--- title: "aisix vs distributed-llama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/api7-aisix-vs-b4rtaz-distributed-llama" tools: ["api7-aisix", "b4rtaz-distributed-llama"] --- # aisix vs distributed-llama *GraphCanon updated Aug 24, 2026* ## Verdict Pick aisix if aISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers; 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. [aisix](https://api7.ai/ai-gateway) reports 92 GitHub stars, 15 forks, and 98 open issues, last pushed Aug 8, 2026. [distributed-llama](https://github.com/b4rtaz/distributed-llama) has 3.0k stars, 246 forks, and 48 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [aisix's repository](https://github.com/api7/aisix) and [distributed-llama's repository](https://github.com/b4rtaz/distributed-llama). | | [aisix](/tools/api7-aisix.md) | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | | --- | --- | --- | | Tagline | Open-source AI gateway for LLMs & AI agents | Distributed LLM inference using home devices cluster | | Stars | 92 | 3,044 | | Forks | 15 | 246 | | Open issues | 98 | 48 | | Language | Rust | C++ | | Adopt for | AISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers | distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. | | Persona | - | - | | Runtime | - | - | | License | AISIX is available under the Apache License, Version 2.0 which allows you to freely use, modify, and distribute it with proper attribution | MIT | | Categories | AI Agents, Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aisix](/tools/api7-aisix.md) | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 1d | 50d | | Open issues (now) | 98 | 48 | | Stars delta | Unknown | +32 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/api7-aisix/trust.md) | [trust report](/tools/b4rtaz-distributed-llama/trust.md) | ## Decision facts: aisix - **Pricing:** freemium - The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model. - **Requirements:** Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files - **Adopt for:** AISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers - **License detail:** AISIX is available under the Apache License, Version 2.0 which allows you to freely use, modify, and distribute it with proper attribution ## 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. ## Choose when ### Choose aisix if… - aisix is primarily Rust; distributed-llama is C++. - License: aisix is Apache-2.0, distributed-llama is MIT. - Pricing: The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model.. - Requirements: Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files. - Tags unique to aisix: ai-agents, llm-gateway, observability, openai-compatible. - Also covers AI Agents. - aisix ships Docker support for self-hosted deployment. - When you need an OpenAI-compatible API that can route requests to multiple LLM providers like OpenAI, Anthropic, Gemini, and Bedrock ### Choose distributed-llama if… - distributed-llama is primarily C++; aisix is Rust. - License: distributed-llama is MIT, aisix 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 NOT to use aisix - If you require a fully managed service with minimal setup and configuration since AISIX requires self-hosting or connecting to AISIX Cloud for management features - For projects preferring dynamic languages over statically compiled binaries, given that AISIX is built in Rust and ships as one static binary ## 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. ## Common questions ### What is the difference between aisix and distributed-llama? aisix: Open-source AI gateway for LLMs & AI agents. distributed-llama: Distributed LLM inference using home devices cluster. See the comparison table for live GitHub stats and shared categories. ### When should I choose aisix over distributed-llama? Choose aisix over distributed-llama when aisix is primarily Rust; distributed-llama is C++; License: aisix is Apache-2.0, distributed-llama is MIT; Pricing: The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model.; Requirements: Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files; Tags unique to aisix: ai-agents, llm-gateway, observability, openai-compatible; Also covers AI Agents; aisix ships Docker support for self-hosted deployment; When you need an OpenAI-compatible API that can route requests to multiple LLM providers like OpenAI, Anthropic, Gemini, and Bedrock. ### When should I choose distributed-llama over aisix? Choose distributed-llama over aisix when distributed-llama is primarily C++; aisix is Rust; License: distributed-llama is MIT, aisix 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 avoid aisix? If you require a fully managed service with minimal setup and configuration since AISIX requires self-hosting or connecting to AISIX Cloud for management features For projects preferring dynamic languages over statically compiled binaries, given that AISIX is built in Rust and ships as one static binary ### 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. ### Is aisix or distributed-llama more popular on GitHub? distributed-llama has more GitHub stars (3,044 vs 92). Stars measure visibility, not whether either tool fits your constraints. ### Are aisix and distributed-llama open source? Yes - both are open-source projects on GitHub (aisix: Apache-2.0, distributed-llama: MIT). ### Where can I find alternatives to aisix or distributed-llama? GraphCanon lists graph-backed alternatives at [aisix alternatives](/tools/api7-aisix/alternatives) and [distributed-llama alternatives](/tools/b4rtaz-distributed-llama/alternatives) ([aisix markdown twin](/tools/api7-aisix/alternatives.md), [distributed-llama markdown twin](/tools/b4rtaz-distributed-llama/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/api7-aisix-vs-b4rtaz-distributed-llama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aisix or distributed-llama? aisix: Very active. distributed-llama: Steady. 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 aisix and distributed-llama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aisix trust report](/tools/api7-aisix/trust); [distributed-llama trust report](/tools/b4rtaz-distributed-llama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=api7-aisix`](/api/graphcanon/graph?tool=api7-aisix) - 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/_