Comparison
REST vs raptor
Verdict
Pick REST if rEST is a retrieval-based speculative decoding tool implemented in C, designed for use cases that demand efficiency and fine-grained control over inference processes through its distinctive approach; pick raptor if a specialized tool with a unique recursive abstractive processing approach for retrieval-augmented generation.
Markdown twin · REST alternatives · raptor alternatives
GraphCanon updated today
Trust & integrity
| Signal | REST | raptor |
|---|---|---|
| Maintenance | Slowing (128d since push) As of today · github_public_v1 | Dormant (676d 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 today · osv@v1 | No lockfile As of today · none |
Tagline
- REST
- REST: Retrieval-Based Speculative Decoding
- raptor
- The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Stars
- REST
- 220
- raptor
- 1.7k
Forks
- REST
- 17
- raptor
- 231
Open issues
- REST
- 15
- raptor
- 45
Language
- REST
- C
- raptor
- Python
Adopt for
- REST
- REST is a retrieval-based speculative decoding tool implemented in C, designed for use cases that demand efficiency and fine-grained control over inference processes through its distinctive approach.
- raptor
- A specialized tool with a unique recursive abstractive processing approach for retrieval-augmented generation
Persona
- REST
- -
- raptor
- -
Runtime
- REST
- -
- raptor
- -
License
- REST
- Apache-2.0
- raptor
- Released under the permissive MIT license, allowing free integration into various projects with attribution
Last pushed
- REST
- Mar 5, 2026
- raptor
- Sep 3, 2024
Categories
- REST
- Data & Retrieval, Inference & Serving
- raptor
- LLM Frameworks, AI Agents, Vector Databases
Trust and health
Maintenance
- REST
- Slowing (36%)
- raptor
- Dormant (18%)
Days since push
- REST
- 128d
- raptor
- 676d
Open issues (now)
- REST
- 15
- raptor
- 45
Owner type
- REST
- Organization
- raptor
- User
Security scan
- REST
- 2 low (2 low)
- raptor
- No lockfile
Full report
- REST
- Trust report
- raptor
- Trust report
Choose REST if…
- REST is primarily C; raptor is Python.
- License: REST is Apache-2.0, raptor is MIT.
- Tags unique to REST: speculative-decoding, llm-inference.
- Also covers Data & Retrieval, Inference & Serving.
- - When you need high performance and are willing to work with the C language for customization and optimization.
When NOT to use REST
- - Avoid if your team lacks proficiency in C programming as this may lead to an overhead in developing and maintaining the tool.
- - Not recommended for projects where flexibility with commonly used high-level languages like Python is essential, as REST primarily relies on lower-level language capabilities.
Choose raptor if…
- raptor is primarily Python; REST is C.
- License: raptor is MIT, REST is Apache-2.0.
- Requirements: Min 4 GB RAM; Requires Python 3.8 or higher; Dependencies listed in requirements.txt must be installed.
- Tags unique to raptor: clustering, agents, llm, machine-learning.
- Also covers LLM Frameworks, AI Agents, Vector Databases.
- When you need an innovative approach to retrieve and generate content recursively using tree-organized structures.
When NOT to use raptor
- Avoid RAPTOR if your project requires simple or straightforward retrieval methods without advanced recursive abstractive processes.
- Not recommended if rapid iteration is prioritized over deep abstraction; RAPTOR's complex approach might slow down quick testing cycles.
- If you're constrained by the MIT License terms, which offer limited protection against patent claims from contributors, use caution.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (FasterDecoding/REST) · observed Jul 11, 2026
- GitHub forks (FasterDecoding/REST) · observed Jul 11, 2026
- Last push (FasterDecoding/REST) · observed Mar 5, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (parthsarthi03/raptor) · observed Jul 11, 2026
- GitHub forks (parthsarthi03/raptor) · observed Jul 11, 2026
- Last push (parthsarthi03/raptor) · observed Sep 3, 2024
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: REST 220 · raptor 1.7k (synced Jul 11, 2026).
Common questions
- What is the difference between REST and raptor?
- REST: REST: Retrieval-Based Speculative Decoding. raptor: The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval. See the comparison table for live GitHub stats and shared categories.
- When should I choose REST over raptor?
- Choose REST over raptor when REST is primarily C; raptor is Python; License: REST is Apache-2.0, raptor is MIT; Tags unique to REST: speculative-decoding, llm-inference; Also covers Data & Retrieval, Inference & Serving; - When you need high performance and are willing to work with the C language for customization and optimization.
- When should I choose raptor over REST?
- Choose raptor over REST when raptor is primarily Python; REST is C; License: raptor is MIT, REST is Apache-2.0; Requirements: Min 4 GB RAM; Requires Python 3.8 or higher; Dependencies listed in requirements.txt must be installed; Tags unique to raptor: clustering, agents, llm, machine-learning; Also covers LLM Frameworks, AI Agents, Vector Databases; When you need an innovative approach to retrieve and generate content recursively using tree-organized structures.
- When should I avoid REST?
- - Avoid if your team lacks proficiency in C programming as this may lead to an overhead in developing and maintaining the tool. - Not recommended for projects where flexibility with commonly used high-level languages like Python is essential, as REST primarily relies on lower-level language capabilities.
- When should I avoid raptor?
- Avoid RAPTOR if your project requires simple or straightforward retrieval methods without advanced recursive abstractive processes. Not recommended if rapid iteration is prioritized over deep abstraction; RAPTOR's complex approach might slow down quick testing cycles. If you're constrained by the MIT License terms, which offer limited protection against patent claims from contributors, use caution.
- Is REST or raptor more popular on GitHub?
- raptor has more GitHub stars (1,723 vs 220). Stars measure visibility, not whether either tool fits your constraints.
- Are REST and raptor open source?
- Yes - both are open-source projects on GitHub (REST: Apache-2.0, raptor: MIT).
- Where can I find alternatives to REST or raptor?
- GraphCanon lists graph-backed alternatives at REST alternatives and raptor alternatives (REST markdown twin, raptor 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, REST or raptor?
- REST: Slowing. raptor: Dormant. 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 REST and raptor?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: REST trust report; raptor trust report.