Comprehensive side-by-side LLM comparison
GPT-OSS-120B leads with 12.3% higher average benchmark score. GPT-4.1 nano offers 948.2K more tokens in context window than GPT-OSS-120B. GPT-4.1 nano is $Infinity cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, GPT-OSS-120B is the stronger choice for coding tasks.
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.
OpenAI
GPT-OSS-120B, released by OpenAI in August 2025, is an open-weight large language model with 120 billion parameters distributed under the Apache 2.0 license. It represents OpenAI's entry into the open-source model space, enabling developers to self-host and fine-tune a GPT-5-generation-class model. GPT-OSS-120B targets research applications, on-premises deployments, and custom fine-tuning workflows requiring a large open-weight base model.
3 months newer

GPT-4.1 nano
OpenAI
2025-04-14

GPT-OSS-120B
OpenAI
2025-08
Cost per million tokens (USD)
GPT-4.1 nano
GPT-OSS-120B
Context window and performance specifications
Average performance across 1 common benchmarks
GPT-4.1 nano
GPT-OSS-120B
Performance comparison across key benchmark categories
GPT-4.1 nano
GPT-OSS-120B
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
GPT-OSS-120B
GPT-4.1 nano
GPT-OSS-120B
GPT-4.1 nano
GPT-OSS-120B
Hugging Face