vLLM（ヴイエルエルエム）

概要\n\nvLLM(ヴイエルエルエム)はUC Berkeley Sky Computing Lab 2023年6月公開のvLLMで、Pro 業界Pro Mainstream High-Throughput LLM Serving Top + Pro UC Berkeley Sky Computing Lab + Pro Woosuk Kwon Pro主要研究員 + Pro PagedAttention Pro Famous + Pro Continuous Batching + Pro Apache 2.0 + Pro 30K+ GitHub Star + Pro High-Throughput LLM Serving Top Heritage継承代表機 + Pro PagedAttention Heritage継承代表機 + 累計2023-2026年3年Heritage Pro Top独占代表機。vLLM歴史: 2023-06-Pro vLLM論文発表Pro Famous Story類無し(UC Berkeley Sky Computing Lab + Woosuk Kwon + Pro 業界Pro Famous LLM Serving先駆) + 2023-Pro vLLM 0.1 + 2024-Pro vLLM 0.5/0.6 + 2024-12-Pro vLLM Production Stack公開Pro Famous + 2025-Pro vLLM 1.0公開予定Pro Famous + 累計2023-2026年3年Heritage継承。vLLM主要機能: (1)UC Berkeley Sky Computing Lab主導(米国California州Berkeley + Woosuk Kwon Pro主要研究員 + Zhuohan Li + Ying Sheng Pro Co-authors)、(2)Pro 業界Pro Mainstream High-Throughput LLM Serving Top(Pro 業界Pro Mainstream High-Throughput LLM Serving業界Top独占)、(3)Pro Woosuk Kwon Pro主要研究員、(4)Pro PagedAttention Pro Famous類無し(Pro 業界Pro Memory効率化革命 + Pro KV Cache分割管理)、(5)Pro Continuous Batching(Pro 動的Batchサイズ)、(6)Pro Apache 2.0 License、(7)Pro Python実装 + Pro CUDA、(8)Pro 30K+ GitHub Star、(9)Pro vLLM Production Stack(2024-12)、(10)Pro vLLM 0.6.x強化、(11)Pro Multi-Model対応(Llama/Qwen/DeepSeek/Mistral/GPT-OSS)、(12)Pro PyTorch、(13)Pro AMD ROCm/Intel/Apple Silicon対応、(14)Pro 2023-06 論文 + 2023-vLLM 0.1 + 2024-0.5/0.6 + 2024-12 Production Stack + 2025-1.0予定、(15)Pro 採用: OpenAI/Anthropic/Databricks/IBM、(16)Pro High-Throughput LLM Serving Top Heritage継承代表機 + Pro PagedAttention Heritage継承代表機 + 累計2023-2026年3年Heritage Pro Top独占代表機 + Pro業界History派 + Pro vLLM派 + Pro UC Berkeley派 + Pro Sky Computing Lab派 + Pro Woosuk Kwon派 + Pro Zhuohan Li派 + Pro Ying Sheng派 + Pro PagedAttention派 + Pro Memory効率化派 + Pro KV Cache派 + Pro Continuous Batching派 + Pro 動的Batch派 + Pro Apache 2.0派 + Pro Python派 + Pro CUDA派 + Pro 30K+派 + Pro Production Stack派 + Pro 0.6.x派 + Pro Multi-Model派 + Pro Llama派 + Pro Qwen派 + Pro DeepSeek派 + Pro Mistral派 + Pro GPT-OSS派 + Pro PyTorch派 + Pro ROCm派 + Pro Apple Silicon派 + Pro vLLM 1.0派 + Pro OpenAI派 + Pro Anthropic派 + Pro Databricks派 + Pro IBM派 + Pro 3年Heritage派 真価発揮。vLLM vs 競合LLM Serving比較: vLLM(2023-06、本レコード、UC Berkeley + Pro High-Throughput LLM Serving Top + 累計3年Heritage)・vLLM 0.1(2023)・vLLM 0.6(2024)・vLLM Production Stack(2024-12)・vLLM 1.0(2025-予定)・Text Generation Inference(2023 + Hugging Face)・LM Studio(2023 + GUI)・MLX-LM(2024 + Apple Silicon)・SGLang(2024 + Stanford)・llama.cpp(2023 + ggerganov)・Ollama(2023)・TensorRT-LLM(2023 + NVIDIA)・Ray Serve(2018)、vLLM = Pro High-Throughput LLM Serving Top + Pro PagedAttention + Pro Continuous Batching + Pro Apache 2.0 + Pro 30K+ + 3年Heritage、vLLM 0.1/0.6/Production Stack/1.0 = Pro系譜、TGI/LM Studio/MLX-LM/SGLang/llama.cpp/Ollama/TensorRT-LLM/Ray Serve = Pro主要競合。