Model Comparison

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

DeepSeek R1 Zero

DeepSeek

DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Gemini 1.0 Pro

Google

Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.

Gemini 1.0 Pro

Google

2024-02-15

DeepSeek R1 Zero

DeepSeek

2025-01-20

11 months newer

Performance Metrics

Context window and performance specifications

DeepSeek R1 Zero

Max Context:-

Parameters:671.0B

Gemini 1.0 Pro

Larger context

Max Context:41.0K

Average performance across 1 common benchmarks

DeepSeek R1 Zero

+45.4%

Average Score:73.3%

Gemini 1.0 Pro

Average Score:27.9%

Performance comparison across key benchmark categories

DeepSeek R1 Zero

math

+56.3%

95.9%

general

+28.6%

80.0%

Gemini 1.0 Pro

math

39.6%

general

51.4%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Gemini 1.0 Pro

2024-02-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek R1 Zero

0 providers

Gemini 1.0 Pro

1 providers

Google

Throughput: 120 tok/s

Latency: 0.4ms

DeepSeek R1 Zero

+45.4%

Avg Score:73.3%

Providers:0

Gemini 1.0 Pro

Avg Score:27.9%

Providers:1