
根据功能和用途,为你挑选 12 款 Itzam 的替代工具。
| 排名 | 工具和标语 | 官方域名 | 月访问量 | 月度增长 (MoM) | 定价模式 |
|---|
| 主要市场 |
|---|
| 评分 |
|---|
| 比较 |
|---|
| ● | Itzam | itz.am | 0 | 0 (0%) | 免费增值 | 全球 | 4.4 | 概览 |
| 1 | OpenRouter | openrouter.ai | 1994.14万 | -132.65万 (-6.2%) | 付费 | 美国 | 4.8 | 比较 |
| 2 | LLM Gateway | llmgateway.io | 16.84万 | -2.85万 (-14.5%) | 免费增值,定价请咨询 | 韩国 | 4.6 | 比较 |
| 3 | LiteLLM | litellm.ai | 57.7万 | 4.25万 (+7.9%) | 免费增值,定价请咨询 | 美国 | 4.8 | 比较 |
| 4 | APIMaster | apimaster.ai | 21.02万 | 6.65万 (+46.3%) | 付费 | 美国 | 4 | 比较 |
| 5 | Respan | respan.ai | 9.15万 | -1.55万 (-14.5%) | 免费增值 | 美国 | 4.5 | 比较 |
| 6 | OrcaRouter | orcarouter.ai | 97.53万 | -5.38万 (-5.2%) | 免费增值 | 美国 | 4.3 | 比较 |
| 7 | ZenMux | zenmux.ai | 44.44万 | 6.35万 (+16.7%) | 免费增值,付费 | 中国 | 4.4 | 比较 |
| 8 | Merge | merge.dev | 31.32万 | 5355 (+1.7%) | 免费增值,定价请咨询 | 美国 | 4.4 | 比较 |
| 9 | BeatAPI | beatapi.io | 10万 | 9.1万 (+1,012.7%) | 免费增值 | 中国 | 4.2 | 比较 |
| 10 | RouterBase | routerbase.com | 8326 | 2097 (+33.7%) | 付费 | 印度 | 4.3 | 比较 |
| 11 | AI/ML API | aimlapi.com | 23.29万 | -5.87万 (-20.1%) | Pay-as-you-go credits (free to start); enterprise custom pricing on request | 美国 | 4.3 | 比较 |
| 12 | Together AI | together.ai | 164.59万 | 64.77万 (+64.9%) | 免费增值,付费 | 美国 | 4.7 | 比较 |
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.
一个兼容 OpenAI 的 API,接入 200 多个 AI 模型

一个通用 API,接入 500+ AI 模型与 1,000+ 智能体工具

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.