Model Comparison

DeepSeek-V3.1 vs DeepSeek VL2 Small

Comparing DeepSeek-V3.1 and DeepSeek VL2 Small across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.1 and DeepSeek VL2 Small don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
DeepSeek
DeepSeek VL2 Small
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

655.0B diff

DeepSeek-V3.1 has 655.0B more parameters than DeepSeek VL2 Small, making it 4093.8% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
DeepSeek
DeepSeek VL2 Small
16.0Bparameters
671.0B
DeepSeek-V3.1
16.0B
DeepSeek VL2 Small

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.1 specifies input context (163,840 tokens). Only DeepSeek-V3.1 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Small supports multimodal inputs, whereas DeepSeek-V3.1 does not.

DeepSeek VL2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.1

Text
Images
Audio
Video

DeepSeek VL2 Small

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while DeepSeek VL2 Small uses deepseek.

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

DeepSeek-V3.1

MIT

Open weights

DeepSeek VL2 Small

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while DeepSeek VL2 Small was released on 2024-12-13.

DeepSeek-V3.1 is 1 month newer than DeepSeek VL2 Small.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

4w newer
DeepSeek VL2 Small

Dec 13, 2024

1.4 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

DeepSeek
Larger context window (163,840 tokens)
DeepSeek
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
DeepSeek
DeepSeek VL2 Small

FAQ

Common questions about DeepSeek-V3.1 vs DeepSeek VL2 Small

DeepSeek-V3.1 (DeepSeek) and DeepSeek VL2 Small (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%.
DeepSeek-V3.1 supports 164K tokens and DeepSeek VL2 Small supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.