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.

Google

Gemini 2.5 Flash-Lite

Google

Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). 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 Google's latest advancement in AI technology.

DeepSeek

DeepSeek VL2

DeepSeek

2024-12-13

Google

Gemini 2.5 Flash-Lite

Google

2025-06-17

6 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek VL2

Input:$9.50
Output:$4800.00
Google

Gemini 2.5 Flash-Lite

$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
Google

Gemini 2.5 Flash-Lite

Larger context
Max Context:1.1M

Average performance across 1 common benchmarks

DeepSeek

DeepSeek VL2

Average Score:51.1%
Google

Gemini 2.5 Flash-Lite

+21.8%
Average Score:72.9%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek VL2

vision
+3.8%
76.7%
general
+34.2%
69.9%
Google

Gemini 2.5 Flash-Lite

vision
72.9%
general
35.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Flash-Lite

2025-01-01

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
Google

Gemini 2.5 Flash-Lite

1 providers

Google

Throughput: 5.69 tok/s
Latency: 0.44ms
DeepSeek

DeepSeek VL2

Avg Score:51.1%
Providers:1
Google

Gemini 2.5 Flash-Lite

+21.8%
Avg Score:72.9%
Providers:1