"image_value": {
"height": 320,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x320_1",
"width": 480
}
}
},
{
"key": "summary_photo_image_small",
"value": {
"image_value": {
"height": 202,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=386x202",
"width": 386
}
}
},
{
"key": "thumbnail_image_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
},
{
"key": "photo_image_full_size_small",
"value": {
"image_value": {
"height": 202,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=386x202",
"width": 386
}
}
},
{
"key": "summary_photo_image_large",
"value": {
"image_value": {
"height": 419,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=800x419",
"width": 800
}
}
},
{
"key": "thumbnail_image_small",
"value": {
"image_value": {
"height": 67,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=100x100",
"width": 100
}
}
},
{
"key": "thumbnail_image_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "photo_image_full_size_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
},
{
"key": "vanity_url",
"value": {
"scribe_key": "vanity_url",
"string_value": "anyscale.com"
}
},
{
"key": "photo_image_full_size",
"value": {
"image_value": {
"height": 314,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=600x314",
"width": 600
}
}
},
{
"key": "thumbnail_image_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "title",
"value": {
"string_value": "Achieving Up to 67% Cost Savings with Prefill-Decode Disaggregation Using Ray + vLLM on AMD MI325X..."
}
},
{
"key": "summary_photo_image_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "summary_photo_image_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "summary_photo_image",
"value": {
"image_value": {
"height": 314,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=600x314",
"width": 600
}
}
},
{
"key": "photo_image_full_size_color",
"value": {
"image_color_value": {
"palette": [
{
"percentage": 96.99,
"rgb": {
"blue": 255,
"green": 255,
"red": 255
}
},
{
"percentage": 1.15,
"rgb": {
"blue": 199,
"green": 229,
"red": 200
}
},
{
"percentage": 1.08,
"rgb": {
"blue": 190,
"green": 214,
"red": 254
}
},
{
"percentage": 0.42,
"rgb": {
"blue": 145,
"green": 143,
"red": 143
}
},
{
"percentage": 0.18,
"rgb": {
"blue": 218,
"green": 190,
"red": 148
}
}
]
}
}
},
{
"key": "photo_image_full_size_x_large",
"value": {
"image_value": {
"height": 1365,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=png&name=2048x2048_2_exp",
"width": 2048
}
}
},
{
"key": "card_url",
"value": {
"scribe_key": "card_url",
"string_value": "https://t.co/vTwluijGVW"
}
},
{
"key": "summary_photo_image_original",
"value": {
"image_value": {
"height": 2000,
"url": "https://pbs.twimg.com/card_img/2066571118987919360/8jvVCa18?format=jpg&name=orig",
"width": 3000
}
}
}
],
"card_platform": {
"platform": {
"audience": {
"name": "production"
},
"device": {
"name": "iPhone",
"version": "13"
}
}
},
"name": "summary_large_image",
"url": "https://t.co/vTwluijGVW",
"user_refs_results": []
},
"place": {},
"entities": {
"urls": [
{
"display_url": "anyscale.com/blog/ray-vllm-…",
"expanded_url": "https://www.anyscale.com/blog/ray-vllm-prefill-decode-disaggregation-amd-mi325x-67-percent-savings",
"indices": [
75,
98
],
"url": "https://t.co/vTwluijGVW"
}
]
},
"quoted_tweet": {
"type": "tweet",
"id": "2066571490544455680",
"url": "",
"twitterUrl": "",
"text": "",
"source": "Twitter for iPhone",
"retweetCount": 0,
"replyCount": 0,
"likeCount": 0,
"quoteCount": 0,
"viewCount": 0,
"createdAt": "",
"lang": "",
"bookmarkCount": 0,
"isReply": false,
"inReplyToId": null,
"conversationId": "",
"displayTextRange": [],
"inReplyToUserId": null,
"inReplyToUsername": null,
"author": {},
"extendedEntities": {},
"card": null,
"place": {},
"entities": {},
"quoted_tweet": null,
"retweeted_tweet": null,
"isLimitedReply": false,
"communityInfo": null,
"article": null
},
"retweeted_tweet": null,
"isLimitedReply": false,
"communityInfo": null,
"article": null
},
"retweeted_tweet": null,
"isLimitedReply": false,
"communityInfo": null,
"article": null
}