Model Comparison

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

DeepSeek VL2 Tiny

DeepSeek

DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, 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 VL2 Tiny

DeepSeek

2024-12-13

10 months newer

Performance Metrics

Context window and performance specifications

DeepSeek VL2 Tiny

Max Context:-

Parameters:3.0B

Gemini 1.0 Pro

Larger context

Max Context:41.0K

Average performance across 2 common benchmarks

DeepSeek VL2 Tiny

Average Score:47.2%

Gemini 1.0 Pro

+0.1%

Average Score:47.3%

Performance comparison across key benchmark categories

DeepSeek VL2 Tiny

vision

+21.2%

69.1%

general

+11.1%

62.5%

math

+14.0%

53.6%

Gemini 1.0 Pro

vision

47.9%

general

51.4%

math

39.6%

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 VL2 Tiny

0 providers

Gemini 1.0 Pro

1 providers

Google

Throughput: 120 tok/s

Latency: 0.4ms

DeepSeek VL2 Tiny

Avg Score:47.2%

Providers:0

Gemini 1.0 Pro

+0.1%

Avg Score:47.3%

Providers:1