Comparison
gorilla vs cupel
Verdict
Pick gorilla if gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages; pick cupel if cupel is a JavaScript-based toolkit for discovering and evaluating the performance of large language models using configurable prompts, scoring mechanisms, multi-turn dialogues, and local inference server discovery.
Markdown twin · gorilla alternatives · cupel alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | gorilla | cupel |
|---|---|---|
| Maintenance | Slowing (147d since push) As of Sep 8, 2026 · github_public_v1 | Active (10d since push) As of Sep 10, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 8, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 10, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- gorilla
- Training and Evaluating LLMs for Function Calls (Tool Calls)
- cupel
- discovery tool for evaluating LLM performance
Stars
- gorilla
- 13k
- cupel
- 64
Forks
- gorilla
- 1.4k
- cupel
- 0
Open issues
- gorilla
- 278
- cupel
- 2
Language
- gorilla
- Python
- cupel
- Python
Adopt for
- gorilla
- Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
- cupel
- Cupel is a JavaScript-based toolkit for discovering and evaluating the performance of large language models using configurable prompts, scoring mechanisms, multi-turn dialogues, and local inference server discovery.
Persona
- gorilla
- -
- cupel
- -
Runtime
- gorilla
- -
- cupel
- -
License
- gorilla
- Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes.
- cupel
- Apache-2.0
Last pushed
- gorilla
- Apr 13, 2026
- cupel
- Aug 31, 2026
Categories
- gorilla
- Evaluation & Observability, Model Training
- cupel
- Evaluation & Observability
Trust and health
Maintenance
- gorilla
- Slowing (36%)
- cupel
- Active (82%)
Days since push
- gorilla
- 147d
- cupel
- 10d
Open issues (now)
- gorilla
- 278
- cupel
- 2
Stars delta
- gorilla
- +29 (30d)
- cupel
- +13 (30d)
Open issues delta
- gorilla
- +6 (30d)
- cupel
- 0 (30d)
Full report
- gorilla
- Trust report
- cupel
- Trust report
Shared compatibility
- Python · gorilla: Python runtime · cupel: Python runtime
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.
- Also covers Model Training.
- 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.
Choose cupel if…
- Tags unique to cupel: inference-servers-discovery, llm-evaluation, local-llm, multi-turn-dialogue.
- When aiming to evaluate LLMs on local servers due to its auto-discovery feature for known ports of inference servers
- More recently updated (last pushed Aug 31, 2026).
When NOT to use cupel
- If you require a solution that supports a non-JavaScript runtime environment, as Cupel is JavaScript-exclusive
- When you need a tool without UI capabilities since Cupel's UI is bundled in the package and may not suit headless operations
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ShishirPatil/gorilla) · observed Sep 20, 2026
- GitHub forks (ShishirPatil/gorilla) · observed Sep 20, 2026
- Last push (ShishirPatil/gorilla) · observed Apr 13, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tolitius/cupel) · observed Sep 20, 2026
- GitHub forks (tolitius/cupel) · observed Sep 20, 2026
- Last push (tolitius/cupel) · observed Aug 31, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: gorilla 13k · cupel 64 (synced Sep 20, 2026).
Common questions
- What is the difference between gorilla and cupel?
- gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). cupel: discovery tool for evaluating LLM performance. See the comparison table for live GitHub stats and shared categories.
- When should I choose gorilla over cupel?
- Choose gorilla over cupel 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; Also covers Model Training; You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively.
- When should I choose cupel over gorilla?
- Choose cupel over gorilla when Tags unique to cupel: inference-servers-discovery, llm-evaluation, local-llm, multi-turn-dialogue; When aiming to evaluate LLMs on local servers due to its auto-discovery feature for known ports of inference servers; More recently updated (last pushed Aug 31, 2026).
- 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.
- When should I avoid cupel?
- If you require a solution that supports a non-JavaScript runtime environment, as Cupel is JavaScript-exclusive When you need a tool without UI capabilities since Cupel's UI is bundled in the package and may not suit headless operations
- Is gorilla or cupel more popular on GitHub?
- gorilla has more GitHub stars (13,017 vs 64). Stars measure visibility, not whether either tool fits your constraints.
- Are gorilla and cupel open source?
- Yes - both are open-source projects on GitHub (gorilla: Apache-2.0, cupel: Apache-2.0).
- Where can I find alternatives to gorilla or cupel?
- GraphCanon lists graph-backed alternatives at gorilla alternatives and cupel alternatives (gorilla markdown twin, cupel 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, gorilla or cupel?
- gorilla: Slowing. cupel: 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 gorilla and cupel?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gorilla trust report; cupel trust report.