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OpenAI o3-mini

OpenAI

87·Strong

Overall Trust Score

Efficient reasoning model from OpenAI achieving 50% on SWE-bench and 87.3% on HumanEval. Optimized for fast reasoning at competitive pricing with strong coding capabilities.

reasoning
code-generation
mini-model
budget-friendly
chain-of-thought
efficient
soc-2-certified
Version: 20251201
Last Evaluated: November 8, 2025
Official Website →

Trust Vector

Performance & Reliability

89

Strong performance with efficient reasoning. Excellent HumanEval at 87.3% with fast latency.

task accuracy code
92
Methodology
Industry-standard coding benchmarks
Evidence
SWE-bench Verified
50% resolution rate
Date: 2025-12-01
HumanEval
87.3% accuracy on code generation
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
task accuracy reasoning
87
Methodology
Competition-level reasoning benchmarks
Evidence
AIME 2024
62% on competition math
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
task accuracy general
86
Methodology
Comprehensive knowledge testing
Evidence
MMLU
75.8% on comprehensive knowledge
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
output consistency
88
Methodology
Internal testing
Evidence
OpenAI Documentation
Good consistency with efficient reasoning
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
latency p50
Value: 1.8s
Methodology
Median latency
Evidence
OpenAI Documentation
Fast response time ~1.8s
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
latency p95
Value: 3.2s
Methodology
95th percentile
Evidence
Community benchmarking
p95 latency ~3.2s
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
context window
Value: 128,000 tokens
Methodology
Official specification
Evidence
OpenAI Documentation
128K tokens
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
uptime
99
Methodology
Historical data
Evidence
OpenAI Status
99.9% uptime
Date: 2025-11-01
Confidence: highLast verified: 2025-11-08

Security

86

Good security with reasoning-enhanced safety.

prompt injection resistance
87
Methodology
OWASP LLM01 testing
Evidence
OpenAI Safety
Strong resistance
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
jailbreak resistance
88
Methodology
Adversarial testing
Evidence
OpenAI Safety
Good jailbreak resistance
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
data leakage prevention
83
Methodology
Policy analysis
Evidence
OpenAI Privacy
Standard practices
Date: 2025-12-01
Confidence: mediumLast verified: 2025-11-08
output safety
89
Methodology
Safety testing
Evidence
OpenAI Safety
Comprehensive filtering
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
api security
87
Methodology
Security review
Evidence
OpenAI API
Enterprise security
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08

Privacy & Compliance

84

Good privacy with SOC 2. 30-day retention minimum.

data residency
Value: US (enterprise options)
Methodology
Documentation review
Evidence
OpenAI Enterprise
US-based
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
training data optout
90
Methodology
Policy analysis
Evidence
OpenAI Privacy
No API training by default
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
data retention
Value: 30 days
Methodology
Policy review
Evidence
OpenAI Policies
30-day retention
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
pii handling
80
Methodology
Documentation review
Evidence
OpenAI Documentation
Customer responsible
Date: 2025-12-01
Confidence: mediumLast verified: 2025-11-08
compliance certifications
86
Methodology
Certification verification
Evidence
OpenAI Trust
SOC 2, GDPR
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
zero data retention
80
Methodology
Policy review
Evidence
OpenAI Enterprise
30-day minimum
Date: 2025-12-01
Confidence: mediumLast verified: 2025-11-08

Trust & Transparency

87

Good transparency with visible reasoning. Strong safety guardrails.

explainability
90
Methodology
Feature evaluation
Evidence
Chain-of-Thought
Visible reasoning
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
hallucination rate
85
Methodology
QA testing
Evidence
OpenAI Benchmarks
Reduced via reasoning
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
bias fairness
82
Methodology
Bias testing
Evidence
OpenAI Safety
Ongoing mitigation
Date: 2025-12-01
Confidence: mediumLast verified: 2025-11-08
uncertainty quantification
86
Methodology
Confidence assessment
Evidence
Model Behavior
Good expression
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
model card quality
89
Methodology
Documentation review
Evidence
OpenAI Docs
Comprehensive docs
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
training data transparency
78
Methodology
Disclosure review
Evidence
OpenAI Research
General description
Date: 2025-12-01
Confidence: mediumLast verified: 2025-11-08
guardrails
90
Methodology
Safety analysis
Evidence
OpenAI Safety
Comprehensive guardrails
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08

Operational Excellence

89

Excellent operational maturity with mature ecosystem.

api design quality
91
Methodology
API review
Evidence
OpenAI API
Well-designed
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
sdk quality
92
Methodology
SDK review
Evidence
OpenAI SDKs
High-quality
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
versioning policy
88
Methodology
Policy review
Evidence
OpenAI Versioning
Clear policy
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
monitoring observability
87
Methodology
Tool review
Evidence
OpenAI Platform
Good dashboard
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
support quality
88
Methodology
Support assessment
Evidence
OpenAI Support
Good support
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
ecosystem maturity
91
Methodology
Ecosystem analysis
Evidence
OpenAI Ecosystem
Mature
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08
license terms
89
Methodology
Terms review
Evidence
OpenAI Terms
Standard commercial
Date: 2025-12-01
Confidence: highLast verified: 2025-11-08

✨ Strengths

  • •Strong HumanEval performance (87.3%)
  • •Fast latency (1.8s p50) for a reasoning model
  • •Good value with reasoning at mini pricing
  • •Visible chain-of-thought reasoning
  • •Strong mathematical capabilities
  • •Comprehensive safety guardrails

⚠️ Limitations

  • •30-day data retention (not ephemeral)
  • •Not HIPAA eligible by default
  • •Lower than o4-mini on some benchmarks
  • •Mini model limitations for complex reasoning
  • •Reasoning overhead for simple tasks
  • •Moderate general knowledge (75.8% MMLU)

📊 Metadata

pricing:
input: $1.00 per 1M tokens
output: $4.00 per 1M tokens
notes: Budget-friendly reasoning model pricing (Flex tier)
last verified: 2025-11-09
context window: 128000
languages:
0: English
1: Spanish
2: French
3: German
4: Italian
5: Portuguese
6: Japanese
7: Korean
8: Chinese
modalities:
0: text
api endpoint: https://api.openai.com/v1/chat/completions
open source: false
architecture: Transformer-based with efficient chain-of-thought
parameters: Not disclosed

Use Case Ratings

code generation

91

Strong coding with 87.3% HumanEval. Fast latency great for development workflows.

customer support

83

Good but reasoning may add latency. Better for complex support.

content creation

82

Adequate but reasoning may be unnecessary for creative tasks.

data analysis

90

Strong analytical capabilities with efficient reasoning.

research assistant

89

Good research with visible reasoning at affordable pricing.

legal compliance

82

Good reasoning but 30-day retention may be concern.

healthcare

81

Not HIPAA eligible by default.

financial analysis

88

Strong analytical capabilities at reasonable pricing.

education

91

Excellent for education with visible reasoning and good value.

creative writing

79

Adequate but reasoning may hinder creativity.

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