Comparison
gpt-neox vs NExT-GPT
Verdict
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; pick NExT-GPT if nExT-GPT is focused on multimodal capabilities and instruction tuning for a large language model, targeting researchers and developers interested in multimodal applications.
Markdown twin · gpt-neox alternatives · NExT-GPT alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | gpt-neox | NExT-GPT |
|---|---|---|
| Maintenance | Steady (56d since push) As of 2w · github_public_v1 | Dormant (461d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- gpt-neox
- Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries
- NExT-GPT
- Code and models for ICML 2024 paper on multimodal large language model
Stars
- gpt-neox
- 7.5k
- NExT-GPT
- 3.6k
Forks
- gpt-neox
- 1.1k
- NExT-GPT
- 359
Open issues
- gpt-neox
- 111
- NExT-GPT
- 81
Language
- gpt-neox
- Python
- NExT-GPT
- Python
Adopt for
- 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.
- NExT-GPT
- NExT-GPT is focused on multimodal capabilities and instruction tuning for a large language model, targeting researchers and developers interested in multimodal applications.
Persona
- gpt-neox
- -
- NExT-GPT
- -
Runtime
- gpt-neox
- -
- NExT-GPT
- -
License
- 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
- NExT-GPT
- BSD-3-Clause
Last pushed
- gpt-neox
- Jun 11, 2026
- NExT-GPT
- May 13, 2025
Categories
- gpt-neox
- LLM Frameworks, Model Training
- NExT-GPT
- LLM Frameworks, Model Training
Trust and health
Maintenance
- gpt-neox
- Steady (60%)
- NExT-GPT
- Dormant (18%)
Days since push
- gpt-neox
- 56d
- NExT-GPT
- 461d
Open issues (now)
- gpt-neox
- 111
- NExT-GPT
- 81
Stars delta
- gpt-neox
- Unknown
- NExT-GPT
- -1 (30d)
Open issues delta
- gpt-neox
- Unknown
- NExT-GPT
- 0 (30d)
Owner type
- gpt-neox
- Organization
- NExT-GPT
- User
OSV dependency advisories
- gpt-neox
- No lockfile (source not queried)
- NExT-GPT
- Published findings
Full report
- gpt-neox
- Trust report
- NExT-GPT
- Trust report
Choose gpt-neox if…
- License: gpt-neox is Apache-2.0, NExT-GPT is BSD-3-Clause.
- 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.
Choose NExT-GPT if…
- License: NExT-GPT is BSD-3-Clause, gpt-neox is Apache-2.0.
- Pricing: NExT-GPT is open-source under BSD-3-Clause license, indicating a free but restricted-for-commercial-use model without associated direct monetary cost..
- Requirements: Min 8 GB RAM; - The repository notes that the code and models are intended for non-commercial use only and must not be used in any illegal or harmful contexts.; - Potential commercial users should seek approval from the authors, making it unsuitable without prior authorization if commercial application is considered..
- Tags unique to NExT-GPT: chatgpt, foundation-models, instruction-tuning, large language models.
- - If you are conducting research specifically centered around multimodal interactions (combining text with visual elements) aligning with the scope of NExT-GPT.
When NOT to use NExT-GPT
- - When your project necessitates a production-ready solution, as NExT-GPT is positioned purely for research and non-commercial use.
- - If your application requires the model to be used in contexts like illegal, harmful, violent, racist, or sexual purposes, since its usage guidelines explicitly prohibit such applications.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (NExT-GPT/NExT-GPT) · observed Aug 18, 2026
- GitHub forks (NExT-GPT/NExT-GPT) · observed Aug 18, 2026
- Last push (NExT-GPT/NExT-GPT) · observed May 13, 2025
- License file (BSD-3-Clause) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt-neox 7.5k · NExT-GPT 3.6k (synced Aug 7, 2026).
Common questions
- What is the difference between gpt-neox and NExT-GPT?
- gpt-neox: Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries. NExT-GPT: Code and models for ICML 2024 paper on multimodal large language model. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt-neox over NExT-GPT?
- Choose gpt-neox over NExT-GPT when License: gpt-neox is Apache-2.0, NExT-GPT is BSD-3-Clause; 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 choose NExT-GPT over gpt-neox?
- Choose NExT-GPT over gpt-neox when License: NExT-GPT is BSD-3-Clause, gpt-neox is Apache-2.0; Pricing: NExT-GPT is open-source under BSD-3-Clause license, indicating a free but restricted-for-commercial-use model without associated direct monetary cost.; Requirements: Min 8 GB RAM; - The repository notes that the code and models are intended for non-commercial use only and must not be used in any illegal or harmful contexts.; - Potential commercial users should seek approval from the authors, making it unsuitable without prior authorization if commercial application is considered.; Tags unique to NExT-GPT: chatgpt, foundation-models, instruction-tuning, large language models; - If you are conducting research specifically centered around multimodal interactions (combining text with visual elements) aligning with the scope of NExT-GPT.
- 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.
- When should I avoid NExT-GPT?
- - When your project necessitates a production-ready solution, as NExT-GPT is positioned purely for research and non-commercial use. - If your application requires the model to be used in contexts like illegal, harmful, violent, racist, or sexual purposes, since its usage guidelines explicitly prohibit such applications.
- Is gpt-neox or NExT-GPT more popular on GitHub?
- gpt-neox has more GitHub stars (7,452 vs 3,637). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt-neox and NExT-GPT open source?
- Yes - both are open-source projects on GitHub (gpt-neox: Apache-2.0, NExT-GPT: BSD-3-Clause).
- Where can I find alternatives to gpt-neox or NExT-GPT?
- GraphCanon lists graph-backed alternatives at gpt-neox alternatives and NExT-GPT alternatives (gpt-neox markdown twin, NExT-GPT 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, gpt-neox or NExT-GPT?
- gpt-neox: Steady. NExT-GPT: Dormant. 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 gpt-neox and NExT-GPT?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt-neox trust report; NExT-GPT trust report.