Comparison
exllama vs xllm
Verdict
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; pick xllm if a high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation.
Markdown twin · exllama alternatives · xllm alternatives
GraphCanon updated Sep 20, 2026
9views this month
Trust & integrity
| Signal | exllama | xllm |
|---|---|---|
| Maintenance | Dormant (1072d since push) As of Sep 7, 2026 · github_public_v1 | Very active (0d since push) As of Sep 19, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 19, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) 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
- exllama
- Memory-efficient rewrite of HF transformers for Llama with quantized weights
- xllm
- A high-performance inference engine for LLM, VLM, DiT and REC models
Stars
- exllama
- 2.9k
- xllm
- 1.6k
Forks
- exllama
- 220
- xllm
- 300
Open issues
- exllama
- 65
- xllm
- 211
Language
- exllama
- Python
- xllm
- C++
Adopt for
- 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.
- xllm
- A high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation.
Persona
- exllama
- -
- xllm
- -
Runtime
- exllama
- -
- xllm
- -
License
- exllama
- MIT
- xllm
- Apache-2.0
Last pushed
- exllama
- Sep 30, 2023
- xllm
- Sep 19, 2026
Categories
- exllama
- Inference & Serving, LLM Frameworks
- xllm
- Inference & Serving
Trust and health
Maintenance
- exllama
- Dormant (18%)
- xllm
- Very active (96%)
Days since push
- exllama
- 1072d
- xllm
- 0d
Open issues (now)
- exllama
- 65
- xllm
- 211
Stars delta
- exllama
- +6 (30d)
- xllm
- +84 (30d)
Open issues delta
- exllama
- 0 (30d)
- xllm
- +20 (30d)
Owner type
- exllama
- User
- xllm
- Organization
OSV dependency advisories
- exllama
- Published findings
- xllm
- No lockfile (source not queried)
Full report
- exllama
- Trust report
- xllm
- Trust report
Choose exllama if…
- exllama is primarily Python; xllm is C++.
- License: exllama is MIT, xllm is Apache-2.0.
- 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).
Choose xllm if…
- xllm is primarily C++; exllama is Python.
- License: xllm is Apache-2.0, exllama is MIT.
- Tags unique to xllm: deepseek, glm, llm-inference.
- When developing applications that require optimized performance on various AI accelerators
When NOT to use xllm
- If your project strictly requires Python-based inference engines for backend support
- In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (xLLM-AI/xllm) · observed Sep 20, 2026
- GitHub forks (xLLM-AI/xllm) · observed Sep 20, 2026
- Last push (xLLM-AI/xllm) · observed Sep 19, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: exllama 2.9k · xllm 1.6k (synced Sep 20, 2026).
Common questions
- What is the difference between exllama and xllm?
- exllama: Memory-efficient rewrite of HF transformers for Llama with quantized weights. xllm: A high-performance inference engine for LLM, VLM, DiT and REC models. See the comparison table for live GitHub stats and shared categories.
- When should I choose exllama over xllm?
- Choose exllama over xllm when exllama is primarily Python; xllm is C++; License: exllama is MIT, xllm is Apache-2.0; 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 choose xllm over exllama?
- Choose xllm over exllama when xllm is primarily C++; exllama is Python; License: xllm is Apache-2.0, exllama is MIT; Tags unique to xllm: deepseek, glm, llm-inference; When developing applications that require optimized performance on various AI accelerators.
- 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).
- When should I avoid xllm?
- If your project strictly requires Python-based inference engines for backend support In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here
- Is exllama or xllm more popular on GitHub?
- exllama has more GitHub stars (2,943 vs 1,577). Stars measure visibility, not whether either tool fits your constraints.
- Are exllama and xllm open source?
- Yes - both are open-source projects on GitHub (exllama: MIT, xllm: Apache-2.0).
- Where can I find alternatives to exllama or xllm?
- GraphCanon lists graph-backed alternatives at exllama alternatives and xllm alternatives (exllama markdown twin, xllm 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, exllama or xllm?
- exllama: Dormant. xllm: Very active. 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 exllama and xllm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: exllama trust report; xllm trust report.