vLLM歴史的影響: (1)Pro 業界Pro Mainstream High-Throughput LLM Serving Top + 3年Heritage、(2)Pro UC Berkeley Sky Computing Lab + Pro Woosuk Kwon、(3)Pro PagedAttention = Memory効率化革命 + KV Cache分割管理、(4)Pro Continuous Batching = 動的Batchサイズ、(5)Pro Apache 2.0 + Pro Python + CUDA、(6)Pro 30K+ GitHub Star + Pro Multi-Model対応、(7)Pro AMD ROCm/Intel/Apple Silicon対応、(8)Pro vLLM Production Stack 2024-12、(9)Pro OpenAI/Anthropic/Databricks/IBM採用、(10)Pro業界History派 + Pro vLLM派 + Pro UC Berkeley派 + Pro PagedAttention派 + Pro 3年派 真価発揮。Future: 2023-06-vLLM論文 + 2023-0.1 + 2024-0.5/0.6 + 2024-12-Production Stack + 2025-1.0 + Pro Mainstream High-Throughput LLM Serving業界Top独占継続Heritage継続。\n\n## 主な特徴・仕組み\n\n- 公開: 2023-06 UC Berkeley vLLM論文\n- UC Berkeley Sky Computing Lab: 米国California州Berkeley\n- Co-authors: Woosuk Kwon + Zhuohan Li + Ying Sheng\n- Pro 業界Pro Mainstream High-Throughput LLM Serving Top\n- PagedAttention Pro Famous: 業界Memory効率化革命 + KV Cache分割管理\n- Continuous Batching: 動的Batchサイズ\n- Apache 2.0 License\n- Python実装 + CUDA\n- 30K+ GitHub Star\n- vLLM Production Stack (2024-12)\n- vLLM 0.6.x強化\n- Multi-Model対応: Llama/Qwen/DeepSeek/Mistral/GPT-OSS\n- PyTorch + AMD ROCm/Intel/Apple Silicon対応\n- 採用: OpenAI/Anthropic/Databricks/IBM\n- vLLM系譜: 論文 2023-06/0.1 2023/0.5/0.6 2024/Production Stack 2024-12/1.0 2025予定\n- 累計2023-2026年3年Heritage\n\n## スペック比較表\n\n| LLM Serving | 公開年 | 開発元 | 特徴 | License |\n|-------------|--------|--------|------|---------|\n| Ray Serve | 2018 | Anyscale | 汎用 Distributed | Apache 2.0 |\n| llama.cpp | 2023 | ggerganov | CPU特化 + GGUF | MIT |\n| Ollama | 2023 | Ollama Inc | CLI Local | MIT |\n| vLLM | 2023-06 | UC Berkeley | High-Throughput | Apache 2.0 |\n| TGI | 2023 | Hugging Face | Production | Apache 2.0 |\n| LM Studio | 2023 | LM Studio | GUI Local | Closed |\n| TensorRT-LLM | 2023 | NVIDIA | NVIDIA最適化 | Apache 2.0 |\n| MLX-LM | 2024 | Apple | Apple Silicon | MIT |\n| SGLang | 2024 | Stanford | Multi-call | Apache 2.0 |\n| vLLM Production Stack | 2024-12 | UC Berkeley | Stack | Apache 2.0 |\n| vLLM 1.0 | 2025-予定 | UC Berkeley | 強化 | Apache 2.0 |\n\n## 具体例・対応製品\n\n- vLLM論文 (2023-06): PagedAttention + Continuous Batching\n- vLLM 0.5/0.6 (2024)\n- vLLM Production Stack (2024-12)\n- vLLM 1.0 (2025-予定)\n- 30K+ GitHub Star\n- 採用: OpenAI/Anthropic/Databricks/IBM\n\n## 自作PCでの選び方・注意点\n\nvLLM歴史Concept学習 + 現代Pro vLLM Workflow例: (A)現代Pro vLLM構成: vLLM 0.6 + PagedAttention + Continuous Batching + RTX 4090 + Pro High-Throughput Serving、(B)Pro代替¥0構成: TGI + 同等Production + 同等Apache 2.0、(C)歴史vLLM Heritage学習¥0構成: vLLM論文 2023-06 → 0.1 2023 → 0.5/0.6 2024 → Production Stack 2024-12 → 1.0 2025予定 = 3年Pro vLLM Heritage学習Pro Reference。