Together AI VS Polygres
Together AI VS Polygres 对比，Together AI 和 Polygres 有什麼區別？
猜你喜歡
總結
Together AI 總結
Together AI 著陸頁
Polygres 總結
Polygres turns Postgres into working memory for AI agents. Retrieve structured rows, connected relationships, semantic matches, and full-text results through one hybrid API. All without a separate vector store, graph database, or sync pipeline. Build grounded agents over the data you already have, with relational, graph, and vector context joined at the source. Use the managed cloud or self-host with our open source components. Polygres is currently free to use, just sign up!
Polygres 著陸頁
比較詳情
Together AI 詳細信息
| 類別 | AI 開發者工具, AI API, AI模型, 開源AI模型, 大型語言模型 LLMs |
| Together AI 網站 | https://www.together.ai?utm_source=toolify |
| 添加時間 | 2025年6月22日 |
| Together AI 定價 | -- |
Polygres 詳細信息
| 類別 | AI 開發者工具, AI 代理, AI 知識圖譜, AI API, AI搜尋引擎 |
| Polygres 網站 | https://polygres.com?utm_source=toolify |
| 添加時間 | 2026年8月26日 |
| Polygres 定價 | -- |
使用對比
如何使用Together AI？
Users can interact with Together AI through easy-to-use APIs for serverless inference or deploy models on custom hardware via dedicated endpoints. Fine-tuning is available through simple commands or by controlling hyperparameters via API. GPU clusters can be requested for large-scale training. The platform also offers a web UI, API, or CLI to start or stop endpoints and manage services. Code execution environments are available for building and running AI development tasks.
如何使用Polygres？
Create a Polygres managed instance or install the open-source components on an existing PostgreSQL database. Connect your schema and use the SDK or retrieval API to submit a natural-language query with options such as graph traversal depth, filters, and token limits. Polygres combines relational, graph, vector, and text results into one ranked, token-ready context block that can be passed directly to an AI agent.
比較 Together AI 和 Polygres 的優點
Together AI 的核心功能
- Serverless Inference API for open-source models
- Dedicated Endpoints for custom hardware deployment
- Fine-Tuning (LoRA and full fine-tuning)
- Together Chat app for open-source AI
- Code Sandbox for AI development environments
- Code Interpreter for executing LLM-generated code
- GPU Clusters (Instant and Reserved) with NVIDIA GPUs (GB200, B200, H200, H100, A100)
- Extensive Model Library (200+ generative AI models)
- OpenAI-compatible APIs
- Accelerated Software Stack (e.g., FlashAttention-3, custom CUDA kernels)
- High-Speed Interconnects (InfiniBand, NVLink)
- Robust Management Tools (Slurm, Kubernetes)
Polygres 的核心功能
- Unified relational, graph, vector, and full-text retrieval
- Native graph traversal over existing PostgreSQL foreign keys
- Fused hybrid search with dense HNSW, sparse, filtered, and semantic retrieval
- Token-ready context assembly for grounded AI agents
- Shortest-path, neighborhood, relationship, and multi-hop graph queries
- Managed cloud hosting and open-source self-hosting
- PostgreSQL-native data retrieval without a separate vector store or sync pipeline
比較用例
Together AI 的用例
- Accelerating AI model training and inference for enterprises (e.g., Salesforce, Zoom, InVideo)
- Building AI customer support bots that scale to high message volumes (e.g., Zomato)
- Developing production-grade AI applications by unlocking data for developers and businesses
- Creating next-generation text-to-video models (e.g., Pika)
- Building cybersecurity models (e.g., Nexusflow)
- Achieving simpler operations, improved latency, and greater cost-efficiency for AI models (e.g., Arcee AI)
- Developing custom generative AI models from scratch
- Performing multi-document analysis, codebase reasoning, and personalized tasks
- Managing complex tool-based interactions and API function calls
- Generating and debugging code with advanced LLMs
- Executing visual tasks with advanced visual reasoning and video understanding
- Data tasks such as classification and structured data extraction
Polygres 的用例
- Build grounded AI agents that retrieve customer records, orders, tickets, and related history
- Investigate failed transactions by combining semantic search with order, payment, and dispute relationships
- Create user-memory systems that retrieve relevant past interactions and connected data
- Query Wikipedia-scale datasets using hybrid indexes and graph relationships
- Provide support agents with ranked, database-backed context
- Develop recommendation and discovery systems using existing PostgreSQL data
Together AI 和 Polygres 之間的計劃不同
Together AI
Varies by model and token count
Prices are per 1 million tokens (input and output for Chat, Multimodal, Language, Code; input only for Embedding; image size/steps for Image models). Batch inference is available at an introductory 50% discount. Specific model prices range from $0.06 to $7.00 per 1M tokens depending on model size and type.
Varies by GPU type, per minute/hour
Deploy models on customizable GPU endpoints with per-minute billing. Supports various NVIDIA GPUs like RTX-6000, L40, A100, H100, H200. Prices range from $0.025/minute ($1.49/hour) for RTX-6000/L40 to $0.083/minute ($4.99/hour) for H200.
