Model Comparison

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

DeepSeek

DeepSeek-R1

DeepSeek

DeepSeek-R1 is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.1% across 20 benchmarks. It excels particularly in MATH-500 (97.3%), MMLU-Redux (92.9%), CLUEWSC (92.8%). It supports a 262K token context window for handling large documents. The model is available through 4 API providers. 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 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-R1

DeepSeek

2025-01-20

Google

Gemini 2.5 Pro

Google

2025-05-20

4 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-R1

$8.51 cheaper
Input:$0.55
Output:$2.19
Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1

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-R1

Average Score:47.5%
Google

Gemini 2.5 Pro

+7.5%
Average Score:55.1%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1

code
+11.5%
82.1%
general
+5.9%
75.3%
reasoning
1.3%
Google

Gemini 2.5 Pro

code
70.6%
general
69.4%
reasoning
+3.6%
4.9%
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-R1

4 providers

Together

Throughput: 4 tok/s
Latency: 0.6ms

DeepInfra

Throughput: 0.9 tok/s
Latency: 0.3ms

Fireworks

Throughput: 2.1 tok/s
Latency: 0.3ms

DeepSeek

Throughput: 9 tok/s
Latency: 0.3ms
Google

Gemini 2.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
DeepSeek

DeepSeek-R1

Avg Score:47.5%
Providers:4
Google

Gemini 2.5 Pro

+7.5%
Avg Score:55.1%
Providers:1