Model Comparison

DeepSeek VL2 Tiny vs LongCat-Flash-Thinking

Comparing DeepSeek VL2 Tiny and LongCat-Flash-Thinking across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Tiny and LongCat-Flash-Thinking 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
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Tiny
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

557.0B diff

LongCat-Flash-Thinking has 557.0B more parameters than DeepSeek VL2 Tiny, making it 18566.7% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Meituan
LongCat-Flash-Thinking
560.0Bparameters
3.0B
DeepSeek VL2 Tiny
560.0B
LongCat-Flash-Thinking

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking specifies input context (128,000 tokens). Only LongCat-Flash-Thinking specifies output context (128,000 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas LongCat-Flash-Thinking 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

LongCat-Flash-Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while LongCat-Flash-Thinking uses MIT.

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

DeepSeek VL2 Tiny

deepseek

Open weights

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while LongCat-Flash-Thinking was released on 2025-09-22.

LongCat-Flash-Thinking is 9 months newer than DeepSeek VL2 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.3 years ago

LongCat-Flash-Thinking

Sep 22, 2025

6 months ago

9mo 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Supports multimodal inputs
Meituan
Larger context window (128,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Meituan
LongCat-Flash-Thinking

FAQ

Common questions about DeepSeek VL2 Tiny vs LongCat-Flash-Thinking

DeepSeek VL2 Tiny (DeepSeek) and LongCat-Flash-Thinking (Meituan) 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%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.
DeepSeek VL2 Tiny supports an unknown number of tokens and LongCat-Flash-Thinking supports 128K 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 MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Tiny is developed by DeepSeek and LongCat-Flash-Thinking is developed by Meituan.