Comparison
qlora vs gpt-neox
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.
Markdown twin · qlora alternatives · gpt-neox alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | qlora | gpt-neox |
|---|---|---|
| Maintenance | Dormant (783d since push) As of 3w · github_public_v1 | Steady (56d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- qlora
- QLoRA finetuning of quantized LLMs
- gpt-neox
- Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries
Stars
- qlora
- 11k
- gpt-neox
- 7.5k
Forks
- qlora
- 876
- gpt-neox
- 1.1k
Open issues
- qlora
- 206
- gpt-neox
- 111
Language
- qlora
- Jupyter Notebook
- gpt-neox
- Python
Adopt for
- qlora
- QLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family.
- gpt-neox
- 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
- qlora
- -
- gpt-neox
- -
Runtime
- qlora
- -
- gpt-neox
- -
License
- qlora
- MIT License; open-source tool for QLoRA fine-tuning process; LLaMA base models must be obtained legally as per their license terms
- gpt-neox
- 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
Last pushed
- qlora
- Jun 10, 2024
- gpt-neox
- Jun 11, 2026
Categories
- qlora
- LLM Frameworks, Model Training
- gpt-neox
- LLM Frameworks, Model Training
Trust and health
Maintenance
- qlora
- Dormant (18%)
- gpt-neox
- Steady (60%)
Days since push
- qlora
- 783d
- gpt-neox
- 56d
Open issues (now)
- qlora
- 206
- gpt-neox
- 111
Owner type
- qlora
- User
- gpt-neox
- Organization
OSV dependency advisories
- qlora
- Published findings
- gpt-neox
- No lockfile (source not queried)
Full report
- qlora
- Trust report
- gpt-neox
- Trust report
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
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
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (artidoro/qlora) · observed Aug 3, 2026
- GitHub forks (artidoro/qlora) · observed Aug 3, 2026
- Last push (artidoro/qlora) · observed Jun 10, 2024
- License file (MIT) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (EleutherAI/gpt-neox) · observed Aug 7, 2026
- GitHub forks (EleutherAI/gpt-neox) · observed Aug 7, 2026
- Last push (EleutherAI/gpt-neox) · observed Jun 11, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: qlora 11k · gpt-neox 7.5k (synced Aug 3, 2026).
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 and gpt-neox alternatives (qlora markdown twin, gpt-neox markdown twin), 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 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; gpt-neox trust report.