--- title: "qlora vs gpt-neox" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/artidoro-qlora-vs-eleutherai-gpt-neox" tools: ["artidoro-qlora", "eleutherai-gpt-neox"] --- # qlora vs gpt-neox *GraphCanon updated Aug 7, 2026* ## Verdict Pick qlora if qLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family; pick gpt-neox if gPT-NeoX from EleutherAI leverages GPU-based model parallelism via Megatron and DeepSpeed libraries to facilitate the training of large-scale autoregressive transformers in Python, under an Apache-2.0 license. [qlora](https://arxiv.org/abs/2305.14314) reports 11k GitHub stars, 876 forks, and 206 open issues, last pushed Jun 10, 2024. [gpt-neox](https://www.eleuther.ai/) has 7.5k stars, 1.1k forks, and 111 open issues, last pushed Jun 11, 2026. Figures are from public GitHub metadata via [qlora's repository](https://github.com/artidoro/qlora) and [gpt-neox's repository](https://github.com/EleutherAI/gpt-neox). | | [qlora](/tools/artidoro-qlora.md) | [gpt-neox](/tools/eleutherai-gpt-neox.md) | | --- | --- | --- | | Tagline | QLoRA finetuning of quantized LLMs | Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries | | Stars | 10,979 | 7,452 | | Forks | 876 | 1,119 | | Open issues | 206 | 111 | | Language | Jupyter Notebook | Python | | Adopt for | QLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family. | GPT-NeoX from EleutherAI leverages GPU-based model parallelism via Megatron and DeepSpeed libraries to facilitate the training of large-scale autoregressive transformers in Python, under an Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | MIT License; open-source tool for QLoRA fine-tuning process; LLaMA base models must be obtained legally as per their license terms | The tool is licensed under Apache-2.0, allowing permissive use but emphasizing that derivative works must preserve copyright headers and licenses as per their origins | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [qlora](/tools/artidoro-qlora.md) | [gpt-neox](/tools/eleutherai-gpt-neox.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 783d | 56d | | Open issues (now) | 206 | 111 | | Owner type | User | Organization | | Full report | [trust report](/tools/artidoro-qlora/trust.md) | [trust report](/tools/eleutherai-gpt-neox/trust.md) | ## Decision facts: qlora - **Pricing:** freemium - Open source under MIT License; requires access to LLaMA base models - **Requirements:** Installation involves installing PyTorch and specific packages from source; Works with model sizes ranging from 7B to 65B, includes recommendations for tuning different sizes - **Adopt for:** QLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family. - **License detail:** MIT License; open-source tool for QLoRA fine-tuning process; LLaMA base models must be obtained legally as per their license terms ## Decision facts: gpt-neox - **Pricing:** freemium - Free to use with the caveat of adhering to the Apache License terms, particularly in preserving copyright and license headers for all derivations. - **Adopt for:** GPT-NeoX from EleutherAI leverages GPU-based model parallelism via Megatron and DeepSpeed libraries to facilitate the training of large-scale autoregressive transformers in Python, under an Apache-2.0 license. - **License detail:** The tool is licensed under Apache-2.0, allowing permissive use but emphasizing that derivative works must preserve copyright headers and licenses as per their origins ## Choose when ### Choose qlora if… - qlora is primarily Jupyter Notebook; gpt-neox is Python. - License: qlora is MIT, gpt-neox is Apache-2.0. - Pricing: Open source under MIT License; requires access to LLaMA base models. - Requirements: Installation involves installing PyTorch and specific packages from source; Works with model sizes ranging from 7B to 65B, includes recommendations for tuning different sizes. - Tags unique to qlora: fine-tuning, guanaco, llama models, quantization. - Need efficient fine-tuning for quantized LLaMA-based models ### Choose gpt-neox if… - gpt-neox is primarily Python; qlora is Jupyter Notebook. - License: gpt-neox is Apache-2.0, qlora is MIT. - Pricing: Free to use with the caveat of adhering to the Apache License terms, particularly in preserving copyright and license headers for all derivations.. - Tags unique to gpt-neox: deepspeed-library, gpt-3, language-model, transformers. - - When your project requires a framework based on state-of-the-art libraries like Megatron and DeepSpeed that are optimized for large GPU clusters. ## When NOT to use qlora - Require native full-precision model tuning without efficiency constraints - Focusing on non-LLaMA-based language models where specific adaptations may not apply ## When NOT to use gpt-neox - - In scenarios where minimal hardware resources, such as a single low-memory GPU or CPU-only environments, are available for training due to GPT-NeoX's requirement for a large-scale infrastructure. - - If your project is limited by the Apache License terms or requires proprietary codebases without open-source contributions and modifications from external parties. ## Common questions ### What is the difference between qlora and gpt-neox? qlora: QLoRA finetuning of quantized LLMs. gpt-neox: Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries. See the comparison table for live GitHub stats and shared categories. ### When should I choose qlora over gpt-neox? Choose qlora over gpt-neox when qlora is primarily Jupyter Notebook; gpt-neox is Python; License: qlora is MIT, gpt-neox is Apache-2.0; Pricing: Open source under MIT License; requires access to LLaMA base models; Requirements: Installation involves installing PyTorch and specific packages from source; Works with model sizes ranging from 7B to 65B, includes recommendations for tuning different sizes; Tags unique to qlora: fine-tuning, guanaco, llama models, quantization; Need efficient fine-tuning for quantized LLaMA-based models. ### When should I choose gpt-neox over qlora? Choose gpt-neox over qlora when gpt-neox is primarily Python; qlora is Jupyter Notebook; License: gpt-neox is Apache-2.0, qlora is MIT; Pricing: Free to use with the caveat of adhering to the Apache License terms, particularly in preserving copyright and license headers for all derivations.; Tags unique to gpt-neox: deepspeed-library, gpt-3, language-model, transformers; - When your project requires a framework based on state-of-the-art libraries like Megatron and DeepSpeed that are optimized for large GPU clusters. ### When should I avoid qlora? Require native full-precision model tuning without efficiency constraints Focusing on non-LLaMA-based language models where specific adaptations may not apply ### When should I avoid gpt-neox? - In scenarios where minimal hardware resources, such as a single low-memory GPU or CPU-only environments, are available for training due to GPT-NeoX's requirement for a large-scale infrastructure. - If your project is limited by the Apache License terms or requires proprietary codebases without open-source contributions and modifications from external parties. ### Is qlora or gpt-neox more popular on GitHub? qlora has more GitHub stars (10,979 vs 7,452). Stars measure visibility, not whether either tool fits your constraints. ### Are qlora and gpt-neox open source? Yes - both are open-source projects on GitHub (qlora: MIT, gpt-neox: Apache-2.0). ### Where can I find alternatives to qlora or gpt-neox? GraphCanon lists graph-backed alternatives at [qlora alternatives](/tools/artidoro-qlora/alternatives) and [gpt-neox alternatives](/tools/eleutherai-gpt-neox/alternatives) ([qlora markdown twin](/tools/artidoro-qlora/alternatives.md), [gpt-neox markdown twin](/tools/eleutherai-gpt-neox/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/artidoro-qlora-vs-eleutherai-gpt-neox.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, qlora or gpt-neox? qlora: Dormant. gpt-neox: 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 qlora and gpt-neox? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [qlora trust report](/tools/artidoro-qlora/trust); [gpt-neox trust report](/tools/eleutherai-gpt-neox/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=artidoro-qlora`](/api/graphcanon/graph?tool=artidoro-qlora) - 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/_