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Home/Compare/litellm vs ray-llm

Comparison

litellm vs ray-llm

Verdict

Pick litellm when pricing: While the core functionality is provided free, specific extended features might require a paid plan.; pick ray-llm when tags unique to ray-llm: ray, llm-serving.

Markdown twin · litellm alternatives · ray-llm alternatives

GraphCanon updated today

litellm logo

litellm

BerriAI/litellm

★ 53kpushed Jul 11, 2026
vs
ray-llm logo

ray-llm

ray-project/ray-llm

★ 1.3kpushed Mar 13, 2025

Trust & integrity

Signallitellmray-llm
Maintenance
Very active (0d since push)
As of today · github_public_v1
Archived (485d 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
litellm trust reportray-llm trust reportTrust methodology

Tagline

litellm
Python SDK and Proxy Server for calling multiple LLM APIs
ray-llm
RayLLM - LLMs on Ray (Archived). Read README for more info.

Stars

litellm
53k
ray-llm
1.3k

Forks

litellm
9.7k
ray-llm
90

Open issues

litellm
3.9k
ray-llm
0

Language

litellm
Python
ray-llm
-

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.
ray-llm
-

Persona

litellm
-
ray-llm
-

Runtime

litellm
-
ray-llm
-

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.
ray-llm
-

Last pushed

litellm
Jul 11, 2026
ray-llm
Mar 13, 2025

Categories

litellm
LLM Frameworks, Inference & Serving
ray-llm
LLM Frameworks, Inference & Serving

Trust and health

Maintenance

litellm
Very active (96%)
ray-llm
Archived (8%)

Days since push

litellm
0d
ray-llm
485d

Archived on GitHub

litellm
No
ray-llm
Yes

Open issues (now)

litellm
3.9k
ray-llm
0

Security scan

litellm
2 low (2 low)
ray-llm
No lockfile

Full report

litellm
Trust report
ray-llm
Trust report

Choose litellm if…

  • Pricing: While the core functionality is provided free, specific extended features might require a paid plan..
  • Requirements: Requires Docker.
  • Tags unique to litellm: bedrock, ai-gateway, openai, vertex-ai.
  • 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.
GitHubDetails

Choose ray-llm if…

  • Tags unique to ray-llm: ray, llm-serving.
  • Leaner open-issue backlog (0).

When NOT to use ray-llm

  • ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
  • 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.
GitHubDetails

Explore

litellm trust report →ray-llm trust report →LLM Frameworks category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: litellm 53k · ray-llm 1.3k (synced Jul 11, 2026).

Common questions

What is the difference between litellm and ray-llm?
litellm: Python SDK and Proxy Server for calling multiple LLM APIs. ray-llm: RayLLM - LLMs on Ray (Archived). Read README for more info.. See the comparison table for live GitHub stats and shared categories.
When should I choose litellm over ray-llm?
Choose litellm over ray-llm when Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: bedrock, ai-gateway, openai, vertex-ai; 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 ray-llm over litellm?
Choose ray-llm over litellm when Tags unique to ray-llm: ray, llm-serving; Leaner open-issue backlog (0).
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 ray-llm?
ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. 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 ray-llm more popular on GitHub?
litellm has more GitHub stars (53,271 vs 1,263). Stars measure visibility, not whether either tool fits your constraints.
Are litellm and ray-llm open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to litellm or ray-llm?
GraphCanon lists graph-backed alternatives at litellm alternatives and ray-llm alternatives (litellm markdown twin, ray-llm 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 ray-llm?
litellm: Very active. ray-llm: Archived. 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 ray-llm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litellm trust report; ray-llm trust report.