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GPT-4.1 nano vs GPT-5 Codex
Comprehensive side-by-side LLM comparison
GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
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OpenAI
GPT-5 Codex, released by OpenAI in August 2025, is a coding-specialized large language model from the GPT-5 family engineered for software engineering, code generation, and agentic development workflows. It builds on GPT-5's architecture with optimizations targeting multi-file code editing, test generation, and automated debugging. GPT-5 Codex targets developers and agentic coding tools requiring a model tuned specifically for programming tasks.
3 months newer
GPT-4.1 nano
OpenAI
2025-04-14
GPT-5 Codex
OpenAI
2025-08
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-06
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-4.1 nano
1 providers
OpenAI
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GPT-5 Codex
0 providers
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GPT-4.1 nano
Avg Score:0.0%
Providers:1
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GPT-5 Codex
Avg Score:0.0%
Providers:0