Home/Compare/awadb vs LlamaFactory

Comparison

awadb vs LlamaFactory

Verdict

Pick awadb when awadb is primarily C++; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; awadb is C++.

Markdown twin · awadb alternatives · LlamaFactory alternatives

GraphCanon updated today

awadb logo

awadb

awa-ai/awadb

175pushed Nov 4, 2024
vs
LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

73kpushed Jul 10, 2026

Trust & integrity

SignalawadbLlamaFactory
Maintenance
Dormant (614d since push)
As of today · github_public_v1
Very active (0d 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 criticals
As of today · osv@v1
No lockfile
As of today · none

Tagline

awadb
AI Native database for embedding vectors
LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs

Stars

awadb
175
LlamaFactory
73k

Forks

awadb
16
LlamaFactory
8.9k

Open issues

awadb
4
LlamaFactory
1.1k

Language

awadb
C++
LlamaFactory
Python

Adopt for

awadb
-
LlamaFactory
LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.

Persona

awadb
-
LlamaFactory
-

Runtime

awadb
-
LlamaFactory
-

License

awadb
Apache-2.0
LlamaFactory
Apache-2.0

Last pushed

awadb
Nov 4, 2024
LlamaFactory
Jul 10, 2026

Categories

awadb
Vector Databases, LLM Frameworks, Model Training
LlamaFactory
LLM Frameworks, Model Training

Trust and health

Maintenance

awadb
Dormant (18%)
LlamaFactory
Very active (96%)

Days since push

awadb
614d
LlamaFactory
0d

Open issues (now)

awadb
4
LlamaFactory
1.1k

Security scan

awadb
No criticals
LlamaFactory
No lockfile

Full report

LlamaFactory
Trust report

Choose awadb if…

  • awadb is primarily C++; LlamaFactory is Python.
  • Tags unique to awadb: embedding-vectors, llm, vectordb, chatgpt.
  • Also covers Vector Databases.

When NOT to use awadb

  • Last GitHub push was 615 days ago (dormant maintenance, Nov 4, 2024). Validate activity before betting a new project on awadb.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Choose LlamaFactory if…

  • LlamaFactory is primarily Python; awadb is C++.
  • Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai.
  • When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.

When NOT to use LlamaFactory

  • When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
  • If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa

Explore

Sources

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

GitHub stars on cards: awadb 175 · LlamaFactory 73k (synced Jul 11, 2026).

Common questions

What is the difference between awadb and LlamaFactory?
awadb: AI Native database for embedding vectors. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose awadb over LlamaFactory?
Choose awadb over LlamaFactory when awadb is primarily C++; LlamaFactory is Python; Tags unique to awadb: embedding-vectors, llm, vectordb, chatgpt; Also covers Vector Databases.
When should I choose LlamaFactory over awadb?
Choose LlamaFactory over awadb when LlamaFactory is primarily Python; awadb is C++; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When should I avoid awadb?
Last GitHub push was 615 days ago (dormant maintenance, Nov 4, 2024). Validate activity before betting a new project on awadb. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
When should I avoid LlamaFactory?
When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Is awadb or LlamaFactory more popular on GitHub?
LlamaFactory has more GitHub stars (73,157 vs 175). Stars measure visibility, not whether either tool fits your constraints.
Are awadb and LlamaFactory open source?
Yes - both are open-source projects on GitHub (awadb: Apache-2.0, LlamaFactory: Apache-2.0).
Where can I find alternatives to awadb or LlamaFactory?
GraphCanon lists graph-backed alternatives at awadb alternatives and LlamaFactory alternatives (awadb markdown twin, LlamaFactory 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, awadb or LlamaFactory?
awadb: Dormant. LlamaFactory: 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 awadb and LlamaFactory?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awadb trust report; LlamaFactory trust report.