Comparison
litellm vs Awesome-LLM-Inference
Verdict
Pick litellm when license: litellm is Other, Awesome-LLM-Inference is GPL-3.0; pick Awesome-LLM-Inference when license: Awesome-LLM-Inference is GPL-3.0, litellm is Other.
Markdown twin · litellm alternatives · Awesome-LLM-Inference alternatives
GraphCanon updated today
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Trust & integrity
| Signal | litellm | Awesome-LLM-Inference |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Active (18d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | 2 low (2 low) As of today · osv@v1 | No lockfile As of today · none |
Tagline
- litellm
- Python SDK and Proxy Server for calling multiple LLM APIs
- Awesome-LLM-Inference
- 📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉
Stars
- litellm
- 53k
- Awesome-LLM-Inference
- 5.4k
Forks
- litellm
- 9.7k
- Awesome-LLM-Inference
- 421
Open issues
- litellm
- 3.9k
- Awesome-LLM-Inference
- 4
Language
- litellm
- Python
- Awesome-LLM-Inference
- Python
Adopt for
- litellm
- litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging.
- Awesome-LLM-Inference
- -
Persona
- litellm
- -
- Awesome-LLM-Inference
- -
Runtime
- litellm
- -
- Awesome-LLM-Inference
- -
License
- litellm
- The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source.
- Awesome-LLM-Inference
- GPL-3.0
Last pushed
- litellm
- Jul 11, 2026
- Awesome-LLM-Inference
- Jun 23, 2026
Categories
- litellm
- LLM Frameworks, Inference & Serving
- Awesome-LLM-Inference
- LLM Frameworks, Inference & Serving
Trust and health
Maintenance
- litellm
- Very active (96%)
- Awesome-LLM-Inference
- Active (82%)
Days since push
- litellm
- 0d
- Awesome-LLM-Inference
- 18d
Open issues (now)
- litellm
- 3.9k
- Awesome-LLM-Inference
- 4
Security scan
- litellm
- 2 low (2 low)
- Awesome-LLM-Inference
- No lockfile
Full report
- litellm
- Trust report
- Awesome-LLM-Inference
- Trust report
Choose litellm if…
- License: litellm is Other, Awesome-LLM-Inference is GPL-3.0.
- Pricing: While the core functionality is provided free, specific extended features might require a paid plan..
- Requirements: Requires Docker.
- Tags unique to litellm: llm, bedrock, ai-gateway, openai.
- litellm ships Docker support for self-hosted deployment.
- When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging
When NOT to use litellm
- If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill.
Choose Awesome-LLM-Inference if…
- License: Awesome-LLM-Inference is GPL-3.0, litellm is Other.
- Tags unique to Awesome-LLM-Inference: deepseek-r1, deepseek-v3, deepseek, flash-mla.
- Leaner open-issue backlog (4).
When NOT to use Awesome-LLM-Inference
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (BerriAI/litellm) · observed Jul 11, 2026
- GitHub forks (BerriAI/litellm) · observed Jul 11, 2026
- Last push (BerriAI/litellm) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (xlite-dev/Awesome-LLM-Inference) · observed Jul 11, 2026
- GitHub forks (xlite-dev/Awesome-LLM-Inference) · observed Jul 11, 2026
- Last push (xlite-dev/Awesome-LLM-Inference) · observed Jun 23, 2026
- License file (GPL-3.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: litellm 53k · Awesome-LLM-Inference 5.4k (synced Jul 11, 2026).
Common questions
- What is the difference between litellm and Awesome-LLM-Inference?
- litellm: Python SDK and Proxy Server for calling multiple LLM APIs. Awesome-LLM-Inference: 📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉. See the comparison table for live GitHub stats and shared categories.
- When should I choose litellm over Awesome-LLM-Inference?
- Choose litellm over Awesome-LLM-Inference when License: litellm is Other, Awesome-LLM-Inference is GPL-3.0; Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: llm, bedrock, ai-gateway, openai; litellm ships Docker support for self-hosted deployment; When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging.
- When should I choose Awesome-LLM-Inference over litellm?
- Choose Awesome-LLM-Inference over litellm when License: Awesome-LLM-Inference is GPL-3.0, litellm is Other; Tags unique to Awesome-LLM-Inference: deepseek-r1, deepseek-v3, deepseek, flash-mla; Leaner open-issue backlog (4).
- When should I avoid litellm?
- If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill.
- When should I avoid Awesome-LLM-Inference?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Is litellm or Awesome-LLM-Inference more popular on GitHub?
- litellm has more GitHub stars (53,271 vs 5,383). Stars measure visibility, not whether either tool fits your constraints.
- Are litellm and Awesome-LLM-Inference open source?
- Yes - both are open-source projects on GitHub (litellm: Other, Awesome-LLM-Inference: GPL-3.0).
- Where can I find alternatives to litellm or Awesome-LLM-Inference?
- GraphCanon lists graph-backed alternatives at litellm alternatives and Awesome-LLM-Inference alternatives (litellm markdown twin, Awesome-LLM-Inference 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, litellm or Awesome-LLM-Inference?
- litellm: Very active. Awesome-LLM-Inference: 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 litellm and Awesome-LLM-Inference?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litellm trust report; Awesome-LLM-Inference trust report.