Model Comparison

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

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Google

Gemini 2.5 Pro

Google

Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 Google's latest advancement in AI technology.

Google

Gemini 2.5 Pro

Google

2025-05-20

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

2025-09-29

4 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.2-Exp

$10.57 cheaper
Input:$0.27
Output:$0.41
Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.2-Exp

Max Context:229.4K
Parameters:685.0B
Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M

Average performance across 23 common benchmarks

DeepSeek

DeepSeek-V3.2-Exp

Average Score:37.7%
Google

Gemini 2.5 Pro

+10.7%
Average Score:48.4%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.2-Exp

factuality
+46.3%
97.1%
math
+3.5%
86.5%
general
62.1%
code
64.3%
Google

Gemini 2.5 Pro

factuality
50.8%
math
83.0%
general
+12.1%
74.1%
code
+8.3%
72.6%
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Pro

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-V3.2-Exp

2 providers

Novita

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
Google

Gemini 2.5 Pro

2 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

ZeroEval

Throughput: 85 tok/s
Latency: 0.7ms
DeepSeek

DeepSeek-V3.2-Exp

Avg Score:37.7%
Providers:2
Google

Gemini 2.5 Pro

+10.7%
Avg Score:48.4%
Providers:2