Model Comparison

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

OpenAI

GPT-5 nano

OpenAI

GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. 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 4 Maverick

Meta

Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). The model shows particular specialization in vision tasks with an average performance of 75.8%. With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Meta

Llama 4 Maverick

Meta

2025-04-05

OpenAI

GPT-5 nano

OpenAI

2025-08-07

4 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-5 nano

$0.32 cheaper
Input:$0.05
Output:$0.40
Meta

Llama 4 Maverick

Input:$0.17
Output:$0.60

Performance Metrics

Context window and performance specifications

OpenAI

GPT-5 nano

Max Context:528.0K
Meta

Llama 4 Maverick

Larger context
Max Context:2.0M
Parameters:400.0B

Average performance across 1 common benchmarks

OpenAI

GPT-5 nano

+1.4%
Average Score:71.2%
Meta

Llama 4 Maverick

Average Score:69.8%

Performance comparison across key benchmark categories

OpenAI

GPT-5 nano

math
9.6%
general
60.2%
Meta

Llama 4 Maverick

math
+66.1%
75.7%
general
+11.3%
71.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-5 nano

2024-05-30

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

OpenAI

GPT-5 nano

2 providers

ZeroEval

Throughput: 500 tok/s
Latency: 0.3ms

OpenAI

Throughput: 500 tok/s
Latency: 0.3ms
Meta

Llama 4 Maverick

7 providers

Sambanova

Throughput: 638.7 tok/s
Latency: 2.04ms

Together

Throughput: 97.93 tok/s
Latency: 0.2ms

DeepInfra

Throughput: 83.59 tok/s
Latency: 0.38ms

Fireworks

Throughput: 63.03 tok/s
Latency: 0.62ms

Groq

Throughput: 307.3 tok/s
Latency: 0.27ms

Novita

Throughput: 69.42 tok/s
Latency: 0.62ms

Lambda

Throughput: 93.69 tok/s
Latency: 0.65ms
OpenAI

GPT-5 nano

+1.4%
Avg Score:71.2%
Providers:2
Meta

Llama 4 Maverick

Avg Score:69.8%
Providers:7