Model Comparison

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

DeepSeek

DeepSeek VL2

DeepSeek

DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). The model shows particular specialization in vision tasks with an average performance of 76.7%. It supports a 259K 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 DeepSeek's latest advancement in AI technology.

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.

DeepSeek

DeepSeek VL2

DeepSeek

2024-12-13

OpenAI

GPT-4.1 nano

OpenAI

2025-04-14

4 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek VL2

Input:$9.50
Output:$4800.00
OpenAI

GPT-4.1 nano

$4809.00 cheaper
Input:$0.10
Output:$0.40

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek VL2

Max Context:258.6K
Parameters:27.0B
OpenAI

GPT-4.1 nano

Larger context
Max Context:1.1M

Average performance across 2 common benchmarks

DeepSeek

DeepSeek VL2

+1.1%
Average Score:57.0%
OpenAI

GPT-4.1 nano

Average Score:55.8%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek VL2

vision
+21.3%
76.7%
general
+37.5%
69.9%
math
+6.6%
62.8%
OpenAI

GPT-4.1 nano

vision
55.4%
general
32.4%
math
56.2%
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

DeepSeek

DeepSeek VL2

1 providers

Replicate

Throughput: 22 tok/s
Latency: 0.5ms
OpenAI

GPT-4.1 nano

1 providers

OpenAI

Throughput: 200 tok/s
Latency: 2ms
DeepSeek

DeepSeek VL2

+1.1%
Avg Score:57.0%
Providers:1
OpenAI

GPT-4.1 nano

Avg Score:55.8%
Providers:1