Model Comparison

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

DeepSeek

DeepSeek-R1-0528

DeepSeek

DeepSeek-R1-0528 is a language model developed by DeepSeek. It achieves strong performance with an average score of 68.1% across 16 benchmarks. It excels particularly in MMLU-Redux (93.4%), AIME 2024 (91.4%), AIME 2025 (87.5%). It supports a 262K token context window for handling large documents. The model is available through 3 API providers. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Google

Gemini 2.5 Flash

Google

Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. 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.

Google

Gemini 2.5 Flash

Google

2025-05-20

DeepSeek

DeepSeek-R1-0528

DeepSeek

2025-05-28

8 days newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-R1-0528

$0.15 cheaper
Input:$0.50
Output:$2.15
Google

Gemini 2.5 Flash

Input:$0.30
Output:$2.50

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1-0528

Max Context:262.1K
Parameters:671.0B
Google

Gemini 2.5 Flash

Larger context
Max Context:1.1M

Average performance across 7 common benchmarks

DeepSeek

DeepSeek-R1-0528

+4.5%
Average Score:62.1%
Google

Gemini 2.5 Flash

Average Score:57.6%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1-0528

code
+8.6%
73.3%
general
+11.2%
69.2%
Google

Gemini 2.5 Flash

code
64.7%
general
58.0%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Flash

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-R1-0528

3 providers

DeepInfra

Throughput: 45.04 tok/s
Latency: 0.61ms

Novita

Throughput: 37.96 tok/s
Latency: 1.18ms

DeepSeek

Throughput: 9 tok/s
Latency: 0.3ms
Google

Gemini 2.5 Flash

2 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

ZeroEval

Throughput: 85 tok/s
Latency: 0.7ms
DeepSeek

DeepSeek-R1-0528

+4.5%
Avg Score:62.1%
Providers:3
Google

Gemini 2.5 Flash

Avg Score:57.6%
Providers:2