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.

Mistral AI

Pixtral Large

Mistral AI

Pixtral Large is a multimodal language model developed by Mistral AI. This model demonstrates exceptional performance with an average score of 80.5% across 7 benchmarks. It excels particularly in AI2D (93.8%), DocVQA (93.3%), ChartQA (88.1%). The model shows particular specialization in general tasks with an average performance of 91.0%. It supports a 256K token context window for handling large documents. 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 2024, it represents Mistral AI's latest advancement in AI technology.

Mistral AI

Pixtral Large

Mistral AI

2024-11-18

OpenAI

GPT-4.1 nano

OpenAI

2025-04-14

4 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-4.1 nano

$7.50 cheaper
Input:$0.10
Output:$0.40
Mistral AI

Pixtral Large

Input:$2.00
Output:$6.00

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M
Mistral AI

Pixtral Large

Max Context:256.0K
Parameters:124.0B

Average performance across 2 common benchmarks

OpenAI

GPT-4.1 nano

Average Score:55.8%
Mistral AI

Pixtral Large

+10.9%
Average Score:66.7%

Performance comparison across key benchmark categories

OpenAI

GPT-4.1 nano

general
32.4%
vision
55.4%
math
56.2%
Mistral AI

Pixtral Large

general
+58.6%
91.0%
vision
+24.0%
79.4%
math
+13.2%
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
Mistral AI

Pixtral Large

1 providers

Mistral AI

Throughput: 0.1 tok/s
Latency: 0.5ms
OpenAI

GPT-4.1 nano

Avg Score:55.8%
Providers:1
Mistral AI

Pixtral Large

+10.9%
Avg Score:66.7%
Providers:1