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GPT-4.1 mini

OpenAI

83·Strong

Overall Trust Score

OpenAI's balanced GPT-4.1 variant offering good performance with efficient resource usage. Optimized for production workloads requiring quality outputs at reasonable cost.

balanced
production-ready
cost-effective
general-purpose
fast
mid-tier
Version: 2025-01
Last Evaluated: November 8, 2025
Official Website →

Trust Vector

Performance & Reliability

78

Balanced performance with good speed. Suitable for most production workloads requiring reliable outputs without premium pricing.

task accuracy code
76
Methodology
Industry-standard coding benchmarks
Evidence
HumanEval Benchmark
49.6% pass rate
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
task accuracy reasoning
78
Methodology
Mathematical reasoning benchmarks
Evidence
MATH Benchmark
58% on mathematical reasoning tasks
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
task accuracy general
80
Methodology
Crowdsourced comparisons and knowledge testing
Evidence
MMLU Benchmark
65% on multitask language understanding
Date: 2025-01-15
LMSYS Chatbot Arena
1180 ELO (Mid-tier performance)
Date: 2025-01-20
Confidence: highLast verified: 2025-11-08
output consistency
79
Methodology
Internal testing with repeated prompts
Evidence
OpenAI Internal Testing
Good consistency for most tasks
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
latency p50
Value: 0.8s
Methodology
Median latency for API requests
Evidence
OpenAI Documentation
Fast response time ~0.8s
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
latency p95
Value: 1.6s
Methodology
95th percentile response time
Evidence
Community benchmarking
p95 latency ~1.6s
Date: 2025-01-25
Confidence: highLast verified: 2025-11-08
context window
Value: 128,000 tokens
Methodology
Official specification from provider
Evidence
OpenAI API Documentation
128K token context window
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
uptime
98
Methodology
Historical uptime data from official status page
Evidence
OpenAI Status Page
99.9% uptime (last 90 days)
Date: 2025-11-01
Confidence: highLast verified: 2025-11-08

Security

84

Strong security posture with robust safety measures. Good balance of safety and usability.

prompt injection resistance
84
Methodology
Testing against OWASP LLM01 prompt injection attacks
Evidence
OpenAI Safety Testing
Good resistance to prompt injection
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
jailbreak resistance
85
Methodology
Testing against adversarial prompt datasets
Evidence
OpenAI Safety Evaluations
Strong safety mechanisms
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
data leakage prevention
83
Methodology
Analysis of privacy policies and data handling practices
Evidence
OpenAI Privacy Policy
API data not used for training by default
Date: 2024-12-15
Confidence: mediumLast verified: 2025-11-08
output safety
86
Methodology
Safety testing across harmful content categories
Evidence
OpenAI Safety Benchmarks
Comprehensive content filtering
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
api security
85
Methodology
Review of API security features and best practices
Evidence
OpenAI API Documentation
API key authentication, HTTPS only, rate limiting
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08

Privacy & Compliance

84

Standard OpenAI privacy practices with SOC 2 compliance. 30-day retention period.

data residency
Value: US (primary)
Methodology
Review of enterprise documentation
Evidence
OpenAI Documentation
US-based infrastructure
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
training data optout
90
Methodology
Analysis of privacy policy
Evidence
OpenAI Privacy Policy
API data not used for training by default
Date: 2024-12-15
Confidence: highLast verified: 2025-11-08
data retention
Value: 30 days
Methodology
Review of terms of service
Evidence
OpenAI Terms of Service
API data retained for 30 days for abuse monitoring
Date: 2024-12-15
Confidence: highLast verified: 2025-11-08
pii handling
82
Methodology
Review of data protection capabilities
Evidence
OpenAI Privacy Documentation
Customer responsible for PII redaction
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
compliance certifications
88
Methodology
Verification of compliance certifications
Evidence
OpenAI Trust Portal
SOC 2 Type II, GDPR compliant
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
zero data retention
75
Methodology
Review of data handling practices
Evidence
OpenAI API Documentation
30-day retention for abuse monitoring
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08

