--- title: "ai-gateway vs ggrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-raketenkater-ggrun" tools: ["ferro-labs-ai-gateway", "raketenkater-ggrun"] --- # ai-gateway vs ggrun *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 ggrun if ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. [ai-gateway](https://docs.ferrolabs.ai) reports 256 GitHub stars, 35 forks, and 68 open issues, last pushed Sep 10, 2026. [ggrun](https://github.com/raketenkater/ggrun) has 275 stars, 18 forks, and 4 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [ggrun's repository](https://github.com/raketenkater/ggrun). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | Auto-tuned launcher for GGUF models on llama.cpp with OpenAI-compatible server | | Stars | 256 | 275 | | Forks | 35 | 18 | | Open issues | 68 | 4 | | Language | Go | Go | | 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. | ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | MIT License allows using ggrun freely in both open source and commercial projects, with conditions that the copyright notice and permission notice are preserved. | | 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) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 68 | 4 | | Stars delta | +37 (30d) | +11 (30d) | | Open issues delta | +5 (30d) | +3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/raketenkater-ggrun/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: ggrun - **Pricing:** freemium - Free to use under MIT license; no direct costs involved in usage. - **Adopt for:** ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. - **License detail:** MIT License allows using ggrun freely in both open source and commercial projects, with conditions that the copyright notice and permission notice are preserved. ## Choose when ### Choose ai-gateway if… - License: ai-gateway is Apache-2.0, ggrun 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 ggrun if… - License: ggrun is MIT, ai-gateway is Apache-2.0. - Pricing: Free to use under MIT license; no direct costs involved in usage.. - Tags unique to ggrun: cuda, gguf, golang, inference-server. - When developing systems that require automatic hardware optimization and tuning for GGUF models on multiple GPUs ## 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 ggrun - For environments where single-GPU setups are preferred, as ggrun specializes in multi-GPU configurations and may offer limited advantage or additional complexity - When you do not require auto-tuning capabilities for hardware performance optimization since this feature is specific to ggrun ## Common questions ### What is the difference between ai-gateway and ggrun? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. ggrun: Auto-tuned launcher for GGUF models on llama.cpp with OpenAI-compatible server. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over ggrun? Choose ai-gateway over ggrun when License: ai-gateway is Apache-2.0, ggrun 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 ggrun over ai-gateway? Choose ggrun over ai-gateway when License: ggrun is MIT, ai-gateway is Apache-2.0; Pricing: Free to use under MIT license; no direct costs involved in usage.; Tags unique to ggrun: cuda, gguf, golang, inference-server; When developing systems that require automatic hardware optimization and tuning for GGUF models on multiple GPUs. ### 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 ggrun? For environments where single-GPU setups are preferred, as ggrun specializes in multi-GPU configurations and may offer limited advantage or additional complexity When you do not require auto-tuning capabilities for hardware performance optimization since this feature is specific to ggrun ### Is ai-gateway or ggrun more popular on GitHub? ggrun has more GitHub stars (275 vs 256). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and ggrun open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, ggrun: MIT). ### Where can I find alternatives to ai-gateway or ggrun? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [ggrun alternatives](/tools/raketenkater-ggrun/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [ggrun markdown twin](/tools/raketenkater-ggrun/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-raketenkater-ggrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or ggrun? ai-gateway: Very active. ggrun: 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 ggrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [ggrun trust report](/tools/raketenkater-ggrun/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/_