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 1.5 Pro

Google

Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M 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 1.5 Pro

Google

2024-05-01

DeepSeek

DeepSeek-R1

DeepSeek

2025-01-20

8 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-R1

$9.76 cheaper
Input:$0.55
Output:$2.19
Google

Gemini 1.5 Pro

Input:$2.50
Output:$10.00

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1

Max Context:262.1K
Parameters:671.0B
Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M

Average performance across 4 common benchmarks

DeepSeek

DeepSeek-R1

+10.7%
Average Score:84.6%
Google

Gemini 1.5 Pro

Average Score:73.9%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1

math
+22.4%
97.3%
reasoning
1.3%
code
+7.7%
82.1%
general
+6.3%
75.3%
Google

Gemini 1.5 Pro

math
74.9%
reasoning
+92.0%
93.3%
code
74.5%
general
68.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

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 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
DeepSeek

DeepSeek-R1

+10.7%
Avg Score:84.6%
Providers:4
Google

Gemini 1.5 Pro

Avg Score:73.9%
Providers:1