--- title: "codellama vs ggrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/meta-llama-codellama-vs-raketenkater-ggrun" tools: ["meta-llama-codellama", "raketenkater-ggrun"] --- # codellama vs ggrun *GraphCanon updated Aug 13, 2026* ## Verdict Pick codellama if codellama offers an open-source inference framework for CodeLlama models using Python; 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. [codellama](https://github.com/meta-llama/codellama) reports 16k GitHub stars, 1.9k forks, and 116 open issues, last pushed Aug 12, 2024. [ggrun](https://github.com/raketenkater/ggrun) has 264 stars, 14 forks, and 1 open issues, last pushed Aug 11, 2026. Figures are from public GitHub metadata via [codellama's repository](https://github.com/meta-llama/codellama) and [ggrun's repository](https://github.com/raketenkater/ggrun). | | [codellama](/tools/meta-llama-codellama.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Tagline | Inference code for CodeLlama models | Auto-tuned launcher for GGUF models on llama.cpp with OpenAI-compatible server | | Stars | 16,280 | 264 | | Forks | 1,939 | 14 | | Open issues | 116 | 1 | | Language | Python | Go | | Adopt for | codellama offers an open-source inference framework for CodeLlama models using Python. | 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 | Other | 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 | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [codellama](/tools/meta-llama-codellama.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Very active (96%) | | Days since push | 722d | 1d | | Archived on GitHub | Yes | No | | Open issues (now) | 116 | 1 | | Owner type | Organization | User | | Full report | [trust report](/tools/meta-llama-codellama/trust.md) | [trust report](/tools/raketenkater-ggrun/trust.md) | ## Decision facts: codellama - **Pricing:** freemium - codellama operates on an open-source model with freedoms for both researchers and commercial entities. Costs will arise from hosting and running environments where required. - **Requirements:** Users should familiarize themselves with the acceptable use policy to align their projects accordingly.; Dependencies include Python, which must be installed for using codellama. - **Adopt for:** codellama offers an open-source inference framework for CodeLlama models using Python. ## 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 codellama if… - codellama is primarily Python; ggrun is Go. - License: codellama is Other, ggrun is MIT. - Pricing: codellama operates on an open-source model with freedoms for both researchers and commercial entities. Costs will arise from hosting and running environments where required.. - Requirements: Users should familiarize themselves with the acceptable use policy to align their projects accordingly.; Dependencies include Python, which must be installed for using codellama.. - Tags unique to codellama: codellama, inference, python. - If you need to work with the CodeLlama models specifically and benefit from their specialized capabilities in coding tasks, codellama provides tailored support that may outperform generic solutions. ### Choose ggrun if… - ggrun is primarily Go; codellama is Python. - License: ggrun is MIT, codellama is Other. - 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 codellama - If you are working on projects that do not align with CodeLlama's acceptable use policy or require compliance with specific industry standards beyond what codellama offers. - For tasks that demand a different primary programming language other than Python, as codellama is primarily developed around the Python ecosystem. ## 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 codellama and ggrun? codellama: Inference code for CodeLlama models. 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 codellama over ggrun? Choose codellama over ggrun when codellama is primarily Python; ggrun is Go; License: codellama is Other, ggrun is MIT; Pricing: codellama operates on an open-source model with freedoms for both researchers and commercial entities. Costs will arise from hosting and running environments where required.; Requirements: Users should familiarize themselves with the acceptable use policy to align their projects accordingly.; Dependencies include Python, which must be installed for using codellama.; Tags unique to codellama: codellama, inference, python; If you need to work with the CodeLlama models specifically and benefit from their specialized capabilities in coding tasks, codellama provides tailored support that may outperform generic solutions. ### When should I choose ggrun over codellama? Choose ggrun over codellama when ggrun is primarily Go; codellama is Python; License: ggrun is MIT, codellama is Other; 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 codellama? If you are working on projects that do not align with CodeLlama's acceptable use policy or require compliance with specific industry standards beyond what codellama offers. For tasks that demand a different primary programming language other than Python, as codellama is primarily developed around the Python ecosystem. ### 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 codellama or ggrun more popular on GitHub? codellama has more GitHub stars (16,280 vs 264). Stars measure visibility, not whether either tool fits your constraints. ### Are codellama and ggrun open source? Yes - both are open-source projects on GitHub (codellama: Other, ggrun: MIT). ### Where can I find alternatives to codellama or ggrun? GraphCanon lists graph-backed alternatives at [codellama alternatives](/tools/meta-llama-codellama/alternatives) and [ggrun alternatives](/tools/raketenkater-ggrun/alternatives) ([codellama markdown twin](/tools/meta-llama-codellama/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/meta-llama-codellama-vs-raketenkater-ggrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, codellama or ggrun? codellama: Archived. 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 codellama and ggrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [codellama trust report](/tools/meta-llama-codellama/trust); [ggrun trust report](/tools/raketenkater-ggrun/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=meta-llama-codellama`](/api/graphcanon/graph?tool=meta-llama-codellama) - 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/_