Comparison
LlamaFactory vs infinity
Verdict
Pick LlamaFactory if 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; pick infinity if infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT.
Markdown twin · LlamaFactory alternatives · infinity alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | LlamaFactory | infinity |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Slowing (109d 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 | No lockfile As of today · none |
Tagline
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- infinity
- High-throughput, low-latency serving engine for text-embeddings and various models
Stars
- LlamaFactory
- 73k
- infinity
- 2.9k
Forks
- LlamaFactory
- 8.9k
- infinity
- 196
Open issues
- LlamaFactory
- 1.1k
- infinity
- 130
Language
- LlamaFactory
- Python
- infinity
- Python
Adopt for
- 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.
- infinity
- Infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT.
Persona
- LlamaFactory
- -
- infinity
- -
Runtime
- LlamaFactory
- -
- infinity
- -
License
- LlamaFactory
- Apache-2.0
- infinity
- MIT
Last pushed
- LlamaFactory
- Jul 10, 2026
- infinity
- Mar 24, 2026
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- infinity
- Inference & Serving
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- infinity
- Slowing (36%)
Days since push
- LlamaFactory
- 0d
- infinity
- 109d
Open issues (now)
- LlamaFactory
- 1.1k
- infinity
- 130
Full report
- LlamaFactory
- Trust report
- infinity
- Trust report
Choose LlamaFactory if…
- License: LlamaFactory is Apache-2.0, infinity is MIT.
- Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning.
- Also covers LLM Frameworks, Model Training.
- 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
Choose infinity if…
- License: infinity is MIT, LlamaFactory is Apache-2.0.
- Tags unique to infinity: clap, clip, colpali, docker-container.
- Also covers Inference & Serving.
- When you need to serve embeddings and various models with high throughput and low latency.
When NOT to use infinity
- Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity.
- Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking).
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hiyouga/LlamaFactory) · observed Jul 11, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Jul 11, 2026
- Last push (hiyouga/LlamaFactory) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (michaelfeil/infinity) · observed Jul 11, 2026
- GitHub forks (michaelfeil/infinity) · observed Jul 11, 2026
- Last push (michaelfeil/infinity) · observed Mar 24, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 73k · infinity 2.9k (synced Jul 11, 2026).
Common questions
- What is the difference between LlamaFactory and infinity?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. infinity: High-throughput, low-latency serving engine for text-embeddings and various models. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over infinity?
- Choose LlamaFactory over infinity when License: LlamaFactory is Apache-2.0, infinity is MIT; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; Also covers LLM Frameworks, Model Training; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- When should I choose infinity over LlamaFactory?
- Choose infinity over LlamaFactory when License: infinity is MIT, LlamaFactory is Apache-2.0; Tags unique to infinity: clap, clip, colpali, docker-container; Also covers Inference & Serving; When you need to serve embeddings and various models with high throughput and low latency.
- 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
- When should I avoid infinity?
- Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity. Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking).
- Is LlamaFactory or infinity more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 2,874). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and infinity open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, infinity: MIT).
- Where can I find alternatives to LlamaFactory or infinity?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and infinity alternatives (LlamaFactory markdown twin, infinity 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, LlamaFactory or infinity?
- LlamaFactory: Very active. infinity: Slowing. 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 LlamaFactory and infinity?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; infinity trust report.