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 2.0 Flash

Google

Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, it represents Google's latest advancement in AI technology.

Google

Gemini 2.0 Flash

Google

2024-12-01

DeepSeek

DeepSeek-V3.2-Exp

DeepSeek

2025-09-29

10 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.2-Exp

Input:$0.27
Output:$0.41
Google

Gemini 2.0 Flash

$0.18 cheaper
Input:$0.10
Output:$0.40

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.2-Exp

Max Context:229.4K
Parameters:685.0B
Google

Gemini 2.0 Flash

Larger context
Max Context:1.1M

Average performance across 24 common benchmarks

DeepSeek

DeepSeek-V3.2-Exp

+2.5%
Average Score:38.6%
Google

Gemini 2.0 Flash

Average Score:36.1%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.2-Exp

factuality
+13.5%
97.1%
math
+10.1%
86.5%
code
+2.8%
64.3%
general
62.1%
Google

Gemini 2.0 Flash

factuality
83.6%
math
76.4%
code
61.4%
general
+0.5%
62.6%
Knowledge Cutoff
Training data recency comparison

Gemini 2.0 Flash

2024-08-01

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 2.0 Flash

1 providers

Google

Throughput: 183 tok/s
Latency: 0.4ms
DeepSeek

DeepSeek-V3.2-Exp

+2.5%
Avg Score:38.6%
Providers:2
Google

Gemini 2.0 Flash

Avg Score:36.1%
Providers:1