Comparison
gpt4all vs exllama
Verdict
Pick gpt4all if gPT4All is an open-source project designed to facilitate the local deployment of large language models (LLMs). It supports commercial usage with a permissive MIT license and is implemented in C++; pick exllama if exLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series.
Markdown twin · gpt4all alternatives · exllama alternatives
GraphCanon updated today
Trust & integrity
| Signal | gpt4all | exllama |
|---|---|---|
| Maintenance | Dormant (453d since push) As of today · github_public_v1 | Dormant (1041d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of 2w · 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
- gpt4all
- Run Local LLMs on Any Device
- exllama
- Memory-efficient rewrite of HF transformers for Llama with quantized weights
Stars
- gpt4all
- 77k
- exllama
- 2.9k
Forks
- gpt4all
- 8.3k
- exllama
- 220
Open issues
- gpt4all
- 772
- exllama
- 65
Language
- gpt4all
- C++
- exllama
- Python
Adopt for
- gpt4all
- GPT4All is an open-source project designed to facilitate the local deployment of large language models (LLMs). It supports commercial usage with a permissive MIT license and is implemented in C++.
- exllama
- ExLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards.
Persona
- gpt4all
- -
- exllama
- -
Runtime
- gpt4all
- -
- exllama
- -
License
- gpt4all
- MIT
- exllama
- MIT
Last pushed
- gpt4all
- May 27, 2025
- exllama
- Sep 30, 2023
Categories
- gpt4all
- Inference & Serving, LLM Frameworks
- exllama
- Inference & Serving, LLM Frameworks
Trust and health
Days since push
- gpt4all
- 453d
- exllama
- 1041d
Open issues (now)
- gpt4all
- 772
- exllama
- 65
Stars delta
- gpt4all
- -3 (30d)
- exllama
- Unknown
Open issues delta
- gpt4all
- -1 (30d)
- exllama
- Unknown
Owner type
- gpt4all
- Organization
- exllama
- User
OSV dependency advisories
- gpt4all
- No lockfile (source not queried)
- exllama
- Published findings
Full report
- gpt4all
- Trust report
- exllama
- Trust report
Choose gpt4all if…
- gpt4all is primarily C++; exllama is Python.
- Tags unique to gpt4all: ai-chat, llm-inference.
- - When you require on-device inference capabilities without reliance on cloud services.
When NOT to use gpt4all
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation.
- - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
Choose exllama if…
- exllama is primarily Python; gpt4all is C++.
- Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu.
- exllama ships Docker support for self-hosted deployment.
- - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support.
When NOT to use exllama
- - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better.
- - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts).
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nomic-ai/gpt4all) · observed Aug 24, 2026
- GitHub forks (nomic-ai/gpt4all) · observed Aug 24, 2026
- Last push (nomic-ai/gpt4all) · observed May 27, 2025
- License file (MIT) · observed Aug 24, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (turboderp/exllama) · observed Aug 7, 2026
- GitHub forks (turboderp/exllama) · observed Aug 7, 2026
- Last push (turboderp/exllama) · observed Sep 30, 2023
- License file (MIT) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt4all 77k · exllama 2.9k (synced Aug 24, 2026).
Common questions
- What is the difference between gpt4all and exllama?
- gpt4all: Run Local LLMs on Any Device. exllama: Memory-efficient rewrite of HF transformers for Llama with quantized weights. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt4all over exllama?
- Choose gpt4all over exllama when gpt4all is primarily C++; exllama is Python; Tags unique to gpt4all: ai-chat, llm-inference; - When you require on-device inference capabilities without reliance on cloud services.
- When should I choose exllama over gpt4all?
- Choose exllama over gpt4all when exllama is primarily Python; gpt4all is C++; Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu; exllama ships Docker support for self-hosted deployment; - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support.
- When should I avoid gpt4all?
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation. - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
- When should I avoid exllama?
- - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better. - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts).
- Is gpt4all or exllama more popular on GitHub?
- gpt4all has more GitHub stars (77,393 vs 2,937). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt4all and exllama open source?
- Yes - both are open-source projects on GitHub (gpt4all: MIT, exllama: MIT).
- Where can I find alternatives to gpt4all or exllama?
- GraphCanon lists graph-backed alternatives at gpt4all alternatives and exllama alternatives (gpt4all markdown twin, exllama 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, gpt4all or exllama?
- gpt4all: Dormant. exllama: 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 gpt4all and exllama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt4all trust report; exllama trust report.