Comparison
dingo vs gorilla
Verdict
Pick dingo if dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks; pick gorilla if gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
Markdown twin · dingo alternatives · gorilla alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | dingo | 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 published findings from this source as of 2026-07-11 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
- dingo
- Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool
- gorilla
- Training and Evaluating LLMs for Function Calls (Tool Calls)
Stars
- dingo
- 733
- gorilla
- 13k
Forks
- dingo
- 74
- gorilla
- 1.4k
Open issues
- dingo
- 4
- gorilla
- 272
Language
- dingo
- Python
- gorilla
- Python
Adopt for
- dingo
- Dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks.
- gorilla
- Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
Persona
- dingo
- -
- gorilla
- -
Runtime
- dingo
- -
- gorilla
- -
License
- dingo
- Licensed under the Apache-2.0 license, it includes fasttext functionality for language detection, which itself is licensed under the MIT License.
- gorilla
- Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes.
Last pushed
- dingo
- Aug 6, 2026
- gorilla
- Apr 13, 2026
Categories
- dingo
- Data & Retrieval, Evaluation & Observability
- gorilla
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- dingo
- Very active (96%)
- gorilla
- Slowing (36%)
Days since push
- dingo
- 0d
- gorilla
- 117d
Open issues (now)
- dingo
- 4
- gorilla
- 272
Owner type
- dingo
- Organization
- gorilla
- User
OSV dependency advisories
- dingo
- No published findings from this source as of 2026-07-11
- gorilla
- No lockfile (source not queried)
Full report
- dingo
- Trust report
- gorilla
- Trust report
Choose dingo if…
- Pricing: The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost..
- Tags unique to dingo: agent-as-a-judge, data-evaluation, data-quality, hallucination-detection.
- Also covers Data & Retrieval.
- When evaluating the quality of data, models, or applications that require insights from multiple perspectives to detect nuances such as bias or hallucination.
When NOT to use dingo
- If your project does not benefit from a multi-agent approach for evaluation, and simpler single-model approaches suffice.
- In scenarios where immediate feedback is critical but Dingo's planned SaaS platform with API access and dashboard support are still under development.
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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (MigoXLab/dingo) · observed Aug 7, 2026
- GitHub forks (MigoXLab/dingo) · observed Aug 7, 2026
- Last push (MigoXLab/dingo) · observed Aug 6, 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: dingo 733 · gorilla 13k (synced Aug 7, 2026).
Common questions
- What is the difference between dingo and gorilla?
- dingo: Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool. 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 dingo over gorilla?
- Choose dingo over gorilla when Pricing: The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost.; Tags unique to dingo: agent-as-a-judge, data-evaluation, data-quality, hallucination-detection; Also covers Data & Retrieval; When evaluating the quality of data, models, or applications that require insights from multiple perspectives to detect nuances such as bias or hallucination.
- When should I choose gorilla over dingo?
- Choose gorilla over dingo 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 avoid dingo?
- If your project does not benefit from a multi-agent approach for evaluation, and simpler single-model approaches suffice. In scenarios where immediate feedback is critical but Dingo's planned SaaS platform with API access and dashboard support are still under development.
- 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 dingo or gorilla more popular on GitHub?
- gorilla has more GitHub stars (12,988 vs 733). Stars measure visibility, not whether either tool fits your constraints.
- Are dingo and gorilla open source?
- Yes - both are open-source projects on GitHub (dingo: Apache-2.0, gorilla: Apache-2.0).
- Where can I find alternatives to dingo or gorilla?
- GraphCanon lists graph-backed alternatives at dingo alternatives and gorilla alternatives (dingo 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, dingo or gorilla?
- dingo: 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 dingo and gorilla?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dingo trust report; gorilla trust report.