Model Comparison

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

DeepSeek

DeepSeek-V2.5

DeepSeek

DeepSeek-V2.5 is a language model developed by DeepSeek. It achieves strong performance with an average score of 71.1% across 15 benchmarks. It excels particularly in GSM8k (95.1%), MT-Bench (90.2%), HumanEval (89.0%). The model is available through 3 API providers. 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-V2.5

DeepSeek

2024-05-08

Google

Gemini 2.5 Pro

Google

2025-05-20

1 year newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V2.5

$10.83 cheaper
Input:$0.14
Output:$0.28
Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V2.5

Max Context:16.4K
Parameters:236.0B
Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M

Average performance across 1 common benchmarks

DeepSeek

DeepSeek-V2.5

Average Score:16.8%
Google

Gemini 2.5 Pro

+46.4%
Average Score:63.2%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V2.5

code
66.1%
general
68.4%
Google

Gemini 2.5 Pro

code
+4.5%
70.6%
general
+1.0%
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-V2.5

3 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 63 tok/s
Latency: 0.5ms

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-V2.5

Avg Score:16.8%
Providers:3
Google

Gemini 2.5 Pro

+46.4%
Avg Score:63.2%
Providers:1