Trust & Transparency

80

Good transparency with reasonable explainability. Moderate hallucination rate suitable for most applications.

explainability
82
Methodology
Evaluation of reasoning transparency
Evidence
Model Behavior
Good explanations for most tasks
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
hallucination rate
80
Methodology
Testing on factual QA datasets
Evidence
SimpleQA Benchmark
Moderate hallucination rate
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
bias fairness
78
Methodology
Evaluation on bias benchmarks
Evidence
OpenAI Safety Report
Regular bias testing applied
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
uncertainty quantification
79
Methodology
Qualitative assessment of confidence expression
Evidence
Model Behavior
Reasonable uncertainty expression
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
model card quality
85
Methodology
Review of documentation completeness
Evidence
OpenAI Model Documentation
Comprehensive documentation
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
training data transparency
74
Methodology
Review of public disclosures
Evidence
OpenAI Public Statements
General description provided
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
guardrails
84
Methodology
Analysis of safety mechanisms
Evidence
OpenAI Safety Systems
Robust safety guardrails
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08

Operational Excellence

88

Excellent operational maturity with OpenAI's established infrastructure and ecosystem.

api design quality
91
Methodology
Review of API design
Evidence
OpenAI API Documentation
Consistent RESTful API
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
sdk quality
93
Methodology
Review of SDK quality
Evidence
OpenAI SDKs
Official SDKs for Python, Node.js
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
versioning policy
85
Methodology
Review of versioning approach
Evidence
OpenAI API Versioning
Clear versioning policy
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
monitoring observability
84
Methodology
Review of monitoring tools
Evidence
OpenAI Dashboard
Usage dashboard available
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
support quality
87
Methodology
Assessment of support channels
Evidence
OpenAI Support
Email support and community
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
ecosystem maturity
94
Methodology
Analysis of integrations
Evidence
GitHub Ecosystem
Mature ecosystem
Date: 2025-11-01
Confidence: highLast verified: 2025-11-08
license terms
90
Methodology
Review of licensing
Evidence
OpenAI Terms of Service
Standard commercial terms
Date: 2024-12-15
Confidence: highLast verified: 2025-11-08

✨ Strengths

  • Balanced performance and cost efficiency
  • Fast response times (~0.8s p50) suitable for production
  • Large 128K context window for document processing
  • Good general knowledge (65% MMLU)
  • Strong OpenAI ecosystem and tooling support
  • Reliable uptime and infrastructure

⚠️ Limitations

  • Mid-tier coding performance (49.6% HumanEval)
  • 30-day data retention period
  • Not HIPAA eligible
  • Moderate hallucination rate requires validation
  • Limited regional data residency options
  • Not suitable for highly specialized or complex tasks

📊 Metadata

pricing:
input: $0.60 per 1M tokens
output: $1.80 per 1M tokens
notes: Mid-tier pricing for balanced performance
context window: 128000
languages:
0: English
1: Spanish
2: French
3: German
4: Italian
5: Portuguese
6: Japanese
7: Korean
8: Chinese
9: Arabic
10: Hindi
modalities:
0: text
api endpoint: https://api.openai.com/v1/chat/completions
open source: false
architecture: Transformer-based, balanced optimization
parameters: Not disclosed (medium)

Use Case Ratings

code generation

78

Good for typical coding tasks. 49.6% HumanEval indicates solid capability for common programming scenarios.

customer support

84

Well-suited for customer support with fast response times and good conversational ability.

content creation

82

Good for content creation with balanced quality and speed.

data analysis

79

Capable of moderate data analysis tasks. Sufficient for most business analytics.

research assistant

81

Good for research assistance with 65% MMLU showing solid knowledge base.

legal compliance

76

Adequate for basic legal tasks but not specialized legal applications.

healthcare

74

Not HIPAA eligible. Limited use for healthcare applications.

financial analysis

78

Good for standard financial analysis. Not suitable for complex modeling.

education

83

Well-suited for educational content and tutoring. Good balance of accuracy and accessibility.

creative writing

80

Good creative writing capabilities with natural language generation.