--- title: "ai-gateway vs inference" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-xorbitsai-inference" tools: ["ferro-labs-ai-gateway", "xorbitsai-inference"] --- # ai-gateway vs inference *GraphCanon updated Aug 9, 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 inference if unified production-ready inference API that supports a wide range of models and deployment methods. [ai-gateway](https://docs.ferrolabs.ai) reports 219 GitHub stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. [inference](https://inference.readthedocs.io) has 9.5k stars, 851 forks, and 42 open issues, last pushed Aug 2, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [inference's repository](https://github.com/xorbitsai/inference). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [inference](/tools/xorbitsai-inference.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | Unified production-ready inference API for various models | | Stars | 219 | 9,470 | | Forks | 33 | 851 | | Open issues | 63 | 42 | | 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. | Unified production-ready inference API that supports a wide range of models and deployment methods. | | 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) | [inference](/tools/xorbitsai-inference.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 63 | 42 | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/xorbitsai-inference/trust.md) | ## 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: inference - **Pricing:** freemium - Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity. - **Requirements:** Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup. - **Adopt for:** Unified production-ready inference API that supports a wide range of models and deployment methods. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; inference 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 inference if… - inference is primarily Python; ai-gateway is Go. - Pricing: Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity.. - Requirements: Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup.. - Tags unique to inference: artificial-intelligence, deployment, machine-learning. - - When you need to deploy multiple types of models (like speech, text, and multimodal) through a single unified interface. ## 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 inference - - When strict control over individual model interfaces is required and a unified API complicates your workflow. - - If you’re working with proprietary models that aren’t supported by Xinference’s built-in or custom integration mechanisms. - - In cases where the project mandates use of specific deployment tools that are not well-aligned with Xinference’s recommended methods (e.g., Docker, Kubernetes), unless you can adapt your setup. ## Common questions ### What is the difference between ai-gateway and inference? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. inference: Unified production-ready inference API for various models. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over inference? Choose ai-gateway over inference when ai-gateway is primarily Go; inference 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 inference over ai-gateway? Choose inference over ai-gateway when inference is primarily Python; ai-gateway is Go; Pricing: Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity.; Requirements: Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup.; Tags unique to inference: artificial-intelligence, deployment, machine-learning; - When you need to deploy multiple types of models (like speech, text, and multimodal) through a single unified interface. ### 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 inference? - When strict control over individual model interfaces is required and a unified API complicates your workflow. - If you’re working with proprietary models that aren’t supported by Xinference’s built-in or custom integration mechanisms. - In cases where the project mandates use of specific deployment tools that are not well-aligned with Xinference’s recommended methods (e.g., Docker, Kubernetes), unless you can adapt your setup. ### Is ai-gateway or inference more popular on GitHub? inference has more GitHub stars (9,470 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and inference open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, inference: Apache-2.0). ### Where can I find alternatives to ai-gateway or inference? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [inference alternatives](/tools/xorbitsai-inference/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [inference markdown twin](/tools/xorbitsai-inference/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-xorbitsai-inference.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or inference? ai-gateway: Very active. inference: 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 inference? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [inference trust report](/tools/xorbitsai-inference/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/_