--- title: "ai-gateway vs infinity" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-michaelfeil-infinity" tools: ["ferro-labs-ai-gateway", "michaelfeil-infinity"] --- # ai-gateway vs infinity *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 infinity if infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT. [ai-gateway](https://docs.ferrolabs.ai) reports 219 GitHub stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. [infinity](https://michaelfeil.github.io/infinity/) has 2.9k stars, 196 forks, and 130 open issues, last pushed Mar 24, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [infinity's repository](https://github.com/michaelfeil/infinity). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [infinity](/tools/michaelfeil-infinity.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | High-throughput, low-latency serving engine for text-embeddings and various models | | Stars | 219 | 2,907 | | Forks | 33 | 196 | | Open issues | 63 | 130 | | 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. | Infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | MIT | | 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) | [infinity](/tools/michaelfeil-infinity.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 2d | 136d | | Open issues (now) | 63 | 130 | | Owner type | Organization | User | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/michaelfeil-infinity/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: infinity - **Adopt for:** Infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; infinity is Python. - License: ai-gateway is Apache-2.0, infinity is MIT. - 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 infinity if… - infinity is primarily Python; ai-gateway is Go. - License: infinity is MIT, ai-gateway is Apache-2.0. - Tags unique to infinity: clap, clip, colpali, docker-container. - When you need to serve embeddings and various models with high throughput and low latency. ## 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 infinity - Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity. - Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking). ## Common questions ### What is the difference between ai-gateway and infinity? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. infinity: High-throughput, low-latency serving engine for text-embeddings and various models. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over infinity? Choose ai-gateway over infinity when ai-gateway is primarily Go; infinity is Python; License: ai-gateway is Apache-2.0, infinity is MIT; 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 infinity over ai-gateway? Choose infinity over ai-gateway when infinity is primarily Python; ai-gateway is Go; License: infinity is MIT, ai-gateway is Apache-2.0; Tags unique to infinity: clap, clip, colpali, docker-container; When you need to serve embeddings and various models with high throughput and low latency. ### 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 infinity? Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity. Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking). ### Is ai-gateway or infinity more popular on GitHub? infinity has more GitHub stars (2,907 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and infinity open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, infinity: MIT). ### Where can I find alternatives to ai-gateway or infinity? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [infinity alternatives](/tools/michaelfeil-infinity/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [infinity markdown twin](/tools/michaelfeil-infinity/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-michaelfeil-infinity.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or infinity? ai-gateway: Very active. infinity: Slowing. 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 infinity? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [infinity trust report](/tools/michaelfeil-infinity/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/_