
依功能與用途,為你挑選 12 款 Itzam 的替代工具。
| 排名 | 工具與標語 | 官方網域 | 每月造訪次數 | 月增幅 | 定價模式 | 主要市場 |
|---|
| 評分 |
|---|
| 比較 |
|---|
| ● | Itzam | itz.am | 0 | 0 (0%) | 免費增值 | 全球 | 4.4 | 簡介 |
| 1 | OpenRouter | openrouter.ai | 1994.14萬 | -132.65萬 (-6.2%) | 付費 | 美國 | 4.8 | 比較 |
| 2 | LLM Gateway | llmgateway.io | 16.84萬 | -2.85萬 (-14.5%) | 免費增值、需聯絡報價 | 南韓 | 4.6 | 比較 |
| 3 | LiteLLM | litellm.ai | 57.7萬 | 4.25萬 (+7.9%) | 免費增值、需聯絡報價 | 美國 | 4.8 | 比較 |
| 4 | APIMaster | apimaster.ai | 21.02萬 | 6.65萬 (+46.3%) | 付費 | 美國 | 4 | 比較 |
| 5 | Respan | respan.ai | 9.15萬 | -1.55萬 (-14.5%) | 免費增值 | 美國 | 4.5 | 比較 |
| 6 | OrcaRouter | orcarouter.ai | 97.53萬 | -5.38萬 (-5.2%) | 免費增值 | 美國 | 4.3 | 比較 |
| 7 | ZenMux | zenmux.ai | 44.44萬 | 6.35萬 (+16.7%) | 免費增值、付費 | 中國 | 4.4 | 比較 |
| 8 | Merge | merge.dev | 31.32萬 | 5355 (+1.7%) | 免費增值、需聯絡報價 | 美國 | 4.4 | 比較 |
| 9 | BeatAPI | beatapi.io | 10萬 | 9.1萬 (+1,012.7%) | 免費增值 | 中國 | 4.2 | 比較 |
| 10 | RouterBase | routerbase.com | 8326 | 2097 (+33.7%) | 付費 | 印度 | 4.3 | 比較 |
| 11 | AI/ML API | aimlapi.com | 23.29萬 | -5.87萬 (-20.1%) | Pay-as-you-go credits (free to start); enterprise custom pricing on request | 美國 | 4.3 | 比較 |
| 12 | Together AI | together.ai | 164.59萬 | 64.77萬 (+64.9%) | 免費增值、付費 | 美國 | 4.7 | 比較 |
OrcaRouter is an OpenAI-compatible AI gateway that grades every prompt and routes it to the best-value model, then layers on failover, guardrails, an agent firewall, and compliance tooling for production AI.
OrcaRouter is an OpenAI-compatible AI gateway that grades every prompt and routes it to the best-value model, then layers on failover, guardrails, an agent firewall, and compliance tooling for production AI.
一個相容 OpenAI 的 API,接入 200 多個 AI 模型

一個通用 API,串接 500+ AI 模型與 1,000+ 代理工具

Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.