--- title: "ai-gateway vs private-gpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-zylon-ai-private-gpt" tools: ["ferro-labs-ai-gateway", "zylon-ai-private-gpt"] --- # ai-gateway vs private-gpt *GraphCanon updated Jul 17, 2026* ## Verdict Pick ai-gateway if ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment; pick private-gpt if privateGPT provides a comprehensive API layer to build private, on-premise AI applications leveraging local OpenAI-compatible inference servers. It offers features such as RAG, skills, tools. [ai-gateway](https://docs.ferrolabs.ai) reports 180 GitHub stars, 31 forks, and 47 open issues, last pushed Jul 14, 2026. [private-gpt](https://www.zylon.ai/private-gpt) has 57k stars, 7.6k forks, and 7 open issues, last pushed Jul 14, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [private-gpt's repository](https://github.com/zylon-ai/private-gpt). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [private-gpt](/tools/zylon-ai-private-gpt.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | Complete API layer for private AI applications on local models | | Stars | 180 | 57,328 | | Forks | 31 | 7,597 | | Open issues | 47 | 7 | | Language | Go | Python | | Adopt for | ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. | PrivateGPT provides a comprehensive API layer to build private, on-premise AI applications leveraging local OpenAI-compatible inference servers. It offers features such as RAG, skills, tools, text-to-SQL functionalities, | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | Apache-2.0 | | Categories | Inference & Serving, Model Training | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [private-gpt](/tools/zylon-ai-private-gpt.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 47 | 7 | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/zylon-ai-private-gpt/trust.md) | **Typed relationship:** ai-gateway _(alternative)_ private-gpt PrivateGPT and ai-gateway both function as API layers to manage multiple LLMs with integrated features, making them alternative tools for similar purposes. ## Decision facts: ai-gateway - **Adopt for:** ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. - **License detail:** Apache-2.0 - a permissive free software license ## Decision facts: private-gpt - **Requirements:** Min 8 GB RAM; Requires Docker - **Adopt for:** PrivateGPT provides a comprehensive API layer to build private, on-premise AI applications leveraging local OpenAI-compatible inference servers. It offers features such as RAG, skills, tools, text-to-SQL functionalities, ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; private-gpt is Python. - PrivateGPT and ai-gateway both function as API layers to manage multiple LLMs with integrated features, making them alternative tools for similar purposes. - Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy. - Also covers Model Training. - When you need to integrate more than 30 different LLM services including OpenAI and Anthropic ### Choose private-gpt if… - private-gpt is primarily Python; ai-gateway is Go. - Requirements: Min 8 GB RAM; Requires Docker. - PrivateGPT and ai-gateway both function as API layers to manage multiple LLMs with integrated features, making them alternative tools for similar purposes. - Tags unique to private-gpt: ai, ai-tools, local-models, mcp. - - You need to deploy and operationalize your own locally-run models without relying on cloud APIs. ## When NOT to use ai-gateway - If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features - For small-scale projects that do not require comprehensive cost analysis tools - When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ## When NOT to use private-gpt - - You prefer simplicity and ease-of-use over full control; PrivateGPT requires more setup than using direct cloud-based AI services. - - Your project does not involve running models locally but strictly relies on public cloud resources for inference server operations. - - You do not have the technical capability to run an OpenAI-compatible inference server or manage local infrastructure effectively. ## Common questions ### What is the difference between ai-gateway and private-gpt? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. private-gpt: Complete API layer for private AI applications on local models. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over private-gpt? Choose ai-gateway over private-gpt when ai-gateway is primarily Go; private-gpt is Python; PrivateGPT and ai-gateway both function as API layers to manage multiple LLMs with integrated features, making them alternative tools for similar purposes; Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy; Also covers Model Training; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic. ### When should I choose private-gpt over ai-gateway? Choose private-gpt over ai-gateway when private-gpt is primarily Python; ai-gateway is Go; Requirements: Min 8 GB RAM; Requires Docker; PrivateGPT and ai-gateway both function as API layers to manage multiple LLMs with integrated features, making them alternative tools for similar purposes; Tags unique to private-gpt: ai, ai-tools, local-models, mcp; - You need to deploy and operationalize your own locally-run models without relying on cloud APIs. ### When should I avoid ai-gateway? If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features For small-scale projects that do not require comprehensive cost analysis tools When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ### When should I avoid private-gpt? - You prefer simplicity and ease-of-use over full control; PrivateGPT requires more setup than using direct cloud-based AI services. - Your project does not involve running models locally but strictly relies on public cloud resources for inference server operations. - You do not have the technical capability to run an OpenAI-compatible inference server or manage local infrastructure effectively. ### Is ai-gateway or private-gpt more popular on GitHub? private-gpt has more GitHub stars (57,328 vs 180). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and private-gpt open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, private-gpt: Apache-2.0). ### Where can I find alternatives to ai-gateway or private-gpt? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [private-gpt alternatives](/tools/zylon-ai-private-gpt/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [private-gpt markdown twin](/tools/zylon-ai-private-gpt/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/ferro-labs-ai-gateway-vs-zylon-ai-private-gpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or private-gpt? ai-gateway: Very active. private-gpt: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for ai-gateway and private-gpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [private-gpt trust report](/tools/zylon-ai-private-gpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ferro-labs-ai-gateway`](/api/graphcanon/graph?tool=ferro-labs-ai-gateway) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_