--- title: "gpt-neox vs LongWriter" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eleutherai-gpt-neox-vs-thudm-longwriter" tools: ["eleutherai-gpt-neox", "thudm-longwriter"] --- # gpt-neox vs LongWriter *GraphCanon updated Aug 24, 2026* ## 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 LongWriter if longWriter specializes in exceeding the text generation limit to over 10,000 words using long-context LLMs for Python-based development. [gpt-neox](https://www.eleuther.ai/) reports 7.5k GitHub stars, 1.1k forks, and 111 open issues, last pushed Jun 11, 2026. [LongWriter](https://github.com/THUDM/LongWriter) has 1.9k stars, 182 forks, and 32 open issues, last pushed Jun 24, 2025. Figures are from public GitHub metadata via [gpt-neox's repository](https://github.com/EleutherAI/gpt-neox) and [LongWriter's repository](https://github.com/THUDM/LongWriter). | | [gpt-neox](/tools/eleutherai-gpt-neox.md) | [LongWriter](/tools/thudm-longwriter.md) | | --- | --- | --- | | Tagline | Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries | LongWriter enables generation of texts longer than 10,000 words using long-context LLMs | | Stars | 7,452 | 1,872 | | Forks | 1,119 | 182 | | Open issues | 111 | 32 | | Language | Python | Python | | 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. | LongWriter specializes in exceeding the text generation limit to over 10,000 words using long-context LLMs for Python-based development. | | Persona | - | - | | Runtime | - | - | | License | 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 | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gpt-neox](/tools/eleutherai-gpt-neox.md) | [LongWriter](/tools/thudm-longwriter.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 56d | 425d | | Open issues (now) | 111 | 32 | | Stars delta | Unknown | +4 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/eleutherai-gpt-neox/trust.md) | [trust report](/tools/thudm-longwriter/trust.md) | ## 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 ## Decision facts: LongWriter - **Adopt for:** LongWriter specializes in exceeding the text generation limit to over 10,000 words using long-context LLMs for Python-based development. ## Choose when ### Choose gpt-neox if… - 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. ### Choose LongWriter if… - Tags unique to LongWriter: fine-tuning, llm, long-context, long-text. - For projects requiring texts longer than 10,000 words with fine-tuned llm models - Leaner open-issue backlog (32). ## 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. ## When NOT to use LongWriter - Avoid for short-form content generation where LLM context is less relevant - Not ideal when the requirement is to maintain conciseness in output texts ## Common questions ### What is the difference between gpt-neox and LongWriter? gpt-neox: Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries. LongWriter: LongWriter enables generation of texts longer than 10,000 words using long-context LLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose gpt-neox over LongWriter? Choose gpt-neox over LongWriter when 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 LongWriter over gpt-neox? Choose LongWriter over gpt-neox when Tags unique to LongWriter: fine-tuning, llm, long-context, long-text; For projects requiring texts longer than 10,000 words with fine-tuned llm models; Leaner open-issue backlog (32). ### 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 LongWriter? Avoid for short-form content generation where LLM context is less relevant Not ideal when the requirement is to maintain conciseness in output texts ### Is gpt-neox or LongWriter more popular on GitHub? gpt-neox has more GitHub stars (7,452 vs 1,872). Stars measure visibility, not whether either tool fits your constraints. ### Are gpt-neox and LongWriter open source? Yes - both are open-source projects on GitHub (gpt-neox: Apache-2.0, LongWriter: Apache-2.0). ### Where can I find alternatives to gpt-neox or LongWriter? GraphCanon lists graph-backed alternatives at [gpt-neox alternatives](/tools/eleutherai-gpt-neox/alternatives) and [LongWriter alternatives](/tools/thudm-longwriter/alternatives) ([gpt-neox markdown twin](/tools/eleutherai-gpt-neox/alternatives.md), [LongWriter markdown twin](/tools/thudm-longwriter/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/eleutherai-gpt-neox-vs-thudm-longwriter.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gpt-neox or LongWriter? gpt-neox: Steady. LongWriter: 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 LongWriter? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gpt-neox trust report](/tools/eleutherai-gpt-neox/trust); [LongWriter trust report](/tools/thudm-longwriter/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eleutherai-gpt-neox`](/api/graphcanon/graph?tool=eleutherai-gpt-neox) - 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/_