Comparison
ROLL vs gorilla
Verdict
Pick ROLL if efficient library for scaling reinforcement learning tasks with large language models; user-friendly setup and debugging tools provided; pick gorilla if gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
Markdown twin · ROLL alternatives · gorilla alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | ROLL | gorilla |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Slowing (117d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- ROLL
- Scaling Library for Reinforcement Learning with Large Language Models
- gorilla
- Training and Evaluating LLMs for Function Calls (Tool Calls)
Stars
- ROLL
- 3.4k
- gorilla
- 13k
Forks
- ROLL
- 304
- gorilla
- 1.4k
Open issues
- ROLL
- 120
- gorilla
- 272
Language
- ROLL
- Python
- gorilla
- Python
Adopt for
- ROLL
- Efficient library for scaling reinforcement learning tasks with large language models; user-friendly setup and debugging tools provided.
- gorilla
- Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
Persona
- ROLL
- -
- gorilla
- -
Runtime
- ROLL
- -
- gorilla
- -
License
- ROLL
- Apache-2.0
- gorilla
- Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes.
Last pushed
- ROLL
- Aug 7, 2026
- gorilla
- Apr 13, 2026
Categories
- ROLL
- Evaluation & Observability, Model Training
- gorilla
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- ROLL
- Very active (96%)
- gorilla
- Slowing (36%)
Days since push
- ROLL
- 0d
- gorilla
- 117d
Open issues (now)
- ROLL
- 120
- gorilla
- 272
Owner type
- ROLL
- Organization
- gorilla
- User
Full report
- ROLL
- Trust report
- gorilla
- Trust report
Choose ROLL if…
- Tags unique to ROLL: agentic, rlhf, rlvr.
- When developing reinforcement learning applications requiring integration of large language models, offering efficient scalability solutions.
- More recently updated (last pushed Aug 7, 2026).
When NOT to use ROLL
- Avoid for tasks that prioritize minimalist setups over advanced feature integrations like Alibaba Cloud Function Compute DevPods.
- Not suitable if you prefer tools without built-in support for converting models between MCoreAdapter and Hugging Face formats.
Choose gorilla if…
- Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning..
- Tags unique to gorilla: api, chatgpt, claude-api, gpt-4-api.
- You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively.
When NOT to use gorilla
- Avoid Gorilla if your primary focus is not on function calling or tool usage capabilities for LLMs; another model-specific framework may better fit your needs.
- If the lack of a direct comparison tool to other models' function-calling performance is critical in your decision process, and you find no suitable alternatives listed on their leaderboard.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (alibaba/ROLL) · observed Aug 7, 2026
- GitHub forks (alibaba/ROLL) · observed Aug 7, 2026
- Last push (alibaba/ROLL) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ShishirPatil/gorilla) · observed Aug 8, 2026
- GitHub forks (ShishirPatil/gorilla) · observed Aug 8, 2026
- Last push (ShishirPatil/gorilla) · observed Apr 13, 2026
- License file (Apache-2.0) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ROLL 3.4k · gorilla 13k (synced Aug 7, 2026).
Common questions
- What is the difference between ROLL and gorilla?
- ROLL: Scaling Library for Reinforcement Learning with Large Language Models. gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). See the comparison table for live GitHub stats and shared categories.
- When should I choose ROLL over gorilla?
- Choose ROLL over gorilla when Tags unique to ROLL: agentic, rlhf, rlvr; When developing reinforcement learning applications requiring integration of large language models, offering efficient scalability solutions; More recently updated (last pushed Aug 7, 2026).
- When should I choose gorilla over ROLL?
- Choose gorilla over ROLL when Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning.; Tags unique to gorilla: api, chatgpt, claude-api, gpt-4-api; You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively.
- When should I avoid ROLL?
- Avoid for tasks that prioritize minimalist setups over advanced feature integrations like Alibaba Cloud Function Compute DevPods. Not suitable if you prefer tools without built-in support for converting models between MCoreAdapter and Hugging Face formats.
- When should I avoid gorilla?
- Avoid Gorilla if your primary focus is not on function calling or tool usage capabilities for LLMs; another model-specific framework may better fit your needs. If the lack of a direct comparison tool to other models' function-calling performance is critical in your decision process, and you find no suitable alternatives listed on their leaderboard.
- Is ROLL or gorilla more popular on GitHub?
- gorilla has more GitHub stars (12,988 vs 3,354). Stars measure visibility, not whether either tool fits your constraints.
- Are ROLL and gorilla open source?
- Yes - both are open-source projects on GitHub (ROLL: Apache-2.0, gorilla: Apache-2.0).
- Where can I find alternatives to ROLL or gorilla?
- GraphCanon lists graph-backed alternatives at ROLL alternatives and gorilla alternatives (ROLL markdown twin, gorilla 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, ROLL or gorilla?
- ROLL: Very active. gorilla: Slowing. 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 ROLL and gorilla?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ROLL trust report; gorilla trust report.