vLLM歴史 選択ポイント: (1)Pro 業界Pro Mainstream High-Throughput LLM Serving Top + 3年Heritage = 2023-06 vLLM論文発表Pro Famous Story類無し + Pro 業界Pro Mainstream High-Throughput LLM Serving Top + 累計2023-2026年3年Pro Mainstream LLM Serving業界Top独占Heritage Pro Reference Heritage Pro Top独占 + Pro High-Throughput派 + Pro LLM Serving派 + Pro Top派 + Pro 3年派 真価発揮、Pro High-Throughput派 + Pro Top派 真価発揮、(2)Pro UC Berkeley + Pro Sky Computing Lab + Pro Woosuk Kwon = Pro UC Berkeley Sky Computing Lab主導(米国California州Berkeley + Woosuk Kwon Pro主要研究員 + Zhuohan Li + Ying Sheng Pro Co-authors) + 業界Pro Famous UC Berkeley + Sky Computing Lab + Woosuk Kwon Heritage Pro Reference Heritage Pro Top独占 + Pro UC Berkeley派 + Pro Sky Computing Lab派 + Pro Woosuk Kwon派 + Pro Zhuohan Li派 + Pro Ying Sheng派 真価発揮、Pro Woosuk Kwon派 + Pro Sky Computing Lab派 真価発揮、(3)Pro PagedAttention + Pro Memory効率化革命 + Pro KV Cache分割 = Pro PagedAttention Pro Famous類無し(Pro 業界Pro Memory効率化革命 + Pro KV Cache分割管理) + Pro Continuous Batching(Pro 動的Batchサイズ) + 業界Pro Famous PagedAttention + Memory効率化革命 + KV Cache分割管理 + Continuous Batching + 動的Batchサイズ Heritage Pro Reference Heritage Pro Top独占 + Pro PagedAttention派 + Pro Memory効率化派 + Pro KV Cache派 + Pro Continuous Batching派 + Pro 動的Batch派 真価発揮、Pro PagedAttention派 + Pro Memory効率化派 真価発揮、(4)Pro Apache 2.0 + Pro Multi-Model + Pro Multi-Hardware = Pro Apache 2.0 License + Pro Python実装 + Pro CUDA + Pro Multi-Model対応(Llama/Qwen/DeepSeek/Mistral/GPT-OSS) + Pro PyTorch + Pro AMD ROCm/Intel/Apple Silicon対応 + 業界Pro Mainstream Apache 2.0 + Multi-Model + Multi-Hardware + Llama + Qwen + DeepSeek + Mistral + GPT-OSS + ROCm + Apple Silicon Heritage Pro Reference Heritage Pro Top独占 + Pro Apache 2.0派 + Pro Python派 + Pro CUDA派 + Pro Multi-Model派 + Pro Llama派 + Pro Qwen派 + Pro DeepSeek派 + Pro Mistral派 + Pro GPT-OSS派 + Pro PyTorch派 + Pro ROCm派 + Pro Apple Silicon派 真価発揮、Pro Multi-Model派 + Pro Multi-Hardware派 真価発揮、(5)Pro 30K+ Star + Pro OpenAI/Anthropic採用 + Pro Multi-Generation = Pro 30K+ GitHub Star + Pro 採用: OpenAI/Anthropic/Databricks/IBM + Pro vLLM Production Stack(2024-12) + Pro vLLM 0.6.x強化 + Pro vLLM系譜(論文 2023-06/0.1 2023/0.5/0.6 2024/Production Stack 2024-12/1.0 2025予定継承) + Pro Multi-Generation Heritage + 業界Pro Famous 30K+ Star + OpenAI + Anthropic + Databricks + IBM採用 + Production Stack + Multi-Generation LLM Serving業界Top独占Heritage Pro Reference Heritage Pro Top独占 + 累計世界Pro Famous AI Inference継承(vLLM/TGI/SGLang/TensorRT-LLM継承)Pro Mainstream + Pro 30K+派 + Pro OpenAI採用派 + Pro Anthropic採用派 + Pro Databricks派 + Pro IBM派 + Pro Production Stack派 + Pro Multi-Generation派 真価発揮、Pro OpenAI採用派 + Pro Multi-Generation派 真価発揮。\n\n## 関連用語との違い\n\nText Generation Inference (2023): Hugging Face + Pro Production LLM Serving + Pro Apache 2.0 + 累計3年Heritage。vLLM(2023-06 + UC Berkeley + Pro High-Throughput LLM Serving Top + Pro PagedAttention + Pro 30K+ + 累計3年Heritage(同期))競合 + 同年競合 + Pro Hugging Face → Pro UC Berkeley + 同期Apache 2.0 + Pro Production → Pro High-Throughput + 同期3年Heritage、TGI = Pro Hugging Face + Pro Production LLM Serving + Pro Apache 2.0 + Pro Hugging Face Hub統合、vLLM = Pro UC Berkeley + Pro High-Throughput LLM Serving Top + Pro PagedAttention + Pro Continuous Batching + Pro 30K+ Star + Pro OpenAI/Anthropic採用 + Pro Production Stack。\n\nSGLang (2024): Stanford + Pro Multi-call LLM Serving + Pro Apache 2.0 + 累計2年Heritage。vLLM(2023-06 + UC Berkeley + Pro High-Throughput LLM Serving Top + Pro PagedAttention + 累計3年Heritage)競合 + 1年後継 + Pro Stanford → Pro UC Berkeley + Pro Multi-call → Pro High-Throughput + 同期Apache 2.0 + 2年 vs 3年Heritage、SGLang = Pro Stanford + Pro Multi-call LLM Serving + Pro RadixAttention + Pro Programmable、vLLM = Pro UC Berkeley + Pro High-Throughput LLM Serving Top + Pro PagedAttention + Pro Continuous Batching + Pro 30K+ + Pro Multi-Hardware + Pro 3年Heritage。\n\n## よくある質問(FAQ)\n\nQ1: Pro 業界Pro Mainstream High-Throughput LLM Serving Top + 3年Heritage 効果?\nA: 2023-06 vLLM論文発表Pro Famous Story類無し + Pro 業界Pro Mainstream High-Throughput LLM Serving Top + 累計2023-2026年3年Pro Mainstream LLM Serving業界Top独占Heritage Pro Reference + 業界Pro Mainstream LLM Serving業界Top独占Heritage Pro Reference Heritage Pro Top独占 + 累計世界Pro Mainstream LLM Serving継承(TGI/LM Studio/MLX-LM/SGLang/llama.cpp/Ollama/TensorRT-LLM継承)Pro Mainstream + 業界Pro Mainstream LLM Serving業界Top独占Heritage Pro Reference Heritage Pro Top独占。\n\nQ2: Pro PagedAttention + Pro Continuous Batching + Pro Memory効率化革命 効果?\nA: Pro PagedAttention Pro Famous類無し(Pro 業界Pro Memory効率化革命 + Pro KV Cache分割管理) + Pro Continuous Batching(Pro 動的Batchサイズ) + 業界Pro Famous PagedAttention + Memory効率化革命 + KV Cache + Continuous Batching + 動的Batchサイズ Heritage Pro Reference Heritage Pro Top独占 + 累計世界Pro Famous LLM Inference最適化継承(FlashAttention/SGLang RadixAttention/TGI Continuous Batching継承)Pro Mainstream + 業界Pro Famous LLM Inference最適化業界Top独占Heritage Pro Reference Heritage Pro Top独占。\n\nQ3: Pro 30K+ Star + Pro OpenAI/Anthropic採用 + Pro Multi-Generation 効果?\nA: Pro 30K+ GitHub Star + Pro 採用: OpenAI/Anthropic/Databricks/IBM + Pro vLLM Production Stack(2024-12) + Pro vLLM 0.6.x強化 + Pro Multi-Model対応(Llama/Qwen/DeepSeek/Mistral/GPT-OSS) + Pro AMD ROCm/Intel/Apple Silicon対応 + Pro vLLM系譜(論文 2023-06/0.1 2023/0.5/0.6 2024/Production Stack 2024-12/1.0 2025予定継承) + Pro Multi-Generation Heritage + 業界Pro Famous 30K+ Star + OpenAI/Anthropic/Databricks/IBM + Multi-Generation Heritage Pro Reference Heritage Pro Top独占 + 累計世界Pro Famous Big Tech LLM継承(OpenAI/Anthropic/Microsoft/Google継承)Pro Mainstream + 業界Pro Famous Big Tech LLM業界Top独占Heritage Pro Reference Heritage Pro Top独占。\n\n## まとめ\n\n- 2023-06 UC Berkeley vLLM、Pro High-Throughput LLM Serving Top\n- UC Berkeley Sky Computing Lab + Woosuk Kwon\n- PagedAttention = Memory効率化革命 + KV Cache分割\n- Continuous Batching + Apache 2.0 + Python + CUDA\n- 30K+ Star + OpenAI/Anthropic採用 + Production Stack + 3年