Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

OpenAI

GPT-4.1 nano

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

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.

Meta

Llama 3.2 90B Instruct

Meta

2024-09-25

OpenAI

GPT-4.1 nano

OpenAI

2025-04-14

6 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-4.1 nano

$0.25 cheaper
Input:$0.10
Output:$0.40
Meta

Llama 3.2 90B Instruct

Input:$0.35
Output:$0.40

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M
Meta

Llama 3.2 90B Instruct

Max Context:256.0K
Parameters:90.0B

Average performance across 4 common benchmarks

OpenAI

GPT-4.1 nano

Average Score:60.5%
Meta

Llama 3.2 90B Instruct

+2.1%
Average Score:62.6%

Performance comparison across key benchmark categories

OpenAI

GPT-4.1 nano

general
32.4%
math
56.2%
vision
55.4%
Meta

Llama 3.2 90B Instruct

general
+41.1%
73.5%
math
+14.5%
70.7%
vision
+14.0%
69.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
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

OpenAI

GPT-4.1 nano

1 providers

OpenAI

Throughput: 200 tok/s
Latency: 2ms
Meta

Llama 3.2 90B Instruct

5 providers

Together

Throughput: 57 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 24 tok/s
Latency: 0.5ms

Fireworks

Throughput: 50 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
OpenAI

GPT-4.1 nano

Avg Score:60.5%
Providers:1
Meta

Llama 3.2 90B Instruct

+2.1%
Avg Score:62.6%
Providers:5