Model Comparison

DeepSeek-V3.2-Exp vs DeepSeek VL2 Tiny

Comparing DeepSeek-V3.2-Exp and DeepSeek VL2 Tiny across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Exp and DeepSeek VL2 Tiny 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
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
DeepSeek
DeepSeek VL2 Tiny
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

682.0B diff

DeepSeek-V3.2-Exp has 682.0B more parameters than DeepSeek VL2 Tiny, making it 22733.3% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
685.0B
DeepSeek-V3.2-Exp
3.0B
DeepSeek VL2 Tiny

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

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

DeepSeek-V3.2-Exp

Text
Images
Audio
Video

DeepSeek VL2 Tiny

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while DeepSeek VL2 Tiny uses deepseek.

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

DeepSeek-V3.2-Exp

MIT

Open weights

DeepSeek VL2 Tiny

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while DeepSeek VL2 Tiny was released on 2024-12-13.

DeepSeek-V3.2-Exp is 10 months newer than DeepSeek VL2 Tiny.

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

9mo newer
DeepSeek VL2 Tiny

Dec 13, 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

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
DeepSeek
DeepSeek VL2 Tiny

FAQ

Common questions about DeepSeek-V3.2-Exp vs DeepSeek VL2 Tiny

DeepSeek-V3.2-Exp (DeepSeek) and DeepSeek VL2 Tiny (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%.
DeepSeek-V3.2-Exp supports 164K tokens and DeepSeek VL2 Tiny 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.