Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 4.4% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Llama 3.3 70B Instruct. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. Llama 3.3 70B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
Meta
Llama 3.3 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.9% across 9 benchmarks. It excels particularly in IFEval (92.1%), MGSM (91.1%), HumanEval (88.4%). It supports a 256K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.
4 months newer
Llama 3.3 70B Instruct
Meta
2024-12-06
GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)
GPT-4.1 nano
Llama 3.3 70B Instruct
Context window and performance specifications
Average performance across 31 common benchmarks
GPT-4.1 nano
Llama 3.3 70B Instruct
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Llama 3.3 70B Instruct
GPT-4.1 nano
Llama 3.3 70B Instruct
GPT-4.1 nano
Llama 3.3 70B Instruct
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