Model Comparison

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

DeepSeek

DeepSeek-V3

DeepSeek

DeepSeek-V3 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, 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 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. 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-V3

DeepSeek

2024-12-25

Google

Gemini 2.5 Pro

Google

2025-05-20

4 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3

$9.88 cheaper
Input:$0.27
Output:$1.10
Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3

Max Context:262.1K
Parameters:671.0B
Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M

Average performance across 6 common benchmarks

DeepSeek

DeepSeek-V3

Average Score:49.1%
Google

Gemini 2.5 Pro

+17.3%
Average Score:66.4%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3

code
+2.6%
73.2%
general
65.1%
Google

Gemini 2.5 Pro

code
70.6%
general
+4.3%
69.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
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

1 providers

DeepSeek

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemini 2.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
DeepSeek

DeepSeek-V3

Avg Score:49.1%
Providers:1
Google

Gemini 2.5 Pro

+17.3%
Avg Score:66.4%
Providers:1