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GPT-4.1

OpenAI

85·Strong

Overall Trust Score

OpenAI's flagship GPT-4.1 model offering strong general-purpose capabilities across diverse tasks. The standard choice for production applications requiring reliable, high-quality outputs.

general-purpose
flagship
production-ready
multimodal
enterprise
balanced
Version: 2025-01
Last Evaluated: November 8, 2025
Official Website →

Trust Vector

Performance & Reliability

85

Strong general-purpose performance with good balance across coding, reasoning, and knowledge tasks. Flagship model for most production use cases.

task accuracy code
82
Methodology
Industry-standard coding benchmarks
Evidence
HumanEval Benchmark
48.1% pass rate
Date: 2025-01-15
MBPP Benchmark
62% on mostly basic programming problems
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
task accuracy reasoning
84
Methodology
Mathematical and scientific reasoning benchmarks
Evidence
MATH Benchmark
68% on mathematical reasoning tasks
Date: 2025-01-15
GPQA
52% on graduate-level reasoning
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
task accuracy general
86
Methodology
Crowdsourced comparisons and comprehensive knowledge testing
Evidence
MMLU Benchmark
66.3% on multitask language understanding
Date: 2025-01-15
LMSYS Chatbot Arena
1250 ELO (Strong mid-tier performance)
Date: 2025-01-20
Confidence: highLast verified: 2025-11-08
output consistency
85
Methodology
Internal testing with repeated prompts
Evidence
OpenAI Internal Testing
Strong consistency across temperature settings
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
latency p50
Value: 1.2s
Methodology
Median latency for API requests
Evidence
OpenAI Documentation
Typical response time ~1.2s
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
latency p95
Value: 2.4s
Methodology
95th percentile response time
Evidence
Community benchmarking
p95 latency ~2.4s
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

86

Strong security posture with comprehensive safety systems. Robust protection against adversarial attacks.

prompt injection resistance
87
Methodology
Testing against OWASP LLM01 prompt injection attacks
Evidence
OpenAI Safety Testing
Strong resistance to prompt injection attacks
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
jailbreak resistance
88
Methodology
Testing against adversarial prompt datasets
Evidence
OpenAI Safety Evaluations
Robust safety mechanisms
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
data leakage prevention
83
Methodology
Analysis of privacy policies
Evidence
OpenAI Privacy Policy
API data not used for training by default
Date: 2024-12-15
Confidence: mediumLast verified: 2025-11-08
output safety
87
Methodology
Safety testing across harmful content categories
Evidence
OpenAI Safety Benchmarks
Comprehensive safety systems
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
api security
85
Methodology
Review of API security features
Evidence
OpenAI API Documentation
API key authentication, HTTPS, rate limiting
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08

Privacy & Compliance

84

Standard enterprise privacy practices with SOC 2 Type II certification. 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
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

82

Good transparency with solid explainability. Lower hallucination rate than smaller models. Comprehensive safety systems.

explainability
84
Methodology
Evaluation of reasoning transparency
Evidence
Model Behavior
Good explanations and reasoning
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
hallucination rate
82
Methodology
Testing on factual QA datasets
Evidence
SimpleQA Benchmark
Good factual accuracy
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
bias fairness
79
Methodology
Evaluation on bias benchmarks
Evidence
OpenAI Safety Report
Regular bias testing and mitigation
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
uncertainty quantification
81
Methodology
Qualitative assessment of confidence expression
Evidence
Model Behavior
Good uncertainty expression
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
model card quality
87
Methodology
Review of documentation completeness
Evidence
OpenAI Model Documentation
Comprehensive documentation with benchmarks
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
86
Methodology
Analysis of safety mechanisms
Evidence
OpenAI Safety Systems
Comprehensive safety guardrails
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08

Operational Excellence

90

Excellent operational maturity with industry-leading ecosystem and developer experience.

api design quality
92
Methodology
Review of API design
Evidence
OpenAI API Documentation
Well-designed RESTful API with comprehensive features
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
sdk quality
93
Methodology
Review of SDK quality
Evidence
OpenAI SDKs
High-quality SDKs for Python, Node.js
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
versioning policy
86
Methodology
Review of versioning approach
Evidence
OpenAI API Versioning
Clear versioning with deprecation notices
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
monitoring observability
85
Methodology
Review of monitoring tools
Evidence
OpenAI Dashboard
Comprehensive usage dashboard
Date: 2025-01-15
Confidence: mediumLast verified: 2025-11-08
support quality
89
Methodology
Assessment of support channels
Evidence
OpenAI Support
Excellent support and documentation
Date: 2025-01-15
Confidence: highLast verified: 2025-11-08
ecosystem maturity
95
Methodology
Analysis of integrations
Evidence
GitHub Ecosystem
Extremely mature ecosystem
Date: 2025-11-01
Confidence: highLast verified: 2025-11-08
license terms
90
Methodology
Review of licensing
Evidence
OpenAI Terms of Service
Clear commercial terms
Date: 2024-12-15
Confidence: highLast verified: 2025-11-08

✨ Strengths

  • Strong general-purpose performance (66.3% MMLU)
  • Good balance of quality and speed (~1.2s p50)
  • Large 128K context window for document processing
  • Mature ecosystem with extensive integrations
  • Reliable uptime and infrastructure (99.9%)
  • Comprehensive safety and security features

⚠️ Limitations

  • Moderate coding performance (48.1% HumanEval)
  • 30-day data retention period
  • Not HIPAA eligible
  • Limited regional data residency options
  • Higher pricing than smaller models
  • Training data transparency limited

📊 Metadata

pricing:
input: $2.50 per 1M tokens
output: $10.00 per 1M tokens
notes: Standard flagship pricing
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
11: Russian
12: Dutch
modalities:
0: text
1: image (input)
api endpoint: https://api.openai.com/v1/chat/completions
open source: false
architecture: Transformer-based with multimodal capabilities
parameters: Not disclosed (large)

Use Case Ratings

code generation

82

Good coding capabilities for typical development tasks. 48.1% HumanEval suitable for standard programming.

customer support

87

Excellent for customer support with strong conversational abilities and good response times.

content creation

86

Strong content creation with natural language and good creativity.

data analysis

83

Good for data analysis and business intelligence tasks.

research assistant

85

Strong research capabilities with good knowledge base (66.3% MMLU).

legal compliance

80

Adequate for legal document analysis but requires human oversight.

healthcare

77

Not HIPAA eligible. Limited use for healthcare applications.

financial analysis

82

Good for financial analysis and reporting tasks.

education

86

Excellent for educational applications and tutoring.

creative writing

84

Strong creative writing with natural storytelling abilities.