DeepSeek公式
3.7億/月
DeepSeek-V4 と R1 を中核とし、極めて低いトークンコストで提供される高効率なオープンウェイト／ホスト型推論 AI。
Large Language Models (LLMs)編集部スコア：4.8フリーミアム+4.3%
フリーミアム
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掲載製品 20,346 件·アクセス動向とツール探索
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459 種類のワークフローで、アクセス推計・機能・代替製品を比較できます。
459 種類のワークフローで、アクセス推計・機能・代替製品を比較できます。
“pgvector” · コーディング・開発·141 件
最初からDeepSeek-V4 と R1 を中核とし、極めて低いトークンコストで提供される高効率なオープンウェイト／ホスト型推論 AI。
Semantic Scholar is a free, non-commercial academic search engine built by the Allen Institute for AI (Ai2). It indexes more than 240 million papers from every field of science and uses machine learning to extract meaning from abstracts, citations, figures and tables, so researchers find relevant work faster than with keyword-only search.
Semantic Scholar is a free, non-commercial academic search engine built by the Allen Institute for AI (Ai2). It indexes more than 240 million papers from every field of science and uses machine learning to extract meaning from abstracts, citations, figures and tables, so researchers find relevant work faster than with keyword-only search.
Pinecone is a managed vector database and AI knowledge platform for building retrieval-augmented generation (RAG), semantic search, and agent memory. It stores vector embeddings at scale, makes writes searchable within seconds with no index tuning, and keeps p99 latency steady as data grows. Pinecone powers products for more than 10,000 customers and over a million developers worldwide.
Pinecone is a managed vector database and AI knowledge platform for building retrieval-augmented generation (RAG), semantic search, and agent memory. It stores vector embeddings at scale, makes writes searchable within seconds with no index tuning, and keeps p99 latency steady as data grows. Pinecone powers products for more than 10,000 customers and over a million developers worldwide.
Zilliz is the company behind Milvus, the open-source vector database, and offers Zilliz Cloud — a fully managed vector database service built for large-scale AI retrieval, RAG, and similarity search workloads.
Qdrant is an open-source vector search engine and database, written in Rust, for high-performance similarity search in AI applications.
50以上のストックライブラリを1回で検索、AIランク付けと価格比較
オープンウェイトLLMのVRAM・スループット・GPUコスト計算機と講座プラットフォーム
オープンウェイトLLMのVRAM・スループット・GPUコスト計算機と講座プラットフォーム
SvectorDB is a natively serverless vector database designed around AWS. It offers pay-per-request pricing, hybrid key-value filtering, built-in text and image vectorizers, and CloudFormation support, making it cheap and simple to add semantic search or recommendations to an existing cloud stack.
SvectorDB is a natively serverless vector database designed around AWS. It offers pay-per-request pricing, hybrid key-value filtering, built-in text and image vectorizers, and CloudFormation support, making it cheap and simple to add semantic search or recommendations to an existing cloud stack.
大規模データ収集のためのグローバル住宅・モバイル・ISPプロキシ
Tinybird is a data platform that pairs managed ClickHouse® with a hosted API, ingestion and MCP layer so engineering teams can build and ship real-time analytics products without operating database clusters themselves. It combines sub-second SQL querying, streaming and batch ingestion connectors, branching workflows and AI-agent tooling in one workflow.
Tinybird is a data platform that pairs managed ClickHouse® with a hosted API, ingestion and MCP layer so engineering teams can build and ship real-time analytics products without operating database clusters themselves. It combines sub-second SQL querying, streaming and batch ingestion connectors, branching workflows and AI-agent tooling in one workflow.
Voxel51 is the data platform for physical AI, built on the open-source FiftyOne library. It helps computer vision and robotics teams search, visualize, curate, annotate, and evaluate multimodal datasets — images, video, 3D scenes, and sensor streams — so they can find where models fail and fix the data behind them.
Voxel51 is the data platform for physical AI, built on the open-source FiftyOne library. It helps computer vision and robotics teams search, visualize, curate, annotate, and evaluate multimodal datasets — images, video, 3D scenes, and sensor streams — so they can find where models fail and fix the data behind them.
