---
title: "gpt-neox vs GLM-130B"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/eleutherai-gpt-neox-vs-zai-org-glm-130b"
tools: ["eleutherai-gpt-neox", "zai-org-glm-130b"]
---

# gpt-neox vs GLM-130B

*GraphCanon updated Aug 7, 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 GLM-130B if gLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license.

[gpt-neox](https://www.eleuther.ai/) reports 7.5k GitHub stars, 1.1k forks, and 111 open issues, last pushed Jun 11, 2026. [GLM-130B](https://github.com/zai-org/GLM-130B) has 7.7k stars, 600 forks, and 124 open issues, last pushed Jul 25, 2023. Figures are from public GitHub metadata via [gpt-neox's repository](https://github.com/EleutherAI/gpt-neox) and [GLM-130B's repository](https://github.com/zai-org/GLM-130B).

| | [gpt-neox](/tools/eleutherai-gpt-neox.md) | [GLM-130B](/tools/zai-org-glm-130b.md) |
| --- | --- | --- |
| Tagline | Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries | GLM-130B: An Open Bilingual Pre-Trained Model |
| Stars | 7,452 | 7,656 |
| Forks | 1,119 | 600 |
| Open issues | 111 | 124 |
| 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. | GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. |
| 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 | The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License. |
| 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) | [GLM-130B](/tools/zai-org-glm-130b.md) |
| --- | --- | --- |
| Maintenance | Steady (60%) | Dormant (18%) |
| Days since push | 56d | 1103d |
| Open issues (now) | 111 | 124 |
| Full report | [trust report](/tools/eleutherai-gpt-neox/trust.md) | [trust report](/tools/zai-org-glm-130b/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: GLM-130B

- **Pricing:** freemium - Free to use with specific licensing requirements for model weights.
- **Requirements:** Min 8 GB RAM
- **Adopt for:** GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license.
- **License detail:** The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License.

## 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, 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 GLM-130B if…

- Pricing: Free to use with specific licensing requirements for model weights..
- Requirements: Min 8 GB RAM.
- Tags unique to GLM-130B: bilingual, iclr 2023, pre-trained.
- Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts.

## 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 GLM-130B

- Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support.
- Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment.

## Common questions

### What is the difference between gpt-neox and GLM-130B?

gpt-neox: Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries. GLM-130B: GLM-130B: An Open Bilingual Pre-Trained Model. See the comparison table for live GitHub stats and shared categories.

### When should I choose gpt-neox over GLM-130B?

Choose gpt-neox over GLM-130B 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, 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 GLM-130B over gpt-neox?

Choose GLM-130B over gpt-neox when Pricing: Free to use with specific licensing requirements for model weights.; Requirements: Min 8 GB RAM; Tags unique to GLM-130B: bilingual, iclr 2023, pre-trained; Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts.

### 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 GLM-130B?

Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support. Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment.

### Is gpt-neox or GLM-130B more popular on GitHub?

GLM-130B has more GitHub stars (7,656 vs 7,452). Stars measure visibility, not whether either tool fits your constraints.

### Are gpt-neox and GLM-130B open source?

Yes - both are open-source projects on GitHub (gpt-neox: Apache-2.0, GLM-130B: Apache-2.0).

### Where can I find alternatives to gpt-neox or GLM-130B?

GraphCanon lists graph-backed alternatives at [gpt-neox alternatives](/tools/eleutherai-gpt-neox/alternatives) and [GLM-130B alternatives](/tools/zai-org-glm-130b/alternatives) ([gpt-neox markdown twin](/tools/eleutherai-gpt-neox/alternatives.md), [GLM-130B markdown twin](/tools/zai-org-glm-130b/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-zai-org-glm-130b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, gpt-neox or GLM-130B?

gpt-neox: Steady. GLM-130B: 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 GLM-130B?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gpt-neox trust report](/tools/eleutherai-gpt-neox/trust); [GLM-130B trust report](/tools/zai-org-glm-130b/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/_