--- title: "distributed-llama vs ai-gateway" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/b4rtaz-distributed-llama-vs-ferro-labs-ai-gateway" tools: ["b4rtaz-distributed-llama", "ferro-labs-ai-gateway"] --- # distributed-llama vs ai-gateway *GraphCanon updated Aug 24, 2026* ## Verdict Pick distributed-llama if distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license; 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. [distributed-llama](https://github.com/b4rtaz/distributed-llama) reports 3.0k GitHub stars, 246 forks, and 48 open issues, last pushed Jul 5, 2026. [ai-gateway](https://docs.ferrolabs.ai) has 219 stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. Figures are from public GitHub metadata via [distributed-llama's repository](https://github.com/b4rtaz/distributed-llama) and [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway). | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | | --- | --- | --- | | Tagline | Distributed LLM inference using home devices cluster | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | | Stars | 3,044 | 219 | | Forks | 246 | 33 | | Open issues | 48 | 63 | | Language | C++ | Go | | Adopt for | distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 - a permissive free software license | | Categories | Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 50d | 2d | | Open issues (now) | 48 | 63 | | Stars delta | +32 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/b4rtaz-distributed-llama/trust.md) | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | ## Decision facts: distributed-llama - **Adopt for:** distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. ## 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 ## Choose when ### Choose distributed-llama if… - distributed-llama is primarily C++; ai-gateway is Go. - License: distributed-llama is MIT, ai-gateway is Apache-2.0. - Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network. - When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks. ### Choose ai-gateway if… - ai-gateway is primarily Go; distributed-llama is C++. - License: ai-gateway is Apache-2.0, distributed-llama 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 NOT to use distributed-llama - For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. - In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices. ## 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 ## Common questions ### What is the difference between distributed-llama and ai-gateway? distributed-llama: Distributed LLM inference using home devices cluster. ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. See the comparison table for live GitHub stats and shared categories. ### When should I choose distributed-llama over ai-gateway? Choose distributed-llama over ai-gateway when distributed-llama is primarily C++; ai-gateway is Go; License: distributed-llama is MIT, ai-gateway is Apache-2.0; Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network; When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks. ### When should I choose ai-gateway over distributed-llama? Choose ai-gateway over distributed-llama when ai-gateway is primarily Go; distributed-llama is C++; License: ai-gateway is Apache-2.0, distributed-llama 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 avoid distributed-llama? For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices. ### 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 ### Is distributed-llama or ai-gateway more popular on GitHub? distributed-llama has more GitHub stars (3,044 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are distributed-llama and ai-gateway open source? Yes - both are open-source projects on GitHub (distributed-llama: MIT, ai-gateway: Apache-2.0). ### Where can I find alternatives to distributed-llama or ai-gateway? GraphCanon lists graph-backed alternatives at [distributed-llama alternatives](/tools/b4rtaz-distributed-llama/alternatives) and [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) ([distributed-llama markdown twin](/tools/b4rtaz-distributed-llama/alternatives.md), [ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/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/b4rtaz-distributed-llama-vs-ferro-labs-ai-gateway.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, distributed-llama or ai-gateway? distributed-llama: Steady. ai-gateway: 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 distributed-llama and ai-gateway? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [distributed-llama trust report](/tools/b4rtaz-distributed-llama/trust); [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=b4rtaz-distributed-llama`](/api/graphcanon/graph?tool=b4rtaz-distributed-llama) - 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/_