Model Comparison

DeepSeek VL2 Tiny vs Step-3.5-Flash

Comparing DeepSeek VL2 Tiny and Step-3.5-Flash across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Tiny and Step-3.5-Flash 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
Tue Apr 14 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Tiny
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
StepFun
Step-3.5-Flash
Input tokens$0.10
Output tokens$0.40
Best providerStepFun
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

193.0B diff

Step-3.5-Flash has 193.0B more parameters than DeepSeek VL2 Tiny, making it 6433.3% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
3.0B
DeepSeek VL2 Tiny
196.0B
Step-3.5-Flash

Context Window

Maximum input and output token capacity

Only Step-3.5-Flash specifies input context (65,536 tokens). Only Step-3.5-Flash specifies output context (8,192 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas Step-3.5-Flash does not.

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

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Step-3.5-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Step-3.5-Flash uses Apache 2.0.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Step-3.5-Flash was released on 2026-02-02.

Step-3.5-Flash is 14 months newer than DeepSeek VL2 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.3 years ago

Step-3.5-Flash

Feb 2, 2026

2 months ago

1.1yr 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

Outputs Comparison

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Key Takeaways

DeepSeek
Supports multimodal inputs
StepFun
Larger context window (65,536 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
StepFun
Step-3.5-Flash

FAQ

Common questions about DeepSeek VL2 Tiny vs Step-3.5-Flash

DeepSeek VL2 Tiny (DeepSeek) and Step-3.5-Flash (StepFun) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Step-3.5-Flash scores AIME 2025: 97.3%, Tau-bench: 88.2%, LiveCodeBench v6: 86.4%, IMO-AnswerBench: 85.4%, SWE-Bench Verified: 74.4%.
DeepSeek VL2 Tiny supports an unknown number of tokens and Step-3.5-Flash supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Tiny is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.