+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
GPT-4.1 nano vs Llama 3.2 90B Instruct
Comprehensive side-by-side LLM comparison
Llama 3.2 90B Instruct leads with 2.1% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Llama 3.2 90B Instruct. Both models have similar pricing. Llama 3.2 90B Instruct is available on 5 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 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Meta's latest advancement in AI technology.
6 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
GPT-4.1 nano
OpenAI
2025-04-14
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
GPT-4.1 nano
Input:$0.10
Output:$0.40($0.25 cheaper)
+
+
+
+
Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 34 common benchmarks
+
+
+
+
GPT-4.1 nano
Average Score:25.1%
+
+
+
+
Llama 3.2 90B Instruct
Average Score:27.3%(+2.1%)
+
+
+
+
Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
+
+
+
+
Llama 3.2 90B Instruct
+
+
+
+
GPT-4.1 nano
Avg Score:25.1%
Providers:1
+
+
+
+
Llama 3.2 90B Instruct
Avg Score:27.3%(+2.1%)
Providers:5