Comparison
gorilla vs textgrad
Verdict
Pick gorilla if gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages; pick textgrad if textGrad optimizes prompts using large language models to backpropagate textual gradients.
Markdown twin · gorilla alternatives · textgrad alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | gorilla | textgrad |
|---|---|---|
| Maintenance | Slowing (117d since push) As of 1w · github_public_v1 | Dormant (388d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- gorilla
- Training and Evaluating LLMs for Function Calls (Tool Calls)
- textgrad
- Automatic 'Differentiation' via Text using Large Language Models to Backpropagate Textual Gradients
Stars
- gorilla
- 13k
- textgrad
- 3.7k
Forks
- gorilla
- 1.4k
- textgrad
- 294
Open issues
- gorilla
- 272
- textgrad
- 66
Language
- gorilla
- Python
- textgrad
- Python
Adopt for
- gorilla
- Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
- textgrad
- TextGrad optimizes prompts using large language models to backpropagate textual gradients.
Persona
- gorilla
- -
- textgrad
- -
Runtime
- gorilla
- -
- textgrad
- -
License
- gorilla
- Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes.
- textgrad
- MIT
Last pushed
- gorilla
- Apr 13, 2026
- textgrad
- Jul 25, 2025
Categories
- gorilla
- Evaluation & Observability, Model Training
- textgrad
- Model Training
Trust and health
Maintenance
- gorilla
- Slowing (36%)
- textgrad
- Dormant (18%)
Days since push
- gorilla
- 117d
- textgrad
- 388d
Open issues (now)
- gorilla
- 272
- textgrad
- 66
Stars delta
- gorilla
- Unknown
- textgrad
- +44 (30d)
Open issues delta
- gorilla
- Unknown
- textgrad
- 0 (30d)
Owner type
- gorilla
- User
- textgrad
- Organization
OSV dependency advisories
- gorilla
- No lockfile (source not queried)
- textgrad
- Published findings
Full report
- gorilla
- Trust report
- textgrad
- Trust report
Shared compatibility
- Python · gorilla: Python runtime · textgrad: Python runtime
Choose gorilla if…
- License: gorilla is Apache-2.0, textgrad is MIT.
- 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 Evaluation & Observability.
- 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 textgrad if…
- License: textgrad is MIT, gorilla is Apache-2.0.
- Tags unique to textgrad: ai_optimization, compound-systems, large language models, prompt-optimization.
- When optimizing complex prompting for large language models in production due to its published effectiveness.
When NOT to use textgrad
- If only basic and traditional manual tuning methods are needed for simpler use cases.
- Avoid if strict version control is required since the bleeding edge installation points to GitHub directly.
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 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 (zou-group/textgrad) · observed Aug 18, 2026
- GitHub forks (zou-group/textgrad) · observed Aug 18, 2026
- Last push (zou-group/textgrad) · observed Jul 25, 2025
- License file (MIT) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gorilla 13k · textgrad 3.7k (synced Aug 8, 2026).
Common questions
- What is the difference between gorilla and textgrad?
- gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). textgrad: Automatic 'Differentiation' via Text using Large Language Models to Backpropagate Textual Gradients. See the comparison table for live GitHub stats and shared categories.
- When should I choose gorilla over textgrad?
- Choose gorilla over textgrad when License: gorilla is Apache-2.0, textgrad is MIT; 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 Evaluation & Observability; You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively.
- When should I choose textgrad over gorilla?
- Choose textgrad over gorilla when License: textgrad is MIT, gorilla is Apache-2.0; Tags unique to textgrad: ai_optimization, compound-systems, large language models, prompt-optimization; When optimizing complex prompting for large language models in production due to its published effectiveness.
- 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 textgrad?
- If only basic and traditional manual tuning methods are needed for simpler use cases. Avoid if strict version control is required since the bleeding edge installation points to GitHub directly.
- Is gorilla or textgrad more popular on GitHub?
- gorilla has more GitHub stars (12,988 vs 3,700). Stars measure visibility, not whether either tool fits your constraints.
- Are gorilla and textgrad open source?
- Yes - both are open-source projects on GitHub (gorilla: Apache-2.0, textgrad: MIT).
- Where can I find alternatives to gorilla or textgrad?
- GraphCanon lists graph-backed alternatives at gorilla alternatives and textgrad alternatives (gorilla markdown twin, textgrad 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 textgrad?
- gorilla: Slowing. textgrad: 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 gorilla and textgrad?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gorilla trust report; textgrad trust report.