Per 1M Tokens processed
Pricing is based on model size, dataset size, and number of epochs. Supervised Fine-tuning (LoRA) ranges from $0.48 to $2.90 per 1M tokens. Full Fine-tuning ranges from $0.54 to $3.20 per 1M tokens. DPO (LoRA) ranges from $1.20 to $7.25 per 1M tokens. DPO (Full FT) ranges from $1.35 to $8.00 per 1M tokens.
Starting at $1.30/hour
State-of-the-art clusters with NVIDIA Blackwell and Hopper GPUs (H200, H100, A100) for optimal AI training and inference. H200 starts at $2.09/hr, H100 at $1.75/hr, A100 at $1.30/hr. GB200 and B200 pricing requires contact.
Per hour or per session
Together Code Sandbox is priced per vCPU ($0.0446/hour) and per GiB RAM ($0.0149/hour). Together Code Interpreter is priced per session ($0.03 for 60 minutes).
Polygres
$0 / forever
Open-source pgGraph and pgVector, runnable on any PostgreSQL instance, with community support.
$16 / month
Managed cloud database hosting with email and community Discord support. Currently free for now.
$256 / month minimum usage
Automated vertical and horizontal scaling, email and community Discord support, private Discord or Slack channel, and support hours from 8:00 AM to 5:00 PM.
$4,096 / month minimum usage
Coming soon. Includes dedicated database infrastructure, custom compliance, high availability, 24/7 support, and dedicated support and uptime SLAs.
Together AI 的流量
Together AI 是月访问量為 838.4K 且平均訪問時長為 00:01:57 的工具。 Together AI 的每次訪問頁數為 3.15，跳出率為 42.30%。
最新網站流量
| 月訪問量 | 838.4K |
| 平均訪問時長 | 00:01:57 |
| 每次訪問頁數 | 3.15 |
| 跳出率 | 42.30% |
Polygres 的流量
Polygres 是月访问量為 11.6K 且平均訪問時長為 00:00:12 的工具。 Polygres 的每次訪問頁數為 1.40，跳出率為 92.09%。
最新網站流量
| 月訪問量 | 11.6K |
| 平均訪問時長 | 00:00:12 |
| 每次訪問頁數 | 1.40 |
| 跳出率 | 92.09% |
地理流量
The top 5 countries/regions for Together AI are:United States 28.99%, India 10.64%, Pakistan 6.88%, Thailand 3.39%, China 2.11%
Top 5 Countries/regions
 | 28.99% |
 | 10.64% |
 | 6.88% |
 | 3.39% |
 | 2.11% |
地理流量
The top 1 countries/regions for Polygres are:United States 100.00%
Top 1 Countries/regions
| 100.00% |
網站流量來源
Together AI 的 6 個主要流量來源是：直接 39.42%, vs_sourcesSearchOrganic 33.83%, 引薦 10.70%, vs_sourcesSearchPaid 7.11%, vs_sourcesSocialOrganic 4.46%, vs_sourcesGenAi 3.15%, 郵件 0.79%, vs_sourcesSocialPaid 0.31%, vs_sourcesDisplayAds 0.22%, vs_sourcesAffiliate 0.00%
直接 | 39.42% |
vs_sourcesSearchOrganic | 33.83% |
引薦 | 10.70% |
vs_sourcesSearchPaid | 7.11% |
vs_sourcesSocialOrganic | 4.46% |
vs_sourcesGenAi | 3.15% |
郵件 | 0.79% |
vs_sourcesSocialPaid | 0.31% |
vs_sourcesDisplayAds | 0.22% |
vs_sourcesAffiliate | 0.00% |
網站流量來源
Polygres 的 6 個主要流量來源是：直接 57.14%, vs_sourcesSocialOrganic 21.37%, vs_sourcesSearchOrganic 13.47%, 引薦 5.27%, 郵件 2.75%, vs_sourcesGenAi 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
直接 | 57.14% |
vs_sourcesSocialOrganic | 21.37% |
vs_sourcesSearchOrganic | 13.47% |
引薦 | 5.27% |
郵件 | 2.75% |
vs_sourcesGenAi | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesDisplayAds | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Together AI 或 Polygres哪個更好？
Together AI 可能比 Polygres 更受歡迎。如您所見，Together AI 每月有 838.4K 次訪問，而 Polygres 每月有 11.6K 次訪問。 所以更多的人選擇Together AI。 因此，人們很可能會在社交平台上更多地推薦 Together AI。
Together AI 的平均訪問持續時間為 00:01:57，而 Polygres 的平均訪問持續時間為 00:00:12。 此外，Together AI 的每次訪問頁面為 3.15，跳出率為 42.30%。 Polygres 的每次訪問頁面為 1.40，跳出率為 92.09%。
Together AI 的主要用戶是United States, India, Pakistan, Thailand, China，分佈如下：28.99%, 10.64%, 6.88%, 3.39%, 2.11%。
Polygres 的主要用戶是 United States，分佈如下：100.00%。
查看其他对比
精選*
