Gemma 3 27B
Overall Trust Score
Google's open-source Gemma 3 model with 27 billion parameters. Designed for developers seeking Google's research quality with open-source flexibility and commercial-friendly licensing.
Trust Vector
Performance & Reliability
Moderate performance suitable for basic tasks. Limited by smaller context window (8K tokens). Open-source flexibility.
task accuracy code68
task accuracy reasoning69
task accuracy general72
output consistency71
latency p50Value: 1.0s
latency p95Value: 2.0s
context windowValue: 8,192 tokens
uptime95
Security
Basic security with self-hosted deployment control. Additional safety layers recommended for production.
prompt injection resistance76
jailbreak resistance77
data leakage prevention85
output safety78
api security80
Privacy & Compliance
Excellent privacy with self-hosted deployment. Full control over all data aspects.
data residencyValue: User-controlled
training data optout98
data retentionValue: User-controlled
pii handling92
compliance certifications92
zero data retention98
Trust & Transparency
Good transparency as open-source model from Google. Comprehensive documentation.
explainability80
hallucination rate78
bias fairness82
uncertainty quantification81
model card quality90
training data transparency88
guardrails86
Operational Excellence
Good operational maturity with Google's backing. Easier deployment than larger models.
api design quality84
sdk quality85
versioning policy86
monitoring observability76
support quality82
ecosystem maturity84
license terms92
✨ Strengths
- •Open-source with commercial-friendly Google license
- •Complete data sovereignty with self-hosted deployment
- •Lower resource requirements than larger models
- •No data sharing with Google
- •Google's research quality in open-source package
- •Cost-effective for basic tasks
⚠️ Limitations
- •Limited accuracy (42.4% MMLU) compared to larger models
- •Small context window (8K tokens)
- •Moderate coding capabilities
- •Requires infrastructure for deployment
- •Not suitable for complex or specialized tasks
- •Limited ecosystem compared to Llama
📊 Metadata
Use Case Ratings
code generation
Basic coding capabilities. Limited context window (8K) restricts complex projects.
customer support
Adequate for basic customer support with privacy benefits.
content creation
Good for short-form content. Limited by 8K context window.
data analysis
Basic data analysis only. Not suitable for complex tasks.
research assistant
Basic research tasks. 42.4% MMLU shows limited knowledge depth.
legal compliance
Basic legal tasks with data sovereignty. Limited accuracy for complex work.
healthcare
Basic healthcare tasks with self-hosted HIPAA compliance.
financial analysis
Basic financial tasks only. Not suitable for complex modeling.
education
Good for basic educational content and tutoring.
creative writing
Adequate for short creative writing. Context limit restricts long-form content.