--- title: "distributed-llama vs litellm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/b4rtaz-distributed-llama-vs-berriai-litellm" tools: ["b4rtaz-distributed-llama", "berriai-litellm"] --- # distributed-llama vs litellm *GraphCanon updated Jul 11, 2026* ## Verdict Pick distributed-llama when distributed-llama is primarily C++; litellm is Python; pick litellm when litellm is primarily Python; distributed-llama is C++. [distributed-llama](https://github.com/b4rtaz/distributed-llama) reports 3.0k GitHub stars, 238 forks, and 48 open issues, last pushed Jul 5, 2026. [litellm](https://docs.litellm.ai/docs/) has 53k stars, 9.7k forks, and 3.9k open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [distributed-llama's repository](https://github.com/b4rtaz/distributed-llama) and [litellm's repository](https://github.com/BerriAI/litellm). | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Tagline | Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference. | Python SDK and Proxy Server for calling multiple LLM APIs | | Stars | 2,981 | 53,271 | | Forks | 238 | 9,671 | | Open issues | 48 | 3,915 | | Language | C++ | Python | | Adopt for | - | litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. | | Persona | - | - | | Runtime | - | - | | License | MIT | The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Days since push | 5d | 0d | | Open issues (now) | 48 | 3.9k | | Owner type | User | Organization | | Security scan | No lockfile | 2 low (2 low) | | Full report | [trust report](/tools/b4rtaz-distributed-llama/trust.md) | [trust report](/tools/berriai-litellm/trust.md) | ## Decision facts: litellm - **Pricing:** freemium - While the core functionality is provided free, specific extended features might require a paid plan. - **Requirements:** Requires Docker - **Adopt for:** litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. - **License detail:** The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. ## Choose when ### Choose distributed-llama if… - distributed-llama is primarily C++; litellm is Python. - License: distributed-llama is MIT, litellm is Other. - Tags unique to distributed-llama: distributed-computing, distributed-llm, llama2, llama3. ### Choose litellm if… - litellm is primarily Python; distributed-llama is C++. - License: litellm is Other, distributed-llama is MIT. - Pricing: While the core functionality is provided free, specific extended features might require a paid plan.. - Requirements: Requires Docker. - Tags unique to litellm: ai-gateway, azure-openai, bedrock, openai. - litellm ships Docker support for self-hosted deployment. - When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging ## When NOT to use distributed-llama - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use litellm - If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ## Common questions ### What is the difference between distributed-llama and litellm? distributed-llama: Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference.. litellm: Python SDK and Proxy Server for calling multiple LLM APIs. See the comparison table for live GitHub stats and shared categories. ### When should I choose distributed-llama over litellm? Choose distributed-llama over litellm when distributed-llama is primarily C++; litellm is Python; License: distributed-llama is MIT, litellm is Other; Tags unique to distributed-llama: distributed-computing, distributed-llm, llama2, llama3. ### When should I choose litellm over distributed-llama? Choose litellm over distributed-llama when litellm is primarily Python; distributed-llama is C++; License: litellm is Other, distributed-llama is MIT; Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: ai-gateway, azure-openai, bedrock, openai; litellm ships Docker support for self-hosted deployment; When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging. ### When should I avoid distributed-llama? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid litellm? If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ### Is distributed-llama or litellm more popular on GitHub? litellm has more GitHub stars (53,271 vs 2,981). Stars measure visibility, not whether either tool fits your constraints. ### Are distributed-llama and litellm open source? Yes - both are open-source projects on GitHub (distributed-llama: MIT, litellm: Other). ### Where can I find alternatives to distributed-llama or litellm? GraphCanon lists graph-backed alternatives at [distributed-llama alternatives](/tools/b4rtaz-distributed-llama/alternatives) and [litellm alternatives](/tools/berriai-litellm/alternatives) ([distributed-llama markdown twin](/tools/b4rtaz-distributed-llama/alternatives.md), [litellm markdown twin](/tools/berriai-litellm/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-berriai-litellm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, distributed-llama or litellm? distributed-llama: Very active. litellm: 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 litellm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [distributed-llama trust report](/tools/b4rtaz-distributed-llama/trust); [litellm trust report](/tools/berriai-litellm/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/_