Gpt Load
Self-hosted AI API proxy with load balancing and key rotation.
A well-architected open-source solution for teams wanting to centralize AI API access. It simplifies key management and improves reliability, but requires self-hosting and some DevOps know-how. If you need a managed service, look elsewhere.
- Developers building applications that call multiple AI APIs
- Teams managing multiple API keys and quotas across providers
- Enterprises needing a self-hosted AI gateway with failover
- Organizations requiring real-time monitoring of AI API usage
- Users looking for a fully managed cloud AI gateway
- Non-technical users who cannot deploy Docker containers
- Those needing built-in model fine-tuning or training features
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In short
Gpt Load — Self-hosted AI API proxy with load balancing and key rotation. Best for Developers building applications that call multiple AI APIs, Teams managing multiple API keys and quotas across providers, Enterprises needing a self-hosted AI gateway with failover. Free to use.
Viability Score
How likely is Gpt Load to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Multi-channel AI proxy for OpenAI, Gemini, Claude and more
- Intelligent key rotation to prevent rate limiting
- Load balancing across multiple AI providers and keys
- Transparent proxy compatible with OpenAI API format
- Vue 3 management dashboard for monitoring
- Real-time request logging and statistics
- Redis-based caching and distributed locking
- MySQL 8.2+ permanent storage for configs and logs
- Docker Compose one-click deployment
- Cluster mode with master/slave architecture
- Configurable channel types: weighted, fallback, etc.
- Bearer token authentication with custom secret key
- Open-source (MIT license)
- Supports Go 1.23+ backend
- Telegram community support
About Gpt Load
GPT-Load is an open-source, enterprise-grade AI API proxy built with Go 1.23+. It acts as a transparent proxy between your applications and multiple AI service providers like OpenAI, Google Gemini, and Anthropic Claude. The core functionality is intelligent key rotation and load balancing: it manages multiple API keys across different providers, automatically rotates keys to avoid rate limits, and distributes requests evenly for high availability. Designed for developers and teams who need to scale AI integrations without worrying about API key management or provider downtime. It features a three-layer architecture: data storage with MySQL 8.2+, caching with Redis, and a Vue 3 management dashboard for monitoring and configuration. Key differentiators include support for multiple channel types (weighted, fallback, etc.), real-time request logging, and cluster deployment capability. Deployment is simple via Docker Compose, supporting both single-node and master/slave cluster setups. The project is MIT licensed and actively maintained on GitHub. Unlike cloud-managed gateways, GPT-Load gives you full control over your infrastructure and data, but requires self-hosting and DevOps knowledge.
Behind the Verdict
GPT-Load is a solid choice if you need to centralize multiple AI API keys and providers under one roof, especially for production workloads. The intelligent key rotation is a standout feature—it handles rate limiting automatically, which is a pain point for many developers. The Vue 3 dashboard gives decent visibility into usage and logs. We'd reach for this when running a service that calls OpenAI, Gemini, and Claude from different endpoints and we want a single entry point. However, it's not plug-and-play. You need Docker, MySQL, and Redis running, and you'll have to manage upgrades and scaling yourself. Compared to a cloud proxy like Azure API Management or AWS API Gateway, GPT-Load offers more AI-specific features (key rotation, provider-specific fallback) but lacks managed SLAs. For pure simplicity, a single-provider SDK might suffice. Where it bites: no built-in fine-tuning, no chat UI, and the documentation is currently only in Chinese. In practice, the project is active on GitHub, but community support is limited to a Telegram group. Best for teams comfortable with self-hosting and who need a cost-effective, customizable gateway.
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Use Cases
- Route all AI API calls through a single endpoint with automatic key rotation.
- Balance traffic across multiple OpenAI and Gemini keys to avoid rate limits.
- Monitor real-time API usage and request logs from a web dashboard.
- Deploy a high-availability AI gateway using cluster mode with master/slave replication.
- Centralize AI provider configuration and change keys without redeploying applications.
Limitations
- Self-hosted only, requiring Docker and database management.
- No built-in support for non-OpenAI-compatible APIs (must be adapted).
- Free-tier keys might have rate limits depending on upstream providers; advanced features like cluster mode need additional infrastructure.
12-month cost
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Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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