Home/Compare/llm vs exllama

Comparison

llm vs exllama

Verdict

Pick llm when license: llm is Apache-2.0, exllama is MIT; pick exllama when license: exllama is MIT, llm is Apache-2.0.

Markdown twin · llm alternatives · exllama alternatives

GraphCanon updated today

llm logo

llm

simonw/llm

12kpushed Jul 9, 2026
vs
exllama logo

exllama

turboderp/exllama

2.9kpushed Sep 30, 2023

Trust & integrity

Signalllmexllama
Maintenance
Very active (1d since push)
As of today · github_public_v1
Dormant (1014d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
29 low (29 low)
As of today · osv@v1

Tagline

llm
Access large language models from the command-line
exllama
More memory-efficient rewrite of HF transformers for Llama with quantized weights

Stars

llm
12k
exllama
2.9k

Forks

llm
920
exllama
223

Open issues

llm
645
exllama
65

Language

llm
Python
exllama
Python

Adopt for

llm
Decision-critical facts for 'llm'
exllama
-

Persona

llm
-
exllama
-

Runtime

llm
-
exllama
-

License

llm
Apache-2.0
exllama
MIT

Last pushed

llm
Jul 9, 2026
exllama
Sep 30, 2023

Categories

llm
LLM Frameworks, Inference & Serving
exllama
LLM Frameworks, Inference & Serving

Trust and health

Maintenance

llm
Very active (96%)
exllama
Dormant (18%)

Days since push

llm
1d
exllama
1014d

Open issues (now)

llm
645
exllama
65

Security scan

llm
No lockfile
exllama
29 low (29 low)

Full report

Choose llm if…

  • License: llm is Apache-2.0, exllama is MIT.
  • Requirements: - Installation supports multiple methods including `pip`, Homebrew (with caveats noted), `pipx`, and `uv`.; - Requires an OpenAI API key for certain functionalities..
  • Tags unique to llm: llms, ai, openai.
  • - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods.

When NOT to use llm

  • - If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based.
  • - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models.

Choose exllama if…

  • License: exllama is MIT, llm is Apache-2.0.
  • Tags unique to exllama: nvidia support, gpu optimization, memory efficiency, docker container support.
  • exllama ships Docker support for self-hosted deployment.

When NOT to use exllama

  • Last GitHub push was 1015 days ago (dormant maintenance, Sep 30, 2023). Validate activity before betting a new project on exllama.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: llm 12k · exllama 2.9k (synced Jul 11, 2026).

Common questions

What is the difference between llm and exllama?
llm: Access large language models from the command-line. exllama: More 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 llm over exllama?
Choose llm over exllama when License: llm is Apache-2.0, exllama is MIT; Requirements: - Installation supports multiple methods including pip, Homebrew (with caveats noted), pipx, and uv.; - Requires an OpenAI API key for certain functionalities.; Tags unique to llm: llms, ai, openai; - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods.
When should I choose exllama over llm?
Choose exllama over llm when License: exllama is MIT, llm is Apache-2.0; Tags unique to exllama: nvidia support, gpu optimization, memory efficiency, docker container support; exllama ships Docker support for self-hosted deployment.
When should I avoid llm?
- If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based. - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models.
When should I avoid exllama?
Last GitHub push was 1015 days ago (dormant maintenance, Sep 30, 2023). Validate activity before betting a new project on exllama. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Is llm or exllama more popular on GitHub?
llm has more GitHub stars (12,172 vs 2,930). Stars measure visibility, not whether either tool fits your constraints.
Are llm and exllama open source?
Yes - both are open-source projects on GitHub (llm: Apache-2.0, exllama: MIT).
Where can I find alternatives to llm or exllama?
GraphCanon lists graph-backed alternatives at llm alternatives and exllama alternatives (llm 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, llm or exllama?
llm: Very active. 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 llm and exllama?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm trust report; exllama trust report.