GPT-4.1 mini

v2025-01

OpenAI

Modelbalancedproduction-readycost-effectivegeneral-purpose
83
Strong
About This Model

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

Last Evaluated: November 8, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+

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

task accuracy code

Industry-standard coding benchmarks

Evidence
HumanEval Benchmark49.6% pass rate
highVerified: 2025-11-08
task accuracy reasoning

Mathematical reasoning benchmarks

Evidence
MATH Benchmark58% on mathematical reasoning tasks
highVerified: 2025-11-08
task accuracy general

Crowdsourced comparisons and knowledge testing

Evidence
MMLU Benchmark65% on multitask language understanding
LMSYS Chatbot Arena1180 ELO (Mid-tier performance)
highVerified: 2025-11-08
output consistency

Internal testing with repeated prompts

Evidence
OpenAI Internal TestingGood consistency for most tasks
mediumVerified: 2025-11-08
latency p50

Median latency for API requests

Evidence
OpenAI DocumentationFast response time ~0.8s
highVerified: 2025-11-08
latency p95

95th percentile response time

Evidence
Community benchmarkingp95 latency ~1.6s
highVerified: 2025-11-08
context window

Official specification from provider

Evidence
OpenAI API Documentation128K token context window
highVerified: 2025-11-08
uptime

Historical uptime data from official status page

Evidence
OpenAI Status Page99.9% uptime (last 90 days)
highVerified: 2025-11-08
🛡️Security
+

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

prompt injection resistance

Testing against OWASP LLM01 prompt injection attacks

Evidence
OpenAI Safety TestingGood resistance to prompt injection
highVerified: 2025-11-08
jailbreak resistance

Testing against adversarial prompt datasets

Evidence
OpenAI Safety EvaluationsStrong safety mechanisms
highVerified: 2025-11-08
data leakage prevention

Analysis of privacy policies and data handling practices

Evidence
OpenAI Privacy PolicyAPI data not used for training by default
mediumVerified: 2025-11-08
output safety

Safety testing across harmful content categories

Evidence
OpenAI Safety BenchmarksComprehensive content filtering
highVerified: 2025-11-08
api security

Review of API security features and best practices

Evidence
OpenAI API DocumentationAPI key authentication, HTTPS only, rate limiting
highVerified: 2025-11-08
🔒Privacy & Compliance
+

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

data residency

Review of enterprise documentation

Evidence
OpenAI DocumentationUS-based infrastructure
highVerified: 2025-11-08
training data optout

Analysis of privacy policy

Evidence
OpenAI Privacy PolicyAPI data not used for training by default
highVerified: 2025-11-08
data retention

Review of terms of service

Evidence
OpenAI Terms of ServiceAPI data retained for 30 days for abuse monitoring
highVerified: 2025-11-08
pii handling

Review of data protection capabilities

Evidence
OpenAI Privacy DocumentationCustomer responsible for PII redaction
mediumVerified: 2025-11-08
compliance certifications

Verification of compliance certifications

Evidence
OpenAI Trust PortalSOC 2 Type II, GDPR compliant
highVerified: 2025-11-08
zero data retention

Review of data handling practices

Evidence
OpenAI API Documentation30-day retention for abuse monitoring
highVerified: 2025-11-08
👁️Trust & Transparency
+

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

explainability

Evaluation of reasoning transparency

Evidence
Model BehaviorGood explanations for most tasks
mediumVerified: 2025-11-08
hallucination rate

Testing on factual QA datasets

Evidence
SimpleQA BenchmarkModerate hallucination rate
mediumVerified: 2025-11-08
bias fairness

Evaluation on bias benchmarks

Evidence
OpenAI Safety ReportRegular bias testing applied
mediumVerified: 2025-11-08
uncertainty quantification

Qualitative assessment of confidence expression

Evidence
Model BehaviorReasonable uncertainty expression
mediumVerified: 2025-11-08
model card quality

Review of documentation completeness

Evidence
OpenAI Model DocumentationComprehensive documentation
highVerified: 2025-11-08
training data transparency

Review of public disclosures

Evidence
OpenAI Public StatementsGeneral description provided
mediumVerified: 2025-11-08
guardrails

Analysis of safety mechanisms

Evidence
OpenAI Safety SystemsRobust safety guardrails
highVerified: 2025-11-08
⚙️Operational Excellence
+

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

api design quality

Review of API design

Evidence
OpenAI API DocumentationConsistent RESTful API
highVerified: 2025-11-08
sdk quality

Review of SDK quality

Evidence
OpenAI SDKsOfficial SDKs for Python, Node.js
highVerified: 2025-11-08
versioning policy

Review of versioning approach

Evidence
OpenAI API VersioningClear versioning policy
highVerified: 2025-11-08
monitoring observability

Review of monitoring tools

Evidence
OpenAI DashboardUsage dashboard available
mediumVerified: 2025-11-08
support quality

Assessment of support channels

Evidence
OpenAI SupportEmail support and community
highVerified: 2025-11-08
ecosystem maturity

Analysis of integrations

Evidence
GitHub EcosystemMature ecosystem
highVerified: 2025-11-08
license terms

Review of licensing

Evidence
OpenAI Terms of ServiceStandard commercial terms
highVerified: 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

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

customer support

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

content creation

Good for content creation with balanced quality and speed.

data analysis

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

research assistant

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

legal compliance

Adequate for basic legal tasks but not specialized legal applications.

healthcare

Not HIPAA eligible. Limited use for healthcare applications.

financial analysis

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

education

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

creative writing

Good creative writing capabilities with natural language generation.