--- title: "LibreChat vs raft" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/danny-avila-librechat-vs-nvidia-raft" tools: ["danny-avila-librechat", "nvidia-raft"] --- # LibreChat vs raft *GraphCanon updated Aug 25, 2026* ## Verdict Pick LibreChat if libreChat provides a versatile AI chat platform for self-hosting with extensive features like model switching, code interpretation, and secure multi-user authentication; pick raft if rAFT is a collection of CUDA-accelerated algorithms for high-performance machine learning and information retrieval applications. [LibreChat](https://librechat.ai/) reports 42k GitHub stars, 8.8k forks, and 725 open issues, last pushed Aug 25, 2026. [raft](https://docs.rapids.ai/api/raft/stable/) has 1.0k stars, 248 forks, and 446 open issues, last pushed Aug 22, 2026. Figures are from public GitHub metadata via [LibreChat's repository](https://github.com/danny-avila/LibreChat) and [raft's repository](https://github.com/NVIDIA/raft). | | [LibreChat](/tools/danny-avila-librechat.md) | [raft](/tools/nvidia-raft.md) | | --- | --- | --- | | Tagline | Enhanced ChatGPT Clone with extensive features and integrations for self-hosting | A collection of CUDA-accelerated algorithms for building high-performance machine learning and information retrieval applications. | | Stars | 42,443 | 1,036 | | Forks | 8,804 | 248 | | Open issues | 725 | 446 | | Language | TypeScript | Cuda | | Adopt for | LibreChat provides a versatile AI chat platform for self-hosting with extensive features like model switching, code interpretation, and secure multi-user authentication. | RAFT is a collection of CUDA-accelerated algorithms for high-performance machine learning and information retrieval applications. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LibreChat](/tools/danny-avila-librechat.md) | [raft](/tools/nvidia-raft.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 725 | 446 | | Stars delta | +1.2k (30d) | +5 (30d) | | Open issues delta | +100 (30d) | +2 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/danny-avila-librechat/trust.md) | [trust report](/tools/nvidia-raft/trust.md) | ## Decision facts: LibreChat - **Adopt for:** LibreChat provides a versatile AI chat platform for self-hosting with extensive features like model switching, code interpretation, and secure multi-user authentication. ## Decision facts: raft - **Requirements:** Ensure access to NVIDIA GPUs; Compatibility with CUDA is essential for utilizing the RAFT algorithms effectively.; The user must have familiarity or develop understanding of CUDA programming to optimize their application integration with RAFT. - **Adopt for:** RAFT is a collection of CUDA-accelerated algorithms for high-performance machine learning and information retrieval applications. ## Choose when ### Choose LibreChat if… - LibreChat is primarily TypeScript; raft is Cuda. - License: LibreChat is MIT, raft is Apache-2.0. - Tags unique to LibreChat: ai, anthropic, artifacts, aws. - Also covers AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving. - LibreChat ships Docker support for self-hosted deployment. - Need to support multiple AI models and protocols in one tool ### Choose raft if… - raft is primarily Cuda; LibreChat is TypeScript. - License: raft is Apache-2.0, LibreChat is MIT. - Requirements: Ensure access to NVIDIA GPUs; Compatibility with CUDA is essential for utilizing the RAFT algorithms effectively.; The user must have familiarity or develop understanding of CUDA programming to optimize their application integration with RAFT.. - Tags unique to raft: anns, building-blocks, clustering, cuda. - - You are developing on an NVIDIA GPU architecture and require optimized, CUDA-accelerated primitives. ## When NOT to use LibreChat - Looking for a simpler solution with fewer configurability options - Do not require extensive third-party service integrations or complex customizations ## When NOT to use raft - - Your application does not have access to NVIDIA GPUs, as RAFT's algorithms leverage CUDA specifically for performance gains. - - If your workload requires more generalized machine learning libraries without a dependency on GPU-accelerated primitives and you are working in a multi-platform or cross-vendor environment. ## Common questions ### What is the difference between LibreChat and raft? LibreChat: Enhanced ChatGPT Clone with extensive features and integrations for self-hosting. raft: A collection of CUDA-accelerated algorithms for building high-performance machine learning and information retrieval applications.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LibreChat over raft? Choose LibreChat over raft when LibreChat is primarily TypeScript; raft is Cuda; License: LibreChat is MIT, raft is Apache-2.0; Tags unique to LibreChat: ai, anthropic, artifacts, aws; Also covers AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving; LibreChat ships Docker support for self-hosted deployment; Need to support multiple AI models and protocols in one tool. ### When should I choose raft over LibreChat? Choose raft over LibreChat when raft is primarily Cuda; LibreChat is TypeScript; License: raft is Apache-2.0, LibreChat is MIT; Requirements: Ensure access to NVIDIA GPUs; Compatibility with CUDA is essential for utilizing the RAFT algorithms effectively.; The user must have familiarity or develop understanding of CUDA programming to optimize their application integration with RAFT.; Tags unique to raft: anns, building-blocks, clustering, cuda; - You are developing on an NVIDIA GPU architecture and require optimized, CUDA-accelerated primitives. ### When should I avoid LibreChat? Looking for a simpler solution with fewer configurability options Do not require extensive third-party service integrations or complex customizations ### When should I avoid raft? - Your application does not have access to NVIDIA GPUs, as RAFT's algorithms leverage CUDA specifically for performance gains. - If your workload requires more generalized machine learning libraries without a dependency on GPU-accelerated primitives and you are working in a multi-platform or cross-vendor environment. ### Is LibreChat or raft more popular on GitHub? LibreChat has more GitHub stars (42,443 vs 1,036). Stars measure visibility, not whether either tool fits your constraints. ### Are LibreChat and raft open source? Yes - both are open-source projects on GitHub (LibreChat: MIT, raft: Apache-2.0). ### Where can I find alternatives to LibreChat or raft? GraphCanon lists graph-backed alternatives at [LibreChat alternatives](/tools/danny-avila-librechat/alternatives) and [raft alternatives](/tools/nvidia-raft/alternatives) ([LibreChat markdown twin](/tools/danny-avila-librechat/alternatives.md), [raft markdown twin](/tools/nvidia-raft/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/danny-avila-librechat-vs-nvidia-raft.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LibreChat or raft? LibreChat: Very active. raft: 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 LibreChat and raft? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LibreChat trust report](/tools/danny-avila-librechat/trust); [raft trust report](/tools/nvidia-raft/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=danny-avila-librechat`](/api/graphcanon/graph?tool=danny-avila-librechat) - 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/_