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.

Alibaba

Qwen2.5 VL 72B Instruct

Alibaba

Qwen2.5 VL 72B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 66.9% across 30 benchmarks. It excels particularly in DocVQA (96.4%), Android Control Low_EM (93.7%), ChartQA (89.5%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Alibaba's latest advancement in AI technology.

DeepSeek

DeepSeek-R1

DeepSeek

2025-01-20

Alibaba

Qwen2.5 VL 72B Instruct

Alibaba

2025-01-26

6 days newer

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1

Larger context
Max Context:262.1K
Parameters:671.0B
Alibaba

Qwen2.5 VL 72B Instruct

Max Context:-
Parameters:72.0B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1

math
+40.8%
97.3%
general
+5.7%
75.3%
Alibaba

Qwen2.5 VL 72B Instruct

math
56.5%
general
69.6%

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
Alibaba

Qwen2.5 VL 72B Instruct

0 providers
DeepSeek

DeepSeek-R1

Avg Score:0.0%
Providers:4
Alibaba

Qwen2.5 VL 72B Instruct

Avg Score:0.0%
Providers:0