quantumnous/new-api

A unified AI model hub for aggregation & distribution. It supports cross-converting various LLMs into OpenAI-compatible, Claude-compatible, or...

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Summary Information

Updated 6 seconds ago
Added to GitGenius on August 31st, 2026
Created on November 10th, 2023
Open Issues & Pull Requests: 1,298 (+0)
Number of forks: 11,167
Total Stargazers: 46,911 (+0)
Total Subscribers: 151 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.2 hours
Mean response time: 18.0 days
90th percentile: 25.0 days
Tracked items: 2,187

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "missing reproduction steps" is answered fastest, typically in under an hour, while "channel" waits about 10 days. 43% of tracked open issues have had no activity in three months. Only 10% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 635
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 154 days
Stale 30+ days: 553
Stale 90+ days: 275

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (1,511)
  • enhancement (874)
  • invalid (493)
  • stale (356)
  • needs reproduction / insufficient info (124)
  • duplicate (89)
  • missing reproduction steps (50)
  • channel (42)

Detailed Description

New API is an AI gateway and model management system that unifies access to multiple large language models through format conversion and centralized distribution.

The tool solves the problem of managing diverse AI model APIs by providing a single gateway that converts various LLMs into OpenAI-compatible, Claude-compatible, or Gemini-compatible formats. This approach allows organizations to abstract away differences between upstream providers, enabling applications to work with multiple models through standardized interfaces. The system functions as a centralized hub for aggregating different model services and distributing them to clients, while also providing organization-level authentication, usage analytics, and cost accounting capabilities.

Organizations should adopt this tool if they need to manage multiple AI model subscriptions across different providers, want to standardize API interactions across their applications, or require centralized governance and billing for AI services. It suits enterprise deployments and personal use cases where consolidating access to models like OpenAI, Claude, Deepseek, and Gemini behind a single gateway reduces integration complexity. The tool is designed for private deployment scenarios where users maintain control over their infrastructure and API keys.

The project maintains active development with regular updates and Docker deployment support. The codebase is written in Go, suggesting a focus on performance and efficient resource usage for gateway operations. The tool includes comprehensive documentation available in multiple languages, indicating attention to accessibility for international users. The project emphasizes lawful use and compliance, with explicit guidance that users must obtain upstream API keys legitimately and comply with applicable terms of service and regulations.