--- title: "ai-gateway vs langchain-serve" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-jina-ai-langchain-serve" tools: ["ferro-labs-ai-gateway", "jina-ai-langchain-serve"] --- # ai-gateway vs langchain-serve *GraphCanon updated Sep 20, 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 langchain-serve if langchain-serve is a tool for deploying Langchain applications in production using Jina and FastAPI, with support for Docker Compose or Kubernetes deployment and secrets management. [ai-gateway](https://docs.ferrolabs.ai) reports 256 GitHub stars, 35 forks, and 68 open issues, last pushed Sep 10, 2026. [langchain-serve](https://cloud.jina.ai) has 1.6k stars, 133 forks, and 15 open issues, last pushed Sep 20, 2023. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [langchain-serve's repository](https://github.com/jina-ai/langchain-serve). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [langchain-serve](/tools/jina-ai-langchain-serve.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | Self-host LLM Apps with Docker Compose or Kubernetes | | Stars | 256 | 1,639 | | Forks | 35 | 133 | | Open issues | 68 | 15 | | 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. | Langchain-serve is a tool for deploying Langchain applications in production using Jina and FastAPI, with support for Docker Compose or Kubernetes deployment and secrets management. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | Apache-2.0 | | Categories | Inference & Serving, Model Training | Developer Tools, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [langchain-serve](/tools/jina-ai-langchain-serve.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 2d | 1094d | | Archived on GitHub | No | Yes | | Open issues (now) | 68 | 15 | | Stars delta | +37 (30d) | -1 (30d) | | Open issues delta | +5 (30d) | 0 (30d) | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/jina-ai-langchain-serve/trust.md) | ## Shared compatibility - **Python**: [ai-gateway](/tools/ferro-labs-ai-gateway.md) - Python runtime; [langchain-serve](/tools/jina-ai-langchain-serve.md) - Python runtime ## 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: langchain-serve - **Pricing:** freemium - Base credits ensure high availability by maintaining at least one instance running continuously, while serving credits are charged when the application is actively serving requests. Pricing is based, - **Requirements:** Min 1 GB RAM; Requires Docker; Requires Docker Compose or Kubernetes for deployment.; Secrets management is supported via `.env` files. - **Adopt for:** Langchain-serve is a tool for deploying Langchain applications in production using Jina and FastAPI, with support for Docker Compose or Kubernetes deployment and secrets management. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; langchain-serve is Python. - 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 langchain-serve if… - langchain-serve is primarily Python; ai-gateway is Go. - Pricing: Base credits ensure high availability by maintaining at least one instance running continuously, while serving credits are charged when the application is actively serving requests. Pricing is based, . - Requirements: Min 1 GB RAM; Requires Docker; Requires Docker Compose or Kubernetes for deployment.; Secrets management is supported via `.env` files.. - Tags unique to langchain-serve: autogpt, autonomous-agents, babyagi, chatbot. - Also covers Developer Tools. - When you need to deploy Langchain applications with Jina and FastAPI on your own infrastructure. ## 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 langchain-serve - If you do not require or prefer not to use Jina and FastAPI for your Langchain applications. - When you do not need or want to manage secrets through a `.env` file during deployment. - If you are not interested in deploying your applications using Docker Compose or Kubernetes. - If you are looking for a fully managed cloud service without the need to manage your own infrastructure. ## Common questions ### What is the difference between ai-gateway and langchain-serve? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. langchain-serve: Self-host LLM Apps with Docker Compose or Kubernetes. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over langchain-serve? Choose ai-gateway over langchain-serve when ai-gateway is primarily Go; langchain-serve is Python; 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 langchain-serve over ai-gateway? Choose langchain-serve over ai-gateway when langchain-serve is primarily Python; ai-gateway is Go; Pricing: Base credits ensure high availability by maintaining at least one instance running continuously, while serving credits are charged when the application is actively serving requests. Pricing is based, ; Requirements: Min 1 GB RAM; Requires Docker; Requires Docker Compose or Kubernetes for deployment.; Secrets management is supported via `.env` files.; Tags unique to langchain-serve: autogpt, autonomous-agents, babyagi, chatbot; Also covers Developer Tools; When you need to deploy Langchain applications with Jina and FastAPI on your own infrastructure. ### 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 langchain-serve? If you do not require or prefer not to use Jina and FastAPI for your Langchain applications. When you do not need or want to manage secrets through a `.env` file during deployment. If you are not interested in deploying your applications using Docker Compose or Kubernetes. If you are looking for a fully managed cloud service without the need to manage your own infrastructure. ### Is ai-gateway or langchain-serve more popular on GitHub? langchain-serve has more GitHub stars (1,639 vs 256). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and langchain-serve open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, langchain-serve: Apache-2.0). ### Where can I find alternatives to ai-gateway or langchain-serve? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [langchain-serve alternatives](/tools/jina-ai-langchain-serve/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [langchain-serve markdown twin](/tools/jina-ai-langchain-serve/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-jina-ai-langchain-serve.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or langchain-serve? ai-gateway: Very active. langchain-serve: Archived. 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 langchain-serve? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [langchain-serve trust report](/tools/jina-ai-langchain-serve/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/_