DeepSeek VL2 Small vs Nova Lite Comparison

Comparing DeepSeek VL2 Small and Nova Lite across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek VL2 Small outperforms in 1 benchmarks (TextVQA), while Nova Lite is better at 3 benchmarks (ChartQA, DocVQA, MMMU).

Nova Lite shows notably better performance in the majority of benchmarks.

Sat Mar 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Mar 14 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Small
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Amazon
Nova Lite
Input tokens$0.06
Output tokens$0.24
Best providerAWS Bedrock
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Context Window

Maximum input and output token capacity

Only Nova Lite specifies input context (300,000 tokens). Only Nova Lite specifies output context (2,048 tokens).

DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Amazon
Nova Lite
Input300,000 tokens
Output2,048 tokens
Sat Mar 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Small and Nova Lite support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2 Small

Text
Images
Audio
Video

Nova Lite

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small is licensed under deepseek, while Nova Lite uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek VL2 Small

deepseek

Open weights

Nova Lite

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek VL2 Small was released on 2024-12-13, while Nova Lite was released on 2024-11-20.

DeepSeek VL2 Small is 1 month newer than Nova Lite.

DeepSeek VL2 Small

Dec 13, 2024

1.2 years ago

3w newer
Nova Lite

Nov 20, 2024

1.3 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Has open weights
Higher TextVQA score (83.4% vs 80.2%)
Larger context window (300,000 tokens)
Higher ChartQA score (86.8% vs 84.5%)
Higher DocVQA score (92.4% vs 92.3%)
Higher MMMU score (56.2% vs 48.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Small
Amazon
Nova Lite