GPT-4.1 nano
vgpt-4.1-nano-2025-04-14OpenAI
DEPRECATED: OpenAI announced 2026-04-22 that gpt-4.1-nano's API shuts down 2026-10-23; recommended replacement is gpt-5.4-nano. Historically OpenAI's smallest and most efficient GPT-4.1 variant for high-volume, cost-sensitive applications, with a 1,047,576-token context window.
Trust Vector Analysis
Dimension Breakdown
🚀Performance & Reliability+
Basic performance optimized for speed and efficiency. Best for simple tasks where ultra-low latency and cost are priorities.
Industry-standard coding benchmarks measuring basic programming tasks
Basic reasoning benchmarks
Crowdsourced comparisons and knowledge testing
Internal testing with repeated prompts
Median latency for API requests
95th percentile response time
Official specification from provider
Historical uptime data from official status page
🛡️Security+
Good security posture with standard OpenAI safety measures. Smaller model may have slightly lower resistance to adversarial attacks.
Testing against OWASP LLM01 prompt injection attacks
Testing against adversarial prompt datasets
Analysis of privacy policies and data handling practices
Safety testing across harmful content categories
Review of API security features and best practices
🔒Privacy & Compliance+
Standard OpenAI privacy practices. 30-day data retention for abuse monitoring.
Review of enterprise documentation and privacy policies
Analysis of privacy policy and data usage terms
Review of terms of service and data retention policies
Review of data protection capabilities
Verification of compliance certifications
Review of data handling practices
👁️Trust & Transparency+
Basic transparency features. Smaller model size limits explainability depth. Higher hallucination rate than premium models.
Evaluation of reasoning transparency
Testing on factual QA datasets
Evaluation on bias benchmarks
Qualitative assessment of confidence expression
Review of documentation completeness
Review of public disclosures about training data
Analysis of built-in safety mechanisms
⚙️Operational Excellence+
Excellent operational maturity leveraging OpenAI's established infrastructure. Versioning score reduced to reflect deprecation: API shutdown 2026-10-23, migrate to gpt-5.4-nano.
Review of API design and consistency
Review of SDK quality and maintenance
Review of versioning policy
Review of monitoring tools
Assessment of support channels
Analysis of third-party integrations
Review of licensing terms
- +Ultra-low latency (~0.4s p50) ideal for real-time applications
- +Most cost-effective option in GPT-4.1 family ($0.10/$0.40 per 1M)
- +Good for high-volume, simple tasks
- +Very large context window (1,047,576 tokens) at nano pricing
- +Same API and ecosystem as premium OpenAI models
- +Reliable uptime and infrastructure
- !Limited coding capabilities (29.4% HumanEval)
- !Basic reasoning and knowledge (50.3% MMLU)
- !Higher hallucination rate than larger models
- !Not suitable for complex or specialized tasks
- !30-day data retention
- !DEPRECATED: API shutdown 2026-10-23 (announced 2026-04-22); migrate to gpt-5.4-nano
Use Case Ratings
code generation
Basic code generation for simple tasks. 29.4% HumanEval indicates limited capability for complex programming.
customer support
Good for high-volume, simple customer queries. Fast response times make it suitable for basic support automation.
content creation
Adequate for simple content tasks. Limited creativity and depth compared to larger models.
data analysis
Basic data interpretation. Not suitable for complex analytical tasks.
research assistant
Suitable for simple research queries and summaries. Limited depth for complex topics.
legal compliance
Not recommended for legal applications due to limited accuracy and reasoning.
healthcare
Not suitable for healthcare applications. Lacks accuracy and HIPAA eligibility.
financial analysis
Basic financial calculations only. Not suitable for complex financial modeling.
education
Suitable for basic educational content and simple tutoring. Limited for advanced topics.
creative writing
Basic creative writing. Less nuanced and creative than larger models.