Comparison
llama2-webui vs exllama
Verdict
Pick llama2-webui if llama2-webui - Run Llama 2 models locally via Gradio UI on GPU or CPU; 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 onwards.
Markdown twin · llama2-webui alternatives · exllama alternatives
GraphCanon updated today
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Trust & integrity
| Signal | llama2-webui | exllama |
|---|---|---|
| Maintenance | Dormant (885d since push) As of today · github_public_v1 | Dormant (1041d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal 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
- llama2-webui
- Run Llama 2 locally with gradio UI on GPU or CPU
- exllama
- Memory-efficient rewrite of HF transformers for Llama with quantized weights
Stars
- llama2-webui
- 1.9k
- exllama
- 2.9k
Forks
- llama2-webui
- 199
- exllama
- 220
Open issues
- llama2-webui
- 26
- exllama
- 65
Language
- llama2-webui
- Jupyter Notebook
- exllama
- Python
Adopt for
- llama2-webui
- llama2-webui - Run Llama 2 models locally via Gradio UI on GPU or CPU.
- 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
- llama2-webui
- -
- exllama
- -
Runtime
- llama2-webui
- -
- exllama
- -
License
- llama2-webui
- The MIT License grants permissive software rights making llama2-webui suitable for both proprietary and open-source projects.
- exllama
- MIT
Last pushed
- llama2-webui
- Mar 22, 2024
- exllama
- Sep 30, 2023
Categories
- llama2-webui
- Inference & Serving, LLM Frameworks
- exllama
- Inference & Serving, LLM Frameworks
Trust and health
Days since push
- llama2-webui
- 885d
- exllama
- 1041d
Open issues (now)
- llama2-webui
- 26
- exllama
- 65
Stars delta
- llama2-webui
- 0 (30d)
- exllama
- Unknown
Open issues delta
- llama2-webui
- 0 (30d)
- exllama
- Unknown
OSV dependency advisories
- llama2-webui
- No lockfile (source not queried)
- exllama
- Published findings
Full report
- llama2-webui
- Trust report
- exllama
- Trust report
Choose llama2-webui if…
- llama2-webui is primarily Jupyter Notebook; exllama is Python.
- Requirements: - Ensure you have access to Llama 2 models before proceeding.; - Requires a Python environment capable of running Jupyter Notebooks along with the specified dependencies such as Gradio..
- Tags unique to llama2-webui: gradio, llama-2, local-inference.
- - When you want to run Llama 2 models locally with minimal setup across various operating systems like Linux, Windows, and Mac.
When NOT to use llama2-webui
- - Avoid if you are looking for broader support beyond Llama 2 models; this tool is specifically tailored to work with the Llama 2 series.
- - Not recommended if your project strictly requires a web-based deployment without a local server component, as it emphasizes local model inference.
Choose exllama if…
- exllama is primarily Python; llama2-webui is Jupyter Notebook.
- 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 (liltom-eth/llama2-webui) · observed Aug 25, 2026
- GitHub forks (liltom-eth/llama2-webui) · observed Aug 25, 2026
- Last push (liltom-eth/llama2-webui) · observed Mar 22, 2024
- License file (MIT) · observed Aug 25, 2026
- Decision facts (enrichment) · observed Jul 14, 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: llama2-webui 1.9k · exllama 2.9k (synced Aug 25, 2026).
Common questions
- What is the difference between llama2-webui and exllama?
- llama2-webui: Run Llama 2 locally with gradio UI on GPU or CPU. 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 llama2-webui over exllama?
- Choose llama2-webui over exllama when llama2-webui is primarily Jupyter Notebook; exllama is Python; Requirements: - Ensure you have access to Llama 2 models before proceeding.; - Requires a Python environment capable of running Jupyter Notebooks along with the specified dependencies such as Gradio.; Tags unique to llama2-webui: gradio, llama-2, local-inference; - When you want to run Llama 2 models locally with minimal setup across various operating systems like Linux, Windows, and Mac.
- When should I choose exllama over llama2-webui?
- Choose exllama over llama2-webui when exllama is primarily Python; llama2-webui is Jupyter Notebook; 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 llama2-webui?
- - Avoid if you are looking for broader support beyond Llama 2 models; this tool is specifically tailored to work with the Llama 2 series. - Not recommended if your project strictly requires a web-based deployment without a local server component, as it emphasizes local model inference.
- 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 llama2-webui or exllama more popular on GitHub?
- exllama has more GitHub stars (2,937 vs 1,937). Stars measure visibility, not whether either tool fits your constraints.
- Are llama2-webui and exllama open source?
- Yes - both are open-source projects on GitHub (llama2-webui: MIT, exllama: MIT).
- Where can I find alternatives to llama2-webui or exllama?
- GraphCanon lists graph-backed alternatives at llama2-webui alternatives and exllama alternatives (llama2-webui 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, llama2-webui or exllama?
- llama2-webui: 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 llama2-webui and exllama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama2-webui trust report; exllama trust report.