Comparison
llama3.java vs exllama
Verdict
Pick llama3.java if llama3.java is a Java-centric tool for performing inference with Llama 3+ models without relying on external dependencies; 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 · llama3.java alternatives · exllama alternatives
GraphCanon updated Sep 20, 2026
vs
Trust & integrity
| Signal | llama3.java | exllama |
|---|---|---|
| Maintenance | Slowing (148d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (1072d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · 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
- llama3.java
- Llama 3+ inference in pure Java
- exllama
- Memory-efficient rewrite of HF transformers for Llama with quantized weights
Stars
- llama3.java
- 818
- exllama
- 2.9k
Forks
- llama3.java
- 95
- exllama
- 220
Open issues
- llama3.java
- 18
- exllama
- 65
Language
- llama3.java
- Java
- exllama
- Python
Adopt for
- llama3.java
- llama3.java is a Java-centric tool for performing inference with Llama 3+ models without relying on external dependencies.
- 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
- llama3.java
- -
- exllama
- -
Runtime
- llama3.java
- -
- exllama
- -
License
- llama3.java
- MIT
- exllama
- MIT
Last pushed
- llama3.java
- Apr 24, 2026
- exllama
- Sep 30, 2023
Categories
- llama3.java
- Inference & Serving
- exllama
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- llama3.java
- Slowing (36%)
- exllama
- Dormant (18%)
Days since push
- llama3.java
- 148d
- exllama
- 1072d
Open issues (now)
- llama3.java
- 18
- exllama
- 65
Stars delta
- llama3.java
- +2 (30d)
- exllama
- +6 (30d)
OSV dependency advisories
- llama3.java
- No lockfile (source not queried)
- exllama
- Published findings
Full report
- llama3.java
- Trust report
- exllama
- Trust report
Choose llama3.java if…
- llama3.java is primarily Java; exllama is Python.
- Tags unique to llama3.java: chatgpt, genai, gguf, huggingface.
- Use llama3.java when you require language model inference capabilities fully implemented in Java, ensuring consistency within Java-based projects.
When NOT to use llama3.java
- Avoid using llama3.java if your project needs specific features such as real-time chat integration that may be better supported by more specialized libraries.
- Do opt for a different tool if you prioritize performance metrics over the convenience of having an entirely Java-based solution, as competing tools might offer optimizations not found in llama3.java.
Choose exllama if…
- exllama is primarily Python; llama3.java is Java.
- Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu.
- Also covers LLM Frameworks.
- 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 (mukel/llama3.java) · observed Sep 20, 2026
- GitHub forks (mukel/llama3.java) · observed Sep 20, 2026
- Last push (mukel/llama3.java) · observed Apr 24, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (turboderp/exllama) · observed Sep 20, 2026
- GitHub forks (turboderp/exllama) · observed Sep 20, 2026
- Last push (turboderp/exllama) · observed Sep 30, 2023
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llama3.java 818 · exllama 2.9k (synced Sep 20, 2026).
Common questions
- What is the difference between llama3.java and exllama?
- llama3.java: Llama 3+ inference in pure Java. 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 llama3.java over exllama?
- Choose llama3.java over exllama when llama3.java is primarily Java; exllama is Python; Tags unique to llama3.java: chatgpt, genai, gguf, huggingface; Use llama3.java when you require language model inference capabilities fully implemented in Java, ensuring consistency within Java-based projects.
- When should I choose exllama over llama3.java?
- Choose exllama over llama3.java when exllama is primarily Python; llama3.java is Java; Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu; Also covers LLM Frameworks; 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 llama3.java?
- Avoid using llama3.java if your project needs specific features such as real-time chat integration that may be better supported by more specialized libraries. Do opt for a different tool if you prioritize performance metrics over the convenience of having an entirely Java-based solution, as competing tools might offer optimizations not found in llama3.java.
- 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 llama3.java or exllama more popular on GitHub?
- exllama has more GitHub stars (2,943 vs 818). Stars measure visibility, not whether either tool fits your constraints.
- Are llama3.java and exllama open source?
- Yes - both are open-source projects on GitHub (llama3.java: MIT, exllama: MIT).
- Where can I find alternatives to llama3.java or exllama?
- GraphCanon lists graph-backed alternatives at llama3.java alternatives and exllama alternatives (llama3.java 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, llama3.java or exllama?
- llama3.java: Slowing. 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 llama3.java and exllama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama3.java trust report; exllama trust report.