Model Comparison

DeepSeek VL2 vs DeepSeek-V3Which is better in 2026?

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

Verdict: DeepSeek VL2 vs DeepSeek-V3 — which is better?

DeepSeek VL2 (by DeepSeek) and DeepSeek-V3 (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek VL2 if…

  • you are already invested in the DeepSeek ecosystem

Choose DeepSeek-V3 if…

  • you process long inputs — it offers a 131,072 token context window
  • you want the most recent training data — it shipped Dec 2024
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and DeepSeek-V3don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

644.0B diff

DeepSeek-V3 has 644.0B more parameters than DeepSeek VL2, making it 2385.2% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
DeepSeek
DeepSeek-V3
671.0Bparameters
27.0B
DeepSeek VL2
671.0B
DeepSeek-V3

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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

DeepSeek VL2

Text
Images
Audio
Video

DeepSeek-V3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).

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

DeepSeek VL2

deepseek

Open weights

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while DeepSeek-V3 was released on 2024-12-25.

DeepSeek-V3 is 0 month newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.5 years ago

DeepSeek-V3

Dec 25, 2024

1.5 years ago

1w newer

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

Provider Availability

DeepSeek VL2 is available from Replicate. DeepSeek-V3 is available from DeepSeek.

DeepSeek VL2

replicate logo
Replicate

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Supports multimodal inputs
DeepSeek
Larger context window (131,072 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
DeepSeek
DeepSeek-V3

FAQ

Common questions about DeepSeek VL2 vs DeepSeek-V3.

Which is better, DeepSeek VL2 or DeepSeek-V3?

DeepSeek VL2 (DeepSeek) and DeepSeek-V3 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to DeepSeek-V3 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%.

What are the context window sizes for DeepSeek VL2 and DeepSeek-V3?

DeepSeek VL2 supports 129K tokens and DeepSeek-V3 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 and DeepSeek-V3?

Key differences include context window (129K vs 131K), multimodal support (yes vs no), licensing (deepseek vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.

Related comparisons