Comparison
litellm vs long-context-attention
Verdict
Pick litellm when license: litellm is Other, long-context-attention is Apache-2.0; pick long-context-attention when license: long-context-attention is Apache-2.0, litellm is Other.
Markdown twin · litellm alternatives · long-context-attention alternatives
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Trust & integrity
| Signal | litellm | long-context-attention |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Steady (51d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | 2 low (2 low) As of 1d · osv@v1 | No lockfile As of today · none |
Tagline
- litellm
- Python SDK and Proxy Server for calling multiple LLM APIs
- long-context-attention
- USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference
Stars
- litellm
- 53k
- long-context-attention
- 678
Forks
- litellm
- 9.7k
- long-context-attention
- 80
Open issues
- litellm
- 3.9k
- long-context-attention
- 12
Language
- litellm
- Python
- long-context-attention
- 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.
- long-context-attention
- -
Persona
- litellm
- -
- long-context-attention
- -
Runtime
- litellm
- -
- long-context-attention
- -
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.
- long-context-attention
- Apache-2.0
Last pushed
- litellm
- Jul 11, 2026
- long-context-attention
- May 21, 2026
Categories
- litellm
- Inference & Serving, LLM Frameworks
- long-context-attention
- Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- litellm
- Very active (96%)
- long-context-attention
- Steady (60%)
Days since push
- litellm
- 0d
- long-context-attention
- 51d
Open issues (now)
- litellm
- 3.9k
- long-context-attention
- 12
Owner type
- litellm
- Organization
- long-context-attention
- User
Security scan
- litellm
- 2 low (2 low)
- long-context-attention
- No lockfile
Full report
- litellm
- Trust report
- long-context-attention
- Trust report
Choose litellm if…
- License: litellm is Other, long-context-attention is Apache-2.0.
- 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.
- 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 long-context-attention if…
- License: long-context-attention is Apache-2.0, litellm is Other.
- Tags unique to long-context-attention: attention-is-all-you-need, deepspeed-ulysses, llm-inference, llm-training.
- Also covers Model Training.
When NOT to use long-context-attention
- 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.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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 (feifeibear/long-context-attention) · observed Jul 11, 2026
- GitHub forks (feifeibear/long-context-attention) · observed Jul 11, 2026
- Last push (feifeibear/long-context-attention) · observed May 21, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: litellm 53k · long-context-attention 678 (synced Jul 11, 2026).
Common questions
- What is the difference between litellm and long-context-attention?
- litellm: Python SDK and Proxy Server for calling multiple LLM APIs. long-context-attention: USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference. See the comparison table for live GitHub stats and shared categories.
- When should I choose litellm over long-context-attention?
- Choose litellm over long-context-attention when License: litellm is Other, long-context-attention is Apache-2.0; 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; 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 long-context-attention over litellm?
- Choose long-context-attention over litellm when License: long-context-attention is Apache-2.0, litellm is Other; Tags unique to long-context-attention: attention-is-all-you-need, deepspeed-ulysses, llm-inference, llm-training; Also covers Model Training.
- 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 long-context-attention?
- 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. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is litellm or long-context-attention more popular on GitHub?
- litellm has more GitHub stars (53,271 vs 678). Stars measure visibility, not whether either tool fits your constraints.
- Are litellm and long-context-attention open source?
- Yes - both are open-source projects on GitHub (litellm: Other, long-context-attention: Apache-2.0).
- Where can I find alternatives to litellm or long-context-attention?
- GraphCanon lists graph-backed alternatives at litellm alternatives and long-context-attention alternatives (litellm markdown twin, long-context-attention 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 long-context-attention?
- litellm: Very active. long-context-attention: Steady. 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 long-context-attention?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litellm trust report; long-context-attention trust report.