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 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.2 11B 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

Input:$0.10
Output:$0.40
Meta

Llama 3.2 11B Instruct

$0.40 cheaper
Input:$0.05
Output:$0.05

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M
Meta

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B

Average performance across 4 common benchmarks

OpenAI

GPT-4.1 nano

+8.5%
Average Score:60.5%
Meta

Llama 3.2 11B Instruct

Average Score:52.0%

Performance comparison across key benchmark categories

OpenAI

GPT-4.1 nano

general
32.4%
vision
55.4%
math
56.2%
Meta

Llama 3.2 11B Instruct

general
+37.7%
70.1%
vision
+6.4%
61.8%
math
+1.2%
57.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

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 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
OpenAI

GPT-4.1 nano

+8.5%
Avg Score:60.5%
Providers:1
Meta

Llama 3.2 11B Instruct

Avg Score:52.0%
Providers:6