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.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

2024-09-19

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
Alibaba

Qwen2.5-Coder 32B Instruct

$0.32 cheaper
Input:$0.09
Output:$0.09

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M
Alibaba

Qwen2.5-Coder 32B Instruct

Max Context:256.0K
Parameters:32.0B

Average performance across 1 common benchmarks

OpenAI

GPT-4.1 nano

+5.0%
Average Score:80.1%
Alibaba

Qwen2.5-Coder 32B Instruct

Average Score:75.1%

Performance comparison across key benchmark categories

OpenAI

GPT-4.1 nano

code
+16.3%
74.5%
math
56.2%
general
32.4%
Alibaba

Qwen2.5-Coder 32B Instruct

code
58.2%
math
+18.0%
74.2%
general
+29.1%
61.5%
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
Alibaba

Qwen2.5-Coder 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s
Latency: 0.5ms

Fireworks

Throughput: 110 tok/s
Latency: 0.26ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms
OpenAI

GPT-4.1 nano

+5.0%
Avg Score:80.1%
Providers:1
Alibaba

Qwen2.5-Coder 32B Instruct

Avg Score:75.1%
Providers:4