Model Comparison

DeepSeek-V4-Flash-0731 vs DeepSeek VL2 TinyWhich is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and DeepSeek VL2 Tiny across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs DeepSeek VL2 Tiny — which is better?

DeepSeek-V4-Flash-0731 (by DeepSeek) and DeepSeek VL2 Tiny (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.

Choose DeepSeek-V4-Flash-0731 if…

  • you want the most recent training data — it shipped Jul 2026

Choose DeepSeek VL2 Tiny if…

  • you are already invested in the DeepSeek ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Flash-0731 and DeepSeek VL2 Tinydon'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

301.0B diff

DeepSeek-V4-Flash-0731 has 301.0B more parameters than DeepSeek VL2 Tiny, making it 10033.3% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
304.0B
DeepSeek-V4-Flash-0731
3.0B
DeepSeek VL2 Tiny

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Wed Aug 05 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.

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

DeepSeek-V4-Flash-0731

Text
Images
Audio
Video

DeepSeek VL2 Tiny

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 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-V4-Flash-0731

MIT

Open weights

DeepSeek VL2 Tiny

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while DeepSeek VL2 Tiny was released on 2024-12-13.

DeepSeek-V4-Flash-0731 is 20 months newer than DeepSeek VL2 Tiny.

DeepSeek-V4-Flash-0731

Jul 31, 2026

5 days ago

1.6yr newer
DeepSeek VL2 Tiny

Dec 13, 2024

1.6 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (1,048,576 tokens)
DeepSeek
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0731 and DeepSeek VL2 Tiny side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
DeepSeek VL2 Tiny
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
DeepSeek
DeepSeek VL2 Tiny

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs DeepSeek VL2 Tiny.

Which is better, DeepSeek-V4-Flash-0731 or DeepSeek VL2 Tiny?

DeepSeek-V4-Flash-0731 (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.

How does DeepSeek-V4-Flash-0731 compare to DeepSeek VL2 Tiny in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and DeepSeek VL2 Tiny?

DeepSeek-V4-Flash-0731 supports 1.0M 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.

What are the main differences between DeepSeek-V4-Flash-0731 and DeepSeek VL2 Tiny?

Key differences include multimodal support (no vs yes), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

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