DeepSeek VL2 vs DeepSeek VL2 Tiny
DeepSeek VL2 leads the LLM Stats Score 3.1 to -4.5.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek VL2 leads the overall LLM Stats Score 3.1 to -4.5, ranking #299 overall.
In the 14 individual benchmarks reported for both models, DeepSeek VL2 wins 14; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek VL2
- overall performance matters — it scores 3.1 and ranks #299 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 14 of 14 exact shared results
Choose DeepSeek VL2 Tiny
- you are already invested in the DeepSeek ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek VL2 · 14 for DeepSeek VL2 Tiny
DeepSeek VL2 outperforms in 14 benchmarks (AI2D, ChartQA, DocVQA, InfoVQA, MathVista, MMBench, MMBench-V1.1, MME, MMMU, MMStar, MMT-Bench, OCRBench, RealWorldQA, TextVQA), while DeepSeek VL2 Tiny is better at 0 benchmarks.
DeepSeek VL2 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek VL2 has 24.0B more parameters than DeepSeek VL2 Tiny, making it 800.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).
Input capabilities
Documented input modalities across available providers
Both DeepSeek VL2 and DeepSeek VL2 Tiny support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek VL2
DeepSeek VL2 Tiny
License
Usage and distribution terms
Both models are licensed under deepseek.
Both models share the same licensing terms, providing consistent usage rights.
deepseek
Open weights
deepseek
Open weights
Release Timeline
When each model was launched
Both models were released on 2024-12-13.
They likely represent similar generations of model development.
Dec 13, 2024
1.7 years ago
Dec 13, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek VL2 and DeepSeek VL2 Tiny side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek VL2 vs DeepSeek VL2 Tiny.