Comparison
litellm vs deep-research
Verdict
Pick litellm when litellm is primarily Python; deep-research is JavaScript; pick deep-research when deep-research is primarily JavaScript; litellm is Python.
Markdown twin · litellm alternatives · deep-research alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | litellm | deep-research |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3d · github_public_v1 | Active (26d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | Published findings As of 4d · osv@v1 | No lockfile (source not queried) As of today · 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
- litellm
- Python SDK and Proxy Server for calling multiple LLM APIs
- deep-research
- Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.
Stars
- litellm
- 53k
- deep-research
- 4.6k
Forks
- litellm
- 9.7k
- deep-research
- 1.1k
Open issues
- litellm
- 3.9k
- deep-research
- 36
Language
- litellm
- Python
- deep-research
- JavaScript
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.
- deep-research
- -
Persona
- litellm
- -
- deep-research
- -
Runtime
- litellm
- -
- deep-research
- -
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.
- deep-research
- MIT
Last pushed
- litellm
- Jul 11, 2026
- deep-research
- Jun 18, 2026
Categories
- litellm
- Inference & Serving, LLM Frameworks
- deep-research
- Inference & Serving, LLM Frameworks, Vector Databases
Trust and health
Maintenance
- litellm
- Very active (96%)
- deep-research
- Active (82%)
Days since push
- litellm
- 0d
- deep-research
- 26d
Open issues (now)
- litellm
- 3.9k
- deep-research
- 36
OSV dependency advisories
- litellm
- Published findings
- deep-research
- No lockfile (source not queried)
Full report
- litellm
- Trust report
- deep-research
- Trust report
Choose litellm if…
- litellm is primarily Python; deep-research is JavaScript.
- License: litellm is Other, deep-research is MIT.
- Pricing: While the core functionality is provided free, specific extended features might require a paid plan..
- Requirements: Requires Docker.
- Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm.
- 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 deep-research if…
- deep-research is primarily JavaScript; litellm is Python.
- License: deep-research is MIT, litellm is Other.
- Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch.
- Also covers Vector Databases.
When NOT to use deep-research
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
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 (u14app/deep-research) · observed Jul 15, 2026
- GitHub forks (u14app/deep-research) · observed Jul 15, 2026
- Last push (u14app/deep-research) · observed Jun 18, 2026
- License file (MIT) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: litellm 53k · deep-research 4.6k (synced Jul 11, 2026).
Common questions
- What is the difference between litellm and deep-research?
- litellm: Python SDK and Proxy Server for calling multiple LLM APIs. deep-research: Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.. See the comparison table for live GitHub stats and shared categories.
- When should I choose litellm over deep-research?
- Choose litellm over deep-research when litellm is primarily Python; deep-research is JavaScript; License: litellm is Other, deep-research is MIT; Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm; 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 deep-research over litellm?
- Choose deep-research over litellm when deep-research is primarily JavaScript; litellm is Python; License: deep-research is MIT, litellm is Other; Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch; Also covers Vector Databases.
- 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 deep-research?
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is litellm or deep-research more popular on GitHub?
- litellm has more GitHub stars (53,271 vs 4,632). Stars measure visibility, not whether either tool fits your constraints.
- Are litellm and deep-research open source?
- Yes - both are open-source projects on GitHub (litellm: Other, deep-research: MIT).
- Where can I find alternatives to litellm or deep-research?
- GraphCanon lists graph-backed alternatives at litellm alternatives and deep-research alternatives (litellm markdown twin, deep-research 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 deep-research?
- litellm: Very active. deep-research: 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 deep-research?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litellm trust report; deep-research